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Removed old iterations

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geens
2024-11-24 20:38:01 +01:00
parent a9e70f0a22
commit a0353d0d49
52 changed files with 0 additions and 18084 deletions
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12
iterations/iteration_20241119_162542_776.xml
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<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="21.85"
cpu="0"
disk_total="1081101176832"
disk_used="125096226816"
gpu="0"
memory_total="16630435840"
memory_used="1027158016"
stdin="120"
time="2024-11-19T16:07:26Z"&gt;
&lt;/context&gt;</context><response>&lt;read_stdin/&gt;</response></iteration>

21
iterations/iteration_20241119_162948_334.xml
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@@ -1,21 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="22.87"
cpu="0"
disk_total="1081101176832"
disk_used="125096235008"
gpu="0"
memory_total="16630435840"
memory_used="1025536000"
stdin="0"
time="2024-11-19T16:25:42Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;</response></iteration>

26
iterations/iteration_20241119_163020_423.xml
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@@ -1,26 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="24.16"
cpu="0"
disk_total="1081101176832"
disk_used="125096239104"
gpu="0"
memory_total="16630435840"
memory_used="1026473984"
stdin="0"
time="2024-11-19T16:29:48Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;
ls -la /root/sia
&lt;/single&gt;</response></iteration>

63
iterations/iteration_20241119_163136_262.xml
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@@ -1,63 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="31.32"
cpu="0"
disk_total="1081101176832"
disk_used="125096243200"
gpu="0"
memory_total="16630435840"
memory_used="1026932736"
stdin="0"
time="2024-11-19T16:30:20Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;</response></iteration>

66
iterations/iteration_20241119_163307_840.xml
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@@ -1,66 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="32.87"
cpu="0"
disk_total="1081101176832"
disk_used="125096247296"
gpu="0"
memory_total="16630435840"
memory_used="1010360320"
stdin="0"
time="2024-11-19T16:31:36Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;cat /root/sia/README.md&lt;/single&gt;</response></iteration>

112
iterations/iteration_20241119_163835_085.xml
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@@ -1,112 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="37.15"
cpu="0"
disk_total="1081101176832"
disk_used="125096251392"
gpu="0"
memory_total="16630435840"
memory_used="1013915648"
stdin="0"
time="2024-11-19T16:33:07Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;</response></iteration>

115
iterations/iteration_20241119_164646_153.xml
View File

@@ -1,115 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="38.64"
cpu="0"
disk_total="1081101176832"
disk_used="125096296448"
gpu="0"
memory_total="16630435840"
memory_used="1020993536"
stdin="0"
time="2024-11-19T16:46:30Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;tail -c +1024 /root/sia/README.md&lt;/single&gt;</response></iteration>

163
iterations/iteration_20241119_164906_788.xml
View File

@@ -1,163 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="46.95"
cpu="0"
disk_total="1081101176832"
disk_used="125096304640"
gpu="0"
memory_total="16630435840"
memory_used="1021472768"
stdin="0"
time="2024-11-19T16:46:46Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;</response></iteration>

166
iterations/iteration_20241119_164918_620.xml
View File

@@ -1,166 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="48.45"
cpu="0"
disk_total="1081101176832"
disk_used="125096316928"
gpu="0"
memory_total="16630435840"
memory_used="1022173184"
stdin="0"
time="2024-11-19T16:49:06Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;tail -c +2048 /root/sia/README.md&lt;/single&gt;</response></iteration>

210
iterations/iteration_20241119_164947_226.xml
View File

@@ -1,210 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="53.86"
cpu="0"
disk_total="1081101176832"
disk_used="125096325120"
gpu="0"
memory_total="16630435840"
memory_used="1023418368"
stdin="0"
time="2024-11-19T16:49:18Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
&lt;/reasoning&gt;</response></iteration>

213
iterations/iteration_20241119_164951_032.xml
View File

@@ -1,213 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="55.33"
cpu="0"
disk_total="1081101176832"
disk_used="125096337408"
gpu="0"
memory_total="16630435840"
memory_used="1022693376"
stdin="0"
time="2024-11-19T16:49:47Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;tail -c +3072 /root/sia/README.md&lt;/single&gt;</response></iteration>

260
iterations/iteration_20241119_170030_296.xml
View File

@@ -1,260 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="59.36"
cpu="0"
disk_total="1081101176832"
disk_used="125096398848"
gpu="0"
memory_total="16630435840"
memory_used="1036673024"
stdin="0"
time="2024-11-19T16:55:52Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
&lt;/reasoning&gt;</response></iteration>

265
iterations/iteration_20241119_170826_847.xml
View File

@@ -1,265 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="60.69"
cpu="0"
disk_total="1081101176832"
disk_used="125096472576"
gpu="0"
memory_total="16630435840"
memory_used="1048170496"
stdin="0"
time="2024-11-19T17:07:19Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;
grep -Eb "^#" /root/sia/README.md
&lt;/single&gt;</response></iteration>

310
iterations/iteration_20241119_170913_008.xml
View File

@@ -1,310 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="65.09"
cpu="0"
disk_total="1081101176832"
disk_used="125096484864"
gpu="0"
memory_total="16630435840"
memory_used="1047986176"
stdin="0"
time="2024-11-19T17:08:26Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
&lt;/reasoning&gt;</response></iteration>

315
iterations/iteration_20241119_171140_537.xml
View File

@@ -1,315 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="66.48"
cpu="0"
disk_total="1081101176832"
disk_used="125096501248"
gpu="0"
memory_total="16630435840"
memory_used="1048186880"
stdin="0"
time="2024-11-19T17:09:12Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single limit="3157"&gt;
tail -c +3462 /root/sia/README.md
&lt;/single&gt;</response></iteration>

418
iterations/iteration_20241119_172645_984.xml
View File

@@ -1,418 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="75.41"
cpu="0"
disk_total="1081101176832"
disk_used="125096517632"
gpu="0"
memory_total="16630435840"
memory_used="1049075712"
stdin="0"
time="2024-11-19T17:11:40Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
&lt;/reasoning&gt;</response></iteration>

421
iterations/iteration_20241119_173155_263.xml
View File

@@ -1,421 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="76.58"
cpu="0"
disk_total="1081101176832"
disk_used="125096546304"
gpu="0"
memory_total="16630435840"
memory_used="1046962176"
stdin="0"
time="2024-11-19T17:26:45Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;mkdir /root/notes&lt;/single&gt;</response></iteration>

432
iterations/iteration_20241119_174856_198.xml
View File

@@ -1,432 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="77.34"
cpu="0"
disk_total="1081101176832"
disk_used="125140525056"
gpu="0"
memory_total="16630435840"
memory_used="1040027648"
stdin="0"
time="2024-11-19T17:48:30Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="2ae6dc6a-4329-4a26-8a43-35d1434bf7f1"&gt;
&lt;![CDATA[mkdir /root/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single&gt;
&lt;![CDATA[cat &gt; '/root/notes/user request.txt' &lt;&lt; 'EOF'
2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
EOF]]&gt;
&lt;/single&gt;</response></iteration>

437
iterations/iteration_20241119_175008_071.xml
View File

@@ -1,437 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="78.9"
cpu="0"
disk_total="1081101176832"
disk_used="125140549632"
gpu="0"
memory_total="16630435840"
memory_used="1040867328"
stdin="0"
time="2024-11-19T17:48:56Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="2ae6dc6a-4329-4a26-8a43-35d1434bf7f1"&gt;
&lt;![CDATA[mkdir /root/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="a54ef610-8891-4882-8922-9134cb36020b"&gt;
&lt;![CDATA[
cat &gt; '/root/notes/user request.txt' &lt;&lt; 'EOF'
2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
EOF
]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single&gt;cat '/root/notes/user request.txt'&lt;/single&gt;</response></iteration>

447
iterations/iteration_20241119_175215_856.xml
View File

@@ -1,447 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="80.49"
cpu="0"
disk_total="1081101176832"
disk_used="125140570112"
gpu="0"
memory_total="16630435840"
memory_used="1042337792"
stdin="0"
time="2024-11-19T17:50:08Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="2ae6dc6a-4329-4a26-8a43-35d1434bf7f1"&gt;
&lt;![CDATA[mkdir /root/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="a54ef610-8891-4882-8922-9134cb36020b"&gt;
&lt;![CDATA[
cat &gt; '/root/notes/user request.txt' &lt;&lt; 'EOF'
2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
EOF
]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="5168b21a-dd00-4a29-890a-ceaf126708f9"&gt;
&lt;![CDATA[cat '/root/notes/user request.txt']]&gt;
&lt;stdout&gt;
&lt;![CDATA[2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="a54ef610-8891-4882-8922-9134cb36020b"/&gt;</response></iteration>

436
iterations/iteration_20241119_175424_315.xml
View File

@@ -1,436 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="78.93"
cpu="0"
disk_total="1081101176832"
disk_used="125140590592"
gpu="0"
memory_total="16630435840"
memory_used="1047011328"
stdin="0"
time="2024-11-19T17:52:15Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="2ae6dc6a-4329-4a26-8a43-35d1434bf7f1"&gt;
&lt;![CDATA[mkdir /root/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="5168b21a-dd00-4a29-890a-ceaf126708f9"&gt;
&lt;![CDATA[cat '/root/notes/user request.txt']]&gt;
&lt;stdout&gt;
&lt;![CDATA[2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="2ae6dc6a-4329-4a26-8a43-35d1434bf7f1"/&gt;</response></iteration>

431
iterations/iteration_20241119_175521_331.xml
View File

@@ -1,431 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="78.17"
cpu="0"
disk_total="1081101176832"
disk_used="125140611072"
gpu="0"
memory_total="16630435840"
memory_used="1047564288"
stdin="0"
time="2024-11-19T17:54:24Z"&gt;
&lt;read_stdin id="0cd183e6-3db7-4539-8b10-604f97c03a1e"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="ab67e68c-766f-4602-9237-db99e1f4581c"&gt;
&lt;![CDATA[
I have received instructions to look at the SIA source code located in /root/sia.
I need to identify what features are missing and ensure that unit tests are implemented for my work.
First, I will navigate to the /root/sia directory and list its contents to understand the structure.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="e50ee4a4-8adc-496e-80ef-7cc3aaa8fd0b"
stdout_truncated="true"&gt;
&lt;![CDATA[
ls -la /root/sia
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 200
drwxr-xr-x 1 root root 4096 Nov 19 16:07 .
drwx------ 1 root root 4096 Nov 19 16:07 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 19 16:01 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxr-xr-x 2 root root 4096 Nov 19 16:30 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 218 Nov 12 16:26 run.sh
drwxr-xr-x 1 root root 4096 Nov 19 16:07 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root root 4120 Nov 13 16:05 system_prompt.md
drwxr-xr-x 2 root root 4096 N]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="206f9da6-b57a-46c3-b698-110b18602aab"&gt;
&lt;![CDATA[
I have successfully listed the contents of the /root/sia directory.
The directory contains several files and subdirectories, including a README.md file, a Dockerfile, and various scripts.
The next step is to read the README.md file to understand the project structure and identify any missing features.
I will use the `cat` command to display the contents of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="702b5383-e8df-4bb8-a021-d966bbf9e3fb"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&lt;context
time="2024-10-18T12:00:00Z"
cpu="12"
gpu="26"
memory_used="9556302234"
memory_total="17179869184"
disk_used="244434939904"
disk_total="273145991168"
context="3"
s]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="1e3cc87a-8c0d-4f29-9f0b-89b3825b08e0"&gt;
&lt;![CDATA[
I have successfully read the beginning of the README.md file.
The file provides an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="394be1d8-3a5c-4794-abf2-771cb2e5e8c0"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +1024 /root/sia/README.md]]&gt;
&lt;stdout&gt;
145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other runnin
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="7566562e-feeb-4a4a-b8ff-4eaea93f930b"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="c0ca60ee-05aa-45e8-80f0-fe37c16d0e41"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +2048 /root/sia/README.md]]&gt;
&lt;stdout&gt;
annel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="4a92af78-dc3f-42e7-95e6-b1c7a9630013"&gt;
&lt;![CDATA[
I have successfully read the next part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
The next step is to continue reading the README.md file to understand the project structure and identify any missing features.
I will use the `tail` command to display the next part of the README.md file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="aa347374-0bfd-437c-b692-784dab52898f"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +3072 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[ar initial reasoning.
```xml
&lt;delete id="c92d1594-4487-4a42-a153-f0a99da1762f"/&gt;
```
The conversation is kept in context to understand the user's expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="cb3a2d09-0287-4ca0-9bf2-28f90f3a148e"&gt;
&lt;![CDATA[
I have successfully read another part of the README.md file.
The file continues to provide an overview of the SIA project, including its purpose and how it operates.
I can use the structure of the markdown format to navigate through the file.
I will use the `grep` command to find headings and their offset.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="e5067cb3-036a-4bc1-953b-730bef63d9aa"&gt;
&lt;![CDATA[
grep -Eb "^#" /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="9140a160-c687-4d5d-91c0-cca847d1ce9a"&gt;
&lt;![CDATA[
I have successfully retrieved the headings and their offsets from the README.md file.
This will help me navigate through the file more efficiently.
The next step is to read the section on "Working principles" to understand the core actions and scripts better.
I will use the `tail` command with the appropriate offset and limit to display this full section.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="83bbaded-c55f-4a10-a8f5-e3e97badc842"
limit="3157"
stdout_truncated="true"&gt;
&lt;![CDATA[
tail -c +3462 /root/sia/README.md
]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until they are explicitly removed.
In this way the agent manages what information is available in the context.
#### Single-shot script
The script is executed once.
This is useful for most operations e.g. writing to or moving a file or downloading content from the internet.
The next iteration starts after the scripts has finished.
#### Repeat script
The script is restarted on each iteration.
This is useful for monitoring files or the file system.
commands like `head` and `tail` can be used to limit the data in context.
The next iteration starts after all repeat scripts in context have finished.
### Use of XML
The context and actions are formatted as XML.
For the context this adds clear rules for escaping.
This is usefull in case a previous context is embedded.
The LLM is free to escape data any way it wants,
as long as it results in valid XML.
The response is validated against a schema.
#### XML Data Flow
Entries store their content as raw text. During context compilation, the XML formatter
wraps text content in CDATA sections, except when the content contains CDATA closing sequences.
In those cases, the formatter uses standard XML escaping.
This separation between storage and formatting:
- Keeps entry data clean and unescaped
- Centralizes XML formatting rules
- Makes it easy to change escaping rules without modifying entries
- Allows different formatting for different use cases
The Context is escaped using CDATA blocks.
Except when the data contains CDATA closing sequences.
Then the whole block is escaped using standard XML escaping.
### The SIA process
SIA is typically runs with the `restart.sh` script.
This is a simple shell script that runs SIA in a loop.
When stopped, SIA restarts and reloads the Python files.
This is how SIA can self-update.
SIA can also run SIA processes as script.
This can be used for testing updates to the LLM or core functionality.
### Server for debuggin and human input
SIA can be started with an optional `--server` flag.
This starts a web server that can be used to interact with SIA.
It is made, specifically for reinforcement learning by human feedback.
The web interface takes over standard input and output.
It will display the context for editing before handing it to the LLM.
After each run of the LLM, before parsing, it will display the reasoning and actions.
It interactively displays if the actions can be parsed.
At any time, the user can write to the standard input of SIA.
## Architecture
SIA follows a modular architecture centered around an agent that ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="094d22fd-dc5d-4842-85f0-5d3bf8cd1a7b"&gt;
&lt;![CDATA[
My context usage is high.
This seems like a large task.
I will store the user's request in a notes directory.
Here I can formulate a plan.
I will use the `delete` action to clean up the context as I go.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="5168b21a-dd00-4a29-890a-ceaf126708f9"&gt;
&lt;![CDATA[cat '/root/notes/user request.txt']]&gt;
&lt;stdout&gt;
&lt;![CDATA[2024-11-19T17:31:55Z
The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="0cd183e6-3db7-4539-8b10-604f97c03a1e"/&gt;</response></iteration>

12
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@@ -1,12 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="21.84"
cpu="0"
disk_total="1081101176832"
disk_used="125111201792"
gpu="0"
memory_total="16630431744"
memory_used="965623808"
stdin="31"
time="2024-11-20T10:26:25Z"&gt;
&lt;/context&gt;</context><response>&lt;read_stdin/&gt;</response></iteration>

19
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@@ -1,19 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="22.86"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="972587008"
stdin="0"
time="2024-11-20T10:26:52Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
&lt;/reasoning&gt;</response></iteration>

22
iterations/iteration_20241120_102715_486.xml
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@@ -1,22 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="24.37"
cpu="1"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="957931520"
stdin="0"
time="2024-11-20T10:27:05Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;ls -la /root/sia&lt;/single&gt;</response></iteration>

57
iterations/iteration_20241120_102811_343.xml
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@@ -1,57 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="31.48"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="959979520"
stdin="0"
time="2024-11-20T10:27:15Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
&lt;/reasoning&gt;</response></iteration>

60
iterations/iteration_20241120_102831_256.xml
View File

@@ -1,60 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="33.2"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="962973696"
stdin="0"
time="2024-11-20T10:28:11Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single limit="4096"&gt;head -c 4096 /root/sia/README.md&lt;/single&gt;</response></iteration>

188
iterations/iteration_20241120_103130_266.xml
View File

@@ -1,188 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="51.9"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="963706880"
stdin="0"
time="2024-11-20T10:28:31Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
&lt;/reasoning&gt;</response></iteration>

191
iterations/iteration_20241120_103226_304.xml
View File

@@ -1,191 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="52.76"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="957472768"
stdin="0"
time="2024-11-20T10:31:30Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;grep -Eb "^#" /root/sia/README.md&lt;/single&gt;</response></iteration>

237
iterations/iteration_20241120_103917_823.xml
View File

@@ -1,237 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="57.15"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="963469312"
stdin="0"
time="2024-11-20T10:32:26Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
&lt;/reasoning&gt;</response></iteration>

240
iterations/iteration_20241120_104056_264.xml
View File

@@ -1,240 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="58.39"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="972505088"
stdin="0"
time="2024-11-20T10:39:17Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;head -c 668 /root/sia/README.md&lt;/single&gt;</response></iteration>

259
iterations/iteration_20241120_104401_650.xml
View File

@@ -1,259 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="60.9"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="973791232"
stdin="0"
time="2024-11-20T10:40:56Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single limit="266"&gt;tail -c +6619 /root/sia/README.md&lt;/single&gt;</response></iteration>

276
iterations/iteration_20241120_104619_581.xml
View File

@@ -1,276 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="62.74"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="976801792"
stdin="0"
time="2024-11-20T10:44:01Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single limit="9624"&gt;tail -c +10351 /root/sia/README.md&lt;/single&gt;</response></iteration>

665
iterations/iteration_20241120_104703_413.xml
View File

@@ -1,665 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="89.73"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="976543744"
stdin="0"
time="2024-11-20T10:46:19Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;reasoning id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"&gt;
&lt;![CDATA[
I have received a message from the user indicating that the SIA source code is located in /root/sia. The user also mentioned that not all features are implemented yet and that I should look at the readme and code to find what is missing. Additionally, the user instructed me to unit test my work.
My next step will be to list the contents of the /root/sia directory to understand its structure and identify the readme file.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="d8ed5b92-cecb-43bf-a019-63bb9fd8ab64"/&gt;</response></iteration>

658
iterations/iteration_20241120_104742_889.xml
View File

@@ -1,658 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="88.22"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="979644416"
stdin="0"
time="2024-11-20T10:47:03Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="16421800-daa4-46f3-b619-e4efbafb448b"&gt;
&lt;![CDATA[
The listing of the /root/sia directory shows several files and directories. The README.md file is present, which I should read to understand the project better. Additionally, there are directories like .git, _test, iterations, sia, and static, as well as various scripts and configuration files.
My next step will be to read the README.md file to get an overview of the project and identify what features are missing.
Since it is a large file I will only read a part of it.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="16421800-daa4-46f3-b619-e4efbafb448b"/&gt;</response></iteration>

650
iterations/iteration_20241120_104810_545.xml
View File

@@ -1,650 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="86.5"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="983642112"
stdin="0"
time="2024-11-20T10:47:42Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"
limit="4096"&gt;
&lt;![CDATA[head -c 4096 /root/sia/README.md]]&gt;
&lt;stdout&gt;
# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
## Example
This example shows a typical context with some monitored items and previous actions.
Between each of the responses, the context would be updated.
### Context
```xml
&amp;lt;context
time=&amp;quot;2024-10-18T12:00:00Z&amp;quot;
cpu=&amp;quot;12&amp;quot;
gpu=&amp;quot;26&amp;quot;
memory_used=&amp;quot;9556302234&amp;quot;
memory_total=&amp;quot;17179869184&amp;quot;
disk_used=&amp;quot;244434939904&amp;quot;
disk_total=&amp;quot;273145991168&amp;quot;
context=&amp;quot;3&amp;quot;
stdin=&amp;quot;0&amp;quot;
/&amp;gt;
&amp;lt;repeat id=&amp;quot;a3d89ee5-28ec-4c5a-b9e9-a30af53d43a0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 16K
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 ../
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 tasks/
drwxr-xr-x 1 sia 1049089 0 Oct 28 13:40 user/
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;be8070f8-dbd2-47ee-a208-defe6fd49ae0&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[ls -lah /tasks]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[total 0
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ./
drwxr-xr-x 1 ngeens 1049089 0 Oct 28 13:40 ../
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;repeat id=&amp;quot;375e1657-8140-456b-bda4-a8690bc4b3fb&amp;quot; exit_code=&amp;quot;0&amp;quot;&amp;gt;
&amp;lt;![CDATA[cat /user/general_info.txt]]&amp;gt;
&amp;lt;stdout&amp;gt;&amp;lt;![CDATA[Name: John (I don&amp;apos;t know his last name)
Location: Somewhere in Belgium
]]&amp;gt;&amp;lt;/stdout&amp;gt;
&amp;lt;stderr/&amp;gt;
&amp;lt;/repeat&amp;gt;
&amp;lt;reasoning id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;&amp;gt;&amp;lt;![CDATA[There is data available on the standard input channel. I have no other running tasks to tend to and there is room in the context. I should read the standard input.]]&amp;gt;&amp;lt;/reasoning&amp;gt;
&amp;lt;read_stdin id=&amp;quot;5361ad0d-3ed1-4567-9f5a-70f3b462fd8d&amp;quot;&amp;gt;&amp;lt;![CDATA[Remind me to feed the cat tomorrow morning]]&amp;gt;&amp;lt;/read_stdin&amp;gt;
&amp;lt;/context&amp;gt;
```
### Responses
Start by reasoning about the task.
```xml
&amp;lt;reasoning&amp;gt;
John did not specify an exact time.
I&amp;apos;ll suggest 9am.
He also did not specify how to be reminded.
I&amp;apos;ll ask but if he doesn&amp;apos;t respond I&amp;apos;ll assume a text message on standard output is fine.
I&amp;apos;ll write down this task in a file so I remember it even on a power failure.
&amp;lt;/reasoning&amp;gt;
```
Store important information on disk.
```xml
&amp;lt;script&amp;gt;&amp;lt;![CDATA[echo &amp;apos;Remind John to feed the cat on 2024-10-18T09:00:00+02:00. Use standard output.&amp;apos; &amp;gt; /tasks/reminder_to_feed_cat.txt]]&amp;gt;&amp;lt;/script&amp;gt;
```
Respond to the user.
```xml
&amp;lt;write_stdout&amp;gt;I&amp;apos;ll remind you to feed the cat tomorrow morning at 9am. Is a message on the standard output ok?&amp;lt;/write_stdout&amp;gt;
```
Clear initial reasoning.
```xml
&amp;lt;delete id=&amp;quot;c92d1594-4487-4a42-a153-f0a99da1762f&amp;quot;/&amp;gt;
```
The conversation is kept in context to understand the user&amp;apos;s expected response.
If the context was near full, it would be summarized and cleaned up.
The `script` output is also kept in context.
If the file was updated often, it could be replaced by a repeated `cat`, like the general info.
## Working principles
The main context is regenerated for each iteration.
It contains info about the system and previous actions that have not been deleted.
Together with the system prompt and available core actions it forms the prompt for the LLM.
The LLM responds with one core action.
### Core Actions
There are only a few core actions:
- Starting a script
- Deleting data from context
- Stopping SIA
- Reading standard input
- Writing to standard output
- Reasoning
### Scripts
Scripts can run in one of 2 modes: single-shot or repeat.
Their mode and output (stdout and stderr) stay in the context until t
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="f5f8f1d0-f956-46c3-a942-ebac7a0ccf6a"/&gt;</response></iteration>

525
iterations/iteration_20241120_104829_581.xml
View File

@@ -1,525 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="67.8"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="981872640"
stdin="0"
time="2024-11-20T10:48:10Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"&gt;
&lt;![CDATA[
I can use the markdown headings to identify interesting sections.
I will try to find sections containing details about what needs to be implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="554ffbc2-2a90-423b-aafe-ed90dd66b73b"/&gt;</response></iteration>

519
iterations/iteration_20241120_104912_967.xml
View File

@@ -1,519 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="66.94"
cpu="0"
disk_total="1081101176832"
disk_used="125111205888"
gpu="0"
memory_total="16630431744"
memory_used="983924736"
stdin="0"
time="2024-11-20T10:48:29Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single
exit_code="0"
id="8637bd02-7c94-4708-bfa3-bf840d376166"
stdout_truncated="true"&gt;
&lt;![CDATA[ls -la /root/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 204
drwxr-xr-x 1 root root 4096 Nov 20 10:25 .
drwx------ 1 root root 4096 Nov 20 10:26 ..
drwxr-xr-x 2 root root 4096 Oct 31 17:07 .crossnote
-rwxr-xr-x 1 root root 14 Nov 4 16:01 .dockerignore
drwxr-xr-x 8 root root 4096 Nov 20 10:21 .git
-rwxr-xr-x 1 root root 30 Nov 4 16:01 .gitignore
-rwxr-xr-x 1 root root 843 Nov 4 14:52 Dockerfile
-rwxr-xr-x 1 root root 19975 Nov 19 14:20 README.md
drwxr-xr-x 2 root root 4096 Nov 15 16:10 _test
-rwxr-xr-x 1 root root 3923 Nov 13 15:56 action_schema.xsd
-rwxr-xr-x 1 root root 2064 Nov 6 12:29 claude.sh
-rwxr-xr-x 1 root root 85153 Nov 14 13:30 claude.txt
-rwxr-xr-x 1 root root 4939 Nov 20 10:07 finetune_dataset_creator.py
-rwxr-xr-x 1 root root 572 Nov 19 14:20 install.sh
drwxrwxrwx 1 root root 512 Nov 20 10:27 iterations
-rwxr-xr-x 1 root root 105 Nov 19 14:20 requirements.txt
-rwxr-xr-x 1 root root 269 Nov 19 18:05 run.sh
drwxr-xr-x 1 root root 4096 Nov 20 10:26 sia
drwxr-xr-x 3 root root 4096 Nov 19 16:01 static
-rwxr-xr-x 1 root r]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="8637bd02-7c94-4708-bfa3-bf840d376166"/&gt;</response></iteration>

492
iterations/iteration_20241120_105155_821.xml
View File

@@ -1,492 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="59.83"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="985358336"
stdin="0"
time="2024-11-20T10:49:12Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
&lt;/reasoning&gt;</response></iteration>

495
iterations/iteration_20241120_105234_376.xml
View File

@@ -1,495 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="60.84"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="991342592"
stdin="0"
time="2024-11-20T10:51:55Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"&gt;
&lt;![CDATA[
The diagrams section can help me navigate the source files.
I will load this section in memory.
The introduction and first part of the architecture are probably also interesting.
I will load these 3 sections, keep the user request and heading overview.
Other context items can be removed.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;delete id="78103067-d3c4-4606-9ed3-c5c8c5e9ba21"/&gt;</response></iteration>

486
iterations/iteration_20241120_105312_809.xml
View File

@@ -1,486 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="59.6"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="993644544"
stdin="0"
time="2024-11-20T10:52:34Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single limit="10000"&gt;ls -l /root/sia/sia&lt;/single&gt;</response></iteration>

531
iterations/iteration_20241120_105346_117.xml
View File

@@ -1,531 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="72.27"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="993153024"
stdin="0"
time="2024-11-20T10:53:12Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single&gt;cat /root/sia/sia/base_agent.py&lt;/single&gt;</response></iteration>

575
iterations/iteration_20241120_105546_316.xml
View File

@@ -1,575 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="75.89"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="993280000"
stdin="0"
time="2024-11-20T10:53:46Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="eb4dfc2c-9586-4dc0-baf4-efd70d572abd"
stdout_truncated="true"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single&gt;cat /root/sia/sia/web_agent.py&lt;/single&gt;</response></iteration>

531
iterations/iteration_20241120_105718_454.xml
View File

@@ -1,531 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="72.27"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="991608832"
stdin="0"
time="2024-11-20T10:56:44Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;single limit="3072"&gt;cat /root/sia/sia/base_agent.py&lt;/single&gt;</response></iteration>

630
iterations/iteration_20241120_110108_648.xml
View File

@@ -1,630 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="81.34"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="991567872"
stdin="0"
time="2024-11-20T10:57:18Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;reasoning&gt;
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
&lt;/reasoning&gt;</response></iteration>

633
iterations/iteration_20241120_110116_096.xml
View File

@@ -1,633 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="82.52"
cpu="0"
disk_total="1081101176832"
disk_used="125111209984"
gpu="0"
memory_total="16630431744"
memory_used="996315136"
stdin="0"
time="2024-11-20T11:01:08Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;/context&gt;</context><response>&lt;single&gt;mkdir /root/sia/notes&lt;/single&gt;</response></iteration>

638
iterations/iteration_20241120_110239_478.xml
View File

@@ -1,638 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="83.34"
cpu="0"
disk_total="1081101176832"
disk_used="125111214080"
gpu="0"
memory_total="16630431744"
memory_used="994213888"
stdin="0"
time="2024-11-20T11:01:16Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="a9a8e48a-6c5f-42d3-884d-a616921a2a52"&gt;
&lt;![CDATA[mkdir /root/sia/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;repeat&gt;tail -v -n +1 /root/sia/notes/*&lt;/repeat&gt;</response></iteration>

651
iterations/iteration_20241120_110710_079.xml
View File

@@ -1,651 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="84.56"
cpu="0"
disk_total="1081101176832"
disk_used="125111214080"
gpu="0"
memory_total="16630431744"
memory_used="993923072"
stdin="0"
time="2024-11-20T11:02:39Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="a9a8e48a-6c5f-42d3-884d-a616921a2a52"&gt;
&lt;![CDATA[mkdir /root/sia/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;repeat
exit_code="1"
id="29babba9-a49a-4ffb-b506-1ef929b834c2"
limit="1024"&gt;
&lt;![CDATA[tail -v -n +1 /root/sia/notes/*]]&gt;
&lt;stdout/&gt;
&lt;stderr&gt;
&lt;![CDATA[tail: cannot open '/root/sia/notes/*' for reading: No such file or directory
]]&gt;
&lt;/stderr&gt;
&lt;/repeat&gt;
&lt;/context&gt;</context><response>&lt;single&gt;echo "BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
" &gt; /root/sia/notes/base_agent.txt&lt;/single&gt;</response></iteration>

657
iterations/iteration_20241120_110909_721.xml
View File

@@ -1,657 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="85.66"
cpu="0"
disk_total="1081101176832"
disk_used="125111222272"
gpu="0"
memory_total="16630431744"
memory_used="981004288"
stdin="0"
time="2024-11-20T11:07:10Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;single exit_code="0" id="a9a8e48a-6c5f-42d3-884d-a616921a2a52"&gt;
&lt;![CDATA[mkdir /root/sia/notes]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;repeat
exit_code="0"
id="29babba9-a49a-4ffb-b506-1ef929b834c2"
limit="1024"&gt;
&lt;![CDATA[tail -v -n +1 /root/sia/notes/*]]&gt;
&lt;stdout/&gt;
&lt;stderr&gt;
==&gt; /root/sia/notes/base_agent.txt &lt;==
BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
&lt;/stderr&gt;
&lt;/repeat&gt;
&lt;single exit_code="0" id="a4af2309-ed76-4d53-ae92-a22d5caf4085"&gt;
&lt;![CDATA[echo "BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
" &gt; /root/sia/notes/base_agent.txt]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="a9a8e48a-6c5f-42d3-884d-a616921a2a52"/&gt;</response></iteration>

652
iterations/iteration_20241120_110951_671.xml
View File

@@ -1,652 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="84.92"
cpu="0"
disk_total="1081101176832"
disk_used="125111222272"
gpu="0"
memory_total="16630431744"
memory_used="976871424"
stdin="0"
time="2024-11-20T11:09:09Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;repeat
exit_code="0"
id="29babba9-a49a-4ffb-b506-1ef929b834c2"
limit="1024"&gt;
&lt;![CDATA[tail -v -n +1 /root/sia/notes/*]]&gt;
&lt;stdout/&gt;
&lt;stderr&gt;
==&gt; /root/sia/notes/base_agent.txt &lt;==
BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
&lt;/stderr&gt;
&lt;/repeat&gt;
&lt;single exit_code="0" id="a4af2309-ed76-4d53-ae92-a22d5caf4085"&gt;
&lt;![CDATA[echo "BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
" &gt; /root/sia/notes/base_agent.txt]]&gt;
&lt;stdout/&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;/context&gt;</context><response>&lt;delete id="a4af2309-ed76-4d53-ae92-a22d5caf4085"/&gt;</response></iteration>

646
iterations/iteration_20241120_111033_386.xml
View File

@@ -1,646 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="83.82"
cpu="0"
disk_total="1081101176832"
disk_used="125111222272"
gpu="0"
memory_total="16630431744"
memory_used="979468288"
stdin="0"
time="2024-11-20T11:09:51Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c83a4145-a43d-4b78-856b-6d81da1fad76"
limit="3072"&gt;
&lt;![CDATA[cat /root/sia/sia/base_agent.py]]&gt;
&lt;stdout&gt;
&lt;![CDATA[from abc import ABC
import xml.etree.ElementTree as ET
from .llm_engine import LlmEngine
from .response_parser import ResponseParser
from .system_metrics import SystemMetrics
from .util import pretty_print_element
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
class BaseAgent(ABC):
"""
Abstract base class for SIA agents.
Provides core functionality for maintaining working memory, system metrics,
and coordinating components for LLM inference.
"""
def __init__(
self,
system_prompt: str,
action_schema: str,
working_memory: WorkingMemory,
metrics: SystemMetrics,
llm: LlmEngine,
validator: XMLValidator,
parser: ResponseParser,
):
"""
Initialize agent with required components.
"""
self._system_prompt = system_prompt
self._action_schema = action_schema
self._working_memory = working_memory
self._metrics = metrics
self._llm = llm
self._validator = validator
self._parser = parser
def __del__(self):
"""Clean up resources on deletion."""
if hasattr(self, '_metrics'):
self._metrics.stop()
@property
def system_prompt(self) -&gt; str:
"""Get the system prompt."""
return f"{self._system_prompt}\n{self._action_schema}"
def _compile_context(self) -&gt; str:
"""
Compile the current context for LLM inference.
Includes system metrics and working memory entries.
Returns:
str: Complete context as XML string
"""
memory_context = self._working_memory.generate_context()
metrics_data = self._metrics.get_metrics()
# Create context element
context = ET.Element("context")
context.set("time", metrics_data["timestamp"])
context.set("cpu", str(metrics_data["cpu"]))
context.set("gpu", str(metrics_data["gpu"]))
context.set("memory_used", str(metrics_data["memory_used"]))
context.set("memory_total", str(metrics_data["memory_total"]))
context.set("disk_used", str(metrics_data["disk_used"]))
context.set("disk_total", str(metrics_data["disk_total"]))
context.set("stdin", str(self._parser.io_buffer.buffer_length()))
context.set("context", "100")
for entry in memory_context:
context.append(entry)
context_str = pretty_print_element(context)
# Calculate token usage percentage
token_count = self._llm.token_count(self.system_prompt, context_str)
token_limit = self._llm.token_limit()
context_usage = (float(token_count) / float(token_limit)) * 100.0
# Update context usage metric
context.set("context", str(round(context_usage, 2)))
return pretty_print_element(context)]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;repeat
exit_code="0"
id="29babba9-a49a-4ffb-b506-1ef929b834c2"
limit="1024"&gt;
&lt;![CDATA[tail -v -n +1 /root/sia/notes/*]]&gt;
&lt;stdout/&gt;
&lt;stderr&gt;
==&gt; /root/sia/notes/base_agent.txt &lt;==
BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
&lt;/stderr&gt;
&lt;/repeat&gt;
&lt;/context&gt;</context><response>&lt;delete id="c83a4145-a43d-4b78-856b-6d81da1fad76"
/&gt;</response></iteration>

550
iterations/iteration_20241120_111153_435.xml
View File

@@ -1,550 +0,0 @@
<?xml version='1.0' encoding='utf-8'?>
<iteration system_prompt_hash="a357171f34284409058700f0d6c20cbb4f4bfe643aff5b12168c5158767f89b4" action_schema_hash="a4cf87f3d53c7b14aab3c96097d8b7bf838e8f77e413d11f51051afbe22fa3a6"><context>&lt;context
context="74.75"
cpu="0"
disk_total="1081101176832"
disk_used="125111222272"
gpu="0"
memory_total="16630431744"
memory_used="981422080"
stdin="0"
time="2024-11-20T11:10:33Z"&gt;
&lt;read_stdin id="3da7f743-19b7-4738-aaf9-49634618e8f7"&gt;
&lt;![CDATA[The SIA source is located in /root/sia. Not all features are implemented yet. Look at the readme and code to find what is missing. Make sure to unit test your work.]]&gt;
&lt;/read_stdin&gt;
&lt;single exit_code="0" id="ac690fe5-45d0-4028-8120-107c318977a9"&gt;
&lt;![CDATA[grep -Eb "^#" /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[0:# SIA - The Self Improving Agent
668:## Example
832:### Context
2323:### Responses
3462:## Working principles
3759:### Core Actions
3953:### Scripts
4204:#### Single-shot script
4433:#### Repeat script
4711:### Use of XML
5022:#### XML Data Flow
5705:### The SIA process
6048:### Server for debuggin and human input
6619:## Architecture
6885:### Core Components
6908:#### Agent Architecture
7521:#### Working Memory
8059:#### Command Processing
8490:#### IO Handling
8787:### Processing Flow
8810:#### Standard Agent Flow
9109:#### Web Agent Flow
9472:### Web Interface
9600:#### Server-Client Communication
9932:#### WebServer Architecture
10351:### Diagrams
10367:#### Core classes
12662:#### Standard Agent Flow
13387:#### Web Agent
15536:#### Web Agent Flow
16522:#### Entry classes
18459:#### IO Buffer classes
19156:#### Command classes
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single exit_code="0" id="79f5a8b7-cc57-44c3-b942-c74e3bcabcf8"&gt;
&lt;![CDATA[head -c 668 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[# SIA - The Self Improving Agent
SIA is an agentic artificial intelligence system that autonomously completes complex tasks by writing and executing scripts.
It uses a Large Language Model (LLM) which operates in a loop.
Each iteration a context is updated with system info and a list of previous reasoning and actions.
The agent responds with a new reasoning or an action.
Context, reasoning and actions are stored in a file for each iteration.
SIA can read past iterations to improve its reasoning and actions.
It can improve in two ways:
- By finetuning the LLM with a better reasoning or action for a given context
- By modifying its own source code
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="c0aad1a9-48d4-46cd-bd5f-70230566b442"
limit="266"
stdout_truncated="true"&gt;
&lt;![CDATA[tail -c +6619 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
## Architecture
SIA follows a modular architecture centered around an agent that processes context through an LLM to generate actions.
The system can run in two modes: a standard command-line mode and an interactive web mode for debugging and human feedback.
### ]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;single
exit_code="0"
id="973d9034-7076-479a-afea-4aaf81b065be"
limit="9624"&gt;
&lt;![CDATA[tail -c +10351 /root/sia/README.md]]&gt;
&lt;stdout&gt;
&lt;![CDATA[
### Diagrams
#### Core classes
```mermaid
classDiagram
class SystemMetrics {
+SystemMetrics(sample_interval float)
+generate_context(context_usage float) ElementTree
+stop() void
-monitor_loop() void
}
class LLMEngine {
+LLMEngine(model_path str)
+set_model_path(model_path str) void
+infer(system_prompt str, main_context str) Iterator~str~
}
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class WorkingMemory {
-entries: List~Entry~
+WorkingMemory()
+add_entry(entry Entry) void
+remove_entry(id str) void
+clear() void
+get_entry(id str) Optional~Entry~
+get_entries() List~Entry~
+get_entries_count() int
+get_entries_by_type(type Type) List~Entry~
+update() void
+generate_context() List~ElementTree~
}
class XMLValidator {
+XMLValidator(schema str)
+validate(xml str) Optional~str~
+get_valid_root_elements() Set~str~
}
class ResponseParser {
-io_buffer: IOBuffer
+ResponseParser(io_buffer IOBuffer)
+parse(xml str) Command | Entry
}
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
SystemMetrics "1" --* "1" BaseAgent
LLMEngine "1" --* "1" BaseAgent
XMLValidator "1" --* "1" BaseAgent
BaseAgent "1" *-- "1" IOBuffer
BaseAgent "1" *-- "1" WorkingMemory
BaseAgent "1" *-- "1" ResponseParser
WorkingMemory "1" *-- "*" Entry
ResponseParser ..&gt; Entry
ResponseParser ..&gt; Command
```
#### Standard Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Standard Agent Flow" as standard_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; ProcessLLM
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; ParseResponse: Valid XML
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Web Agent
```mermaid
classDiagram
class BaseAgent {
&lt;&lt;abstract&gt;&gt;
-working_memory: WorkingMemory
-metrics: SystemMetrics
-llm: LLMEngine
-parser: ResponseParser
-validator: XMLValidator
-action_schema: str
#_compile_context() str
}
class StandardAgent {
+StandardAgent(model_path str, system_prompt str, action_schema str)
+run() void
}
class WebAgent {
+context: str
+response: str readonly
+current_state WebAgentState readonly
+command_result Optional[CommandResult] readonly
+validation_error Optional[str] readonly
+add_state_change_handler(handler Callable) void
+add_response_change_handler(handler Callable) void
+approve_context() void
+set__response(response str) void
+approve_response() void
}
class WebAgentState {
&lt;&lt;enumeration&gt;&gt;
UPDATE
CONTEXT_APPROVAL
INFERENCE
RESPONSE_APPROVAL
STOPPED
}
class WebSocketManager {
-web_sockets: Set~WebSocket~
+WebServer(agent WebAgent, io_buffer WebIOBuffer, static_files path, host str, port int)
}
class ClientMessage {
&lt;&lt;enumeration&gt;&gt;
APPROVE_CONTEXT
APPROVE_RESPONSE
MODIFY_RESPONSE
SEND_INPUT
}
class ServerMessage {
&lt;&lt;enumeration&gt;&gt;
STATE_CHANGE
CONTEXT_UPDATE
RESPONSE_UPDATE
OUTPUT_UPDATE
VALIDATION_ERROR
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
BaseAgent &lt;|-- WebAgent
BaseAgent &lt;|-- StandardAgent
WebServer --&gt; ClientMessage
WebServer --&gt; ServerMessage
WebServer "1" *-- "1" WebIOBuffer
WebServer "1" *-- "1" WebAgent
WebAgent "1" *-- "1" WebAgentState
```
#### Web Agent Flow
```mermaid
stateDiagram-v2
direction LR
state "Web Agent Flow" as web_agent_flow {
[*] --&gt; UpdateSystem: Start
UpdateSystem --&gt; CompileContext: Updated Metrics &amp; Size
CompileContext --&gt; WaitForContextApproval: Send Context
WaitForContextApproval --&gt; ProcessLLM: Context Approved
ProcessLLM --&gt; ValidateXML: LLM Response
ValidateXML --&gt; WaitForResponseApproval: Send Validation Result
ValidateXML --&gt; UpdateEntries: Invalid XML\nCreate ParseErrorEntry
WaitForResponseApproval --&gt; ValidateXML: Modified Response
WaitForResponseApproval --&gt; ParseResponse: Approved Response
ParseResponse --&gt; ExecuteCommands: Command
ParseResponse --&gt; UpdateEntries: Entry
ExecuteCommands --&gt; [*]: Stop Command
ExecuteCommands --&gt; UpdateEntries: Delete Command
UpdateEntries --&gt; UpdateSystem: Continue Loop
}
```
#### Entry classes
```mermaid
classDiagram
class Entry {
&lt;&lt;abstract&gt;&gt;
+id: str readonly
+timestamp: datetime readonly
+Entry(id str, timestamp datetime)
+update() void*
+generate_context() ElementTree*
+cleanup() void*
}
class ScriptEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+Script(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class RepeatEntry {
+script: str readonly
+stdout: str readonly
+stderr: str readonly
+exit_code: Optional~int~ readonly
+RepeatEntry(script str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReasoningEntry {
+content: str readonly
+ReasoningEntry(content str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ParseErrorEntry {
+content: str readonly
+error: str readonly
+ParseErrorEntry(content str, error str, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class ReadEntry {
+content: str readonly
+ReadEntry(io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
class WriteEntry {
+content: str readonly
+WriteEntry(content str, io_buffer IOBuffer, id str, timestamp datetime)
+update() void
+generate_context() ElementTree
}
ReasoningEntry --|&gt; Entry
ParseErrorEntry --|&gt; Entry
ReadEntry --|&gt; Entry
Entry &lt;|-- WriteEntry
Entry &lt;|-- ScriptEntry
Entry &lt;|-- RepeatEntry
```
#### IO Buffer classes
```mermaid
classDiagram
class IOBuffer {
&lt;&lt;interface&gt;&gt;
+read() str*
+write(content str) void*
+buffer_length() int*
}
class StandardIOBuffer {
+StandardIOBuffer()
+read() str
+write(content str) void
+buffer_length() int
}
class WebIOBuffer {
-stdin_buffer: str
-stdout_buffer: str
+read() str
+write(content str) void
+buffer_length() int
+append_stdin(content str) void
+get_stdout() str
+clear_stdout() void
}
IOBuffer &lt;|.. WebIOBuffer
IOBuffer &lt;|.. StandardIOBuffer
```
#### Command classes
```mermaid
classDiagram
direction LR
class Command {
&lt;&lt;abstract&gt;&gt;
+execute(memory WorkingMemory) CommandResult*
}
class DeleteCommand {
+DeleteCommand(id str)
+execute(memory WorkingMemory) CommandResult
}
class StopCommand {
+StopCommand()
+execute(memory WorkingMemory) CommandResult
}
class CommandResult {
+message: str
+success: bool
+should_stop: bool
+CommandResult(message str, success bool, should_stop bool)
+static success() CommandResult
+static failure(message str) CommandResult
+static stop() CommandResult
}
Command &lt;|-- DeleteCommand
Command &lt;|-- StopCommand
Command -- CommandResult
```
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="869e20e9-48ef-4223-b901-09796f4e0627"&gt;
&lt;![CDATA[
The diagrams give a good overview of which classes to expect.
I will explore the `/root/sia/sia` directory to see which of these classes are already implemented.
]]&gt;
&lt;/reasoning&gt;
&lt;single
exit_code="0"
id="fa7effb0-a1ce-468f-b556-c971f24dca54"
limit="10000"&gt;
&lt;![CDATA[ls -l /root/sia/sia]]&gt;
&lt;stdout&gt;
&lt;![CDATA[total 172
-rwxr-xr-x 1 root root 0 Oct 22 11:48 __init__.py
-rwxr-xr-x 1 root root 4977 Nov 19 14:20 __main__.py
drwxr-xr-x 2 root root 4096 Nov 20 10:26 __pycache__
-rwxr-xr-x 1 root root 5943 Nov 15 15:54 auto_approver.py
-rwxr-xr-x 1 root root 5242 Nov 13 16:31 background_entry.py
-rwxr-xr-x 1 root root 3072 Nov 19 13:45 base_agent.py
-rwxr-xr-x 1 root root 722 Nov 4 09:50 command.py
-rwxr-xr-x 1 root root 1113 Nov 4 09:50 command_result.py
-rwxr-xr-x 1 root root 5865 Nov 19 13:41 config.py
-rwxr-xr-x 1 root root 1337 Nov 4 09:50 delete_command.py
-rwxr-xr-x 1 root root 1537 Nov 4 09:50 entry.py
-rwxr-xr-x 1 root root 2620 Nov 14 15:16 hf_llm_engine.py
-rwxr-xr-x 1 root root 1082 Nov 4 09:50 io_buffer.py
-rwxr-xr-x 1 root root 1683 Nov 19 13:54 iteration_logger.py
-rwxr-xr-x 1 root root 385 Nov 14 14:21 llm_engine.py
-rwxr-xr-x 1 root root 4018 Nov 19 14:20 local_llm_engine.py
-rwxr-xr-x 1 root root 2269 Nov 19 14:20 mistral_llm_engine.py
-rwxr-xr-x 1 root root 2407 Nov 19 14:20 openai_llm_engine.py
-rwxr-xr-x 1 root root 1632 Nov 13 15:40 parse_error_entry.py
-rwxr-xr-x 1 root root 1744 Nov 13 15:39 read_entry.py
-rwxr-xr-x 1 root root 1323 Nov 13 15:38 reasoning_entry.py
-rwxr-xr-x 1 root root 4127 Nov 19 14:20 repeat_entry.py
-rwxr-xr-x 1 root root 5916 Nov 19 14:20 response_parser.py
-rwxr-xr-x 1 root root 4173 Nov 19 14:20 single_entry.py
-rwxr-xr-x 1 root root 2074 Nov 4 09:50 standard_io_buffer.py
-rwxr-xr-x 1 root root 908 Nov 4 09:50 stop_command.py
-rwxr-xr-x 1 root root 4152 Nov 14 13:36 system_metrics.py
-rwxr-xr-x 1 root root 2510 Nov 12 16:17 util.py
-rwxr-xr-x 1 root root 7818 Nov 19 13:54 web_agent.py
-rwxr-xr-x 1 root root 2039 Nov 12 16:17 web_io_buffer.py
-rwxr-xr-x 1 root root 6968 Nov 15 12:48 web_socket_manager.py
-rwxr-xr-x 1 root root 3638 Nov 13 16:35 working_memory.py
-rwxr-xr-x 1 root root 1688 Nov 13 15:41 write_entry.py
-rwxr-xr-x 1 root root 3992 Nov 4 09:50 xml_validator.py
]]&gt;
&lt;/stdout&gt;
&lt;stderr/&gt;
&lt;/single&gt;
&lt;reasoning id="addd6ca0-9623-474e-88f1-6d9cfa6d5a85"&gt;
&lt;![CDATA[
Looking at BaseAgent I can see it is a close match to the diagram with some small differences.
I will create a notes directory where I will list differences between the schemas and the implementation.
I will go over each file or class in the diagram in alphabetical order.
]]&gt;
&lt;/reasoning&gt;
&lt;repeat
exit_code="0"
id="29babba9-a49a-4ffb-b506-1ef929b834c2"
limit="1024"&gt;
&lt;![CDATA[tail -v -n +1 /root/sia/notes/*]]&gt;
&lt;stdout/&gt;
&lt;stderr&gt;
==&gt; /root/sia/notes/base_agent.txt &lt;==
BaseAgent:
- The implementation has a public system_prompt property that is not mentioned in the diagram.
&lt;/stderr&gt;
&lt;/repeat&gt;
&lt;/context&gt;</context><response>&lt;single limit="4977"&gt;cat /root/sia/sia/__main__.py&lt;/single&gt;</response></iteration>