Start work on docker module

This commit is contained in:
2024-10-24 08:39:31 +02:00
parent ab03e6836b
commit 4bbe636f0e
8 changed files with 532 additions and 30 deletions

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@@ -10,4 +10,12 @@ RUN mkdir -p /root/model
CMD ["python3", "-m", "unittest", "discover", "-v", "-p", "*test.py", "-v"]
FROM requirements
RUN apt update
RUN apt install -y \
apt-transport-https ca-certificates \
curl software-properties-common
RUN curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -
RUN add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu bionic stable"
RUN apt update
RUN apt install -y docker-ce
CMD ["python3", "-m", "sia"]

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@@ -1,2 +1,3 @@
transformers
docker
torch
transformers

28
run.sh Executable file
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@@ -0,0 +1,28 @@
#!/bin/bash
# Continue on error
set -e
# Build with progress output and capture the tag
TAG=$( \
docker build \
. \
2>&1 | tee /dev/tty | grep "writing image" | cut -d' ' -f4 \
)
# Exit if tag is empty
[ -z "$TAG" ] && exit 1
# Run tests
docker run \
--rm \
-ti \
--gpus=all \
--privileged \
-v /$(pwd)/model/:/root/model/ \
$TAG \
-c "/bin/bash"
#/etc/init.d/docker start
# Clean up image
[ ! -z "$TAG" ] && docker rmi $TAG

254
sia/docker_module.py Normal file
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@@ -0,0 +1,254 @@
from typing import Dict, List, Optional, Tuple
import docker
from docker.models.containers import Container
import logging
class DockerModule:
"""
Module for handling Docker container operations in SIA.
Manages container lifecycle, I/O operations, and status monitoring.
"""
def __init__(self):
self.client = docker.from_env()
self.containers: Dict[str, Container] = {}
self.logger = logging.getLogger(__name__)
def start_container(
self,
image: str,
name: Optional[str] = None,
timeout: int = -1,
command: Optional[str] = None,
arguments: Optional[List[str]] = None,
volumes: Optional[Dict[str, str]] = None,
ports: Optional[Dict[str, str]] = None,
environment: Optional[Dict[str, str]] = None,
) -> str:
"""Start a new Docker container with the specified configuration.
Args:
image: Docker image to use
name: Unique container name for long running containers
timeout: Timeout in milliseconds for short running containers
command: Main command to run in container
arguments: List of command line arguments
volumes: Dictionary mapping host paths to container paths
ports: Dictionary mapping host ports to container ports
environment: Dictionary of environment variables and values
Returns:
For short-lived containers (with timeout): Container output
For long-running containers: Container name
Raises:
docker.errors.ImageNotFound: If specified image doesn't exist
docker.errors.APIError: If container creation/start fails
"""
# Validate inputs
if name is None and timeout < 0:
raise ValueError("Either name or timeout must be provided")
# Prepare command with arguments
cmd = []
if command:
cmd.append(command)
if arguments:
cmd.extend(arguments)
# Prepare volume bindings
volume_binds = {}
if volumes:
for host_path, container_path in volumes.items():
volume_binds[host_path] = {'bind': container_path, 'mode': 'rw'}
# Prepare port bindings
port_bindings = {}
if ports:
for host_port, container_port in ports.items():
port_bindings[container_port] = host_port
try:
container = self.client.containers.run(
image,
command=cmd if cmd else None,
name=name,
detach=True,
volumes=volume_binds,
ports=port_bindings,
environment=environment,
)
if timeout >= 0:
# For short-lived containers, wait for completion
try:
container.wait(timeout=timeout/1000) # Convert ms to seconds
output = container.logs().decode('utf-8')
container.remove(force=True)
return output
except docker.errors.NotFound:
self.logger.warning(f"Container was removed before timeout")
return ""
else:
# For long-running containers, store reference
self.containers[name] = container
return name
except Exception as e:
self.logger.error(f"Error starting container: {str(e)}")
raise
def stop_container(self, name: str) -> None:
"""Stop and remove a Docker container by name.
Args:
name: Name of the container to stop
Raises:
KeyError: If container name not found
docker.errors.APIError: If container stop/removal fails
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
container.stop()
container.remove()
del self.containers[name]
except Exception as e:
self.logger.error(f"Error stopping container {name}: {str(e)}")
raise
def write_container_stdin(self, name: str, data: str) -> None:
"""Write data to a container's standard input.
Args:
name: Name of the target container
data: Data to write to stdin
Raises:
KeyError: If container name not found
docker.errors.APIError: If write operation fails
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
socket = container.attach_socket(params={'stdin': 1, 'stream': 1})
socket._sock.send(data.encode('utf-8'))
socket.close()
except Exception as e:
self.logger.error(f"Error writing to container {name} stdin: {str(e)}")
raise
def read_container_stdout(self, name: str, n: int = -1) -> str:
"""Read from a container's standard output buffer.
Args:
name: Name of the container
n: Number of bytes to read; -1 means read all available
Returns:
Data read from stdout
Raises:
KeyError: If container name not found
docker.errors.APIError: If read operation fails
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
logs = container.logs(stdout=True, stderr=False, tail=n if n > 0 else 'all')
return logs.decode('utf-8')
except Exception as e:
self.logger.error(f"Error reading container {name} stdout: {str(e)}")
raise
def read_container_stderr(self, name: str, n: int = -1) -> str:
"""Read from a container's standard error buffer.
Args:
name: Name of the container
n: Number of bytes to read; -1 means read all available
Returns:
Data read from stderr
Raises:
KeyError: If container name not found
docker.errors.APIError: If read operation fails
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
logs = container.logs(stdout=False, stderr=True, tail=n if n > 0 else 'all')
return logs.decode('utf-8')
except Exception as e:
self.logger.error(f"Error reading container {name} stderr: {str(e)}")
raise
def wait_container(self, name: str, timeout: int) -> Tuple[int, str]:
"""Wait for a container to finish execution.
Args:
name: Name of the container to wait for
timeout: Time to wait in milliseconds
Returns:
Tuple of (exit_code, output)
Raises:
KeyError: If container name not found
docker.errors.APIError: If wait operation fails
TimeoutError: If container doesn't finish within timeout
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
result = container.wait(timeout=timeout/1000) # Convert ms to seconds
logs = container.logs().decode('utf-8')
return (result['StatusCode'], logs)
except Exception as e:
self.logger.error(f"Error waiting for container {name}: {str(e)}")
raise
def get_container_status(self, name: str) -> Dict[str, any]:
"""Get current status information for a container.
Args:
name: Name of the container
Returns:
Dictionary with container status information
Raises:
KeyError: If container name not found
docker.errors.APIError: If status check fails
"""
if name not in self.containers:
raise KeyError(f"Container {name} not found")
try:
container = self.containers[name]
container.reload() # Refresh container info
return {
'name': name,
'status': container.status,
'started_at': container.attrs['State']['StartedAt'],
'exit_code': container.attrs['State']['ExitCode'],
'error': container.attrs['State']['Error'],
'stdout_size': len(container.logs(stdout=True, stderr=False)),
'stderr_size': len(container.logs(stdout=False, stderr=True))
}
except Exception as e:
self.logger.error(f"Error getting status for container {name}: {str(e)}")
raise

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@@ -1,8 +1,9 @@
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, TextStreamer
from threading import Thread
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, TextIteratorStreamer
import torch
from . import util
from .inference_result import InferenceResult
class LlmEngine:
def __init__(self, model_path: str):
@@ -34,33 +35,26 @@ class LlmEngine:
self.tokenizer.pad_token_id = self.tokenizer.eos_token_id
if model.config.pad_token_id is None:
model.config.pad_token_id = model.config.eos_token_id
streamer = TextStreamer(
self.tokenizer,
skip_prompt=True
)
self.pipeline = pipeline(
"text-generation",
model=model,
tokenizer=self.tokenizer,
torch_dtype=torch.bfloat16,
device_map="auto",
streamer=streamer,
return_full_text=False,
)
def infer(self, system_prompt: str, main_context: str, action_schema: str) -> InferenceResult:
def infer(self, system_prompt: str, main_context: str) -> TextIteratorStreamer:
"""
Run inference using the system prompt and main context, while validating actions against the provided XML schema.
Args:
system_prompt: The system prompt string
main_context: The main context string after templating
action_schema: XML schema to validate the generated actions
Returns:
InferenceResult: Tuple containing reasoning and actions that validate against the schema
TextIteratorStreamer: An iterator that yields the generated text.
"""
valid_elements = util.get_valid_root_elements(action_schema)
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": main_context}
@@ -68,11 +62,19 @@ class LlmEngine:
prompt = self.tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
outputs = self.pipeline(prompt, max_new_tokens=120, do_sample=True)
generated_text = outputs[0]["generated_text"]
#response = generated_text.split("<|start_header_id|>assistant<|end_header_id|>",1)[1].strip()
result = util.split_response(generated_text, valid_elements)
return result
streamer = TextIteratorStreamer(
self.tokenizer,
skip_prompt=True
)
pipeline_kwargs = dict(
text_inputs=prompt,
do_sample=True,
max_new_tokens=1024,
streamer=streamer
)
thread = Thread(target=self.pipeline, kwargs=pipeline_kwargs)
thread.start()
return util.stop_before_value(streamer, '<|eot_id|>')
def finetune(self, dataset_paths: list, output_dir: str):
"""

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@@ -1,7 +1,8 @@
from .inference_result import InferenceResult
import xml.etree.ElementTree as ET
from typing import Iterator, TypeVar
import re
import xml.etree.ElementTree as ET
from .inference_result import InferenceResult
def get_valid_root_elements(schema: str) -> set:
"""
@@ -45,3 +46,24 @@ def split_response(response: str, valid_elements: set) -> InferenceResult:
reasoning = response[:split_point].strip()
actions = response[split_point:].strip()
return InferenceResult(reasoning, actions)
def stop_before_value(iterator: Iterator[str], stop_value: str) -> Iterator[str]:
"""
Creates an iterator that yields values from the input iterator
until it encounters the stop_value (exclusive).
Args:
iterator: The source iterator
stop_value: The value to stop before
Yields:
Values from the iterator until stop_value is encountered
If stop_value is part of an item, yields the part before stop_value
"""
for item in iterator:
if stop_value in item:
split_point = item.index(stop_value)
if split_point > 0:
yield item[:split_point]
break
yield item

186
test/docker_module_test.py Normal file
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@@ -0,0 +1,186 @@
import unittest
import docker
from docker.models.containers import Container
from sia.docker_module import DockerModule
class DockerModuleTest(unittest.TestCase):
def test_initialization(self):
"""Test DockerModule initialization."""
docker_module = DockerModule()
self.assertIsInstance(docker_module, DockerModule)
def test_start_container_short_lived(self):
"""Test starting a short-lived container."""
docker_module = DockerModule()
# Test parameters
image = "sia:latest"
timeout = 1000
command = "echo"
arguments = ["Hello World"]
output = docker_module.start_container(
image=image,
timeout=timeout,
command=command,
arguments=arguments
)
# Verify output was returned
self.assertEqual(output, "Hello World\n")
def test_start_container_long_running(self):
"""Test starting a long-running container."""
docker_module = DockerModule()
name = "test-container"
image = "sia:latest"
container_name = docker_module.start_container(
image=image,
name=name
)
# Verify container was started and stored
self.assertEqual(container_name, name)
self.assertIn(name, docker_module.containers)
self.assertEqual(docker_module.containers[name], self.mock_container)
def test_start_container_with_volumes(self):
"""Test starting a container with volume mappings."""
docker_module = DockerModule()
volumes = {"./pdf": "/pdf"}
output = docker_module.start_container(
image="sia:latest",
timeout=1000,
volumes=volumes
)
# Verify volume bindings were configured correctly
expected_binds = {
"./pdf": {"bind": "/pdf", "mode": "rw"}
}
def test_invalid_container_start(self):
"""Test error handling for invalid container start."""
docker_module = DockerModule()
# Test missing required parameters
with self.assertRaises(ValueError):
docker_module.start_container(image="test:latest")
def test_stop_container(self):
"""Test stopping a container."""
docker_module = DockerModule()
# Start a container first
name = "test-container"
docker_module.start_container(
image="test:latest",
name=name
)
# Stop the container
docker_module.stop_container(name)
# Verify container was stopped and removed
self.mock_container.stop.assert_called_once()
self.mock_container.remove.assert_called_once()
self.assertNotIn(name, docker_module.containers)
def test_stop_nonexistent_container(self):
"""Test stopping a container that doesn't exist."""
docker_module = DockerModule()
with self.assertRaises(KeyError):
docker_module.stop_container("nonexistent")
def test_container_io_operations(self):
"""Test container I/O operations."""
docker_module = DockerModule()
# Start a container
name = "test-container"
docker_module.start_container(
image="test:latest",
name=name
)
# Test stdin write
test_input = "test input"
mock_socket = Mock()
mock_socket._sock = Mock()
self.mock_container.attach_socket.return_value = mock_socket
docker_module.write_container_stdin(name, test_input)
mock_socket._sock.send.assert_called_once_with(test_input.encode('utf-8'))
# Test stdout read
stdout = docker_module.read_container_stdout(name)
self.mock_container.logs.assert_called_with(
stdout=True,
stderr=False,
tail='all'
)
self.assertEqual(stdout, "Test output")
# Test stderr read
stderr = docker_module.read_container_stderr(name)
self.mock_container.logs.assert_called_with(
stdout=False,
stderr=True,
tail='all'
)
self.assertEqual(stderr, "Test output")
def test_wait_container(self):
"""Test waiting for container completion."""
docker_module = DockerModule()
# Start a container
name = "test-container"
docker_module.start_container(
image="test:latest",
name=name
)
# Test wait operation
exit_code, output = docker_module.wait_container(name, timeout=1000)
# Verify wait was called with correct timeout
self.mock_container.wait.assert_called_once_with(timeout=1.0)
self.assertEqual(exit_code, 0)
self.assertEqual(output, "Test output")
def test_get_container_status(self):
"""Test getting container status information."""
docker_module = DockerModule()
# Start a container
name = "test-container"
docker_module.start_container(
image="test:latest",
name=name
)
# Configure mock logs sizes
self.mock_container.logs.side_effect = [b"stdout", b"stderr"]
# Get status
status = docker_module.get_container_status(name)
# Verify status information
self.assertEqual(status['name'], name)
self.assertEqual(status['status'], "running")
self.assertEqual(status['started_at'], "2024-10-23T10:00:00Z")
self.assertEqual(status['exit_code'], 0)
self.assertEqual(status['error'], "")
self.assertEqual(status['stdout_size'], 6) # len(b"stdout")
self.assertEqual(status['stderr_size'], 6) # len(b"stderr")
# Verify container was reloaded
self.mock_container.reload.assert_called_once()
if __name__ == '__main__':
unittest.main()

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@@ -1,14 +1,15 @@
import unittest
from itertools import tee
from . import test_data
from . import test_util
from sia.llm_engine import LlmEngine, InferenceResult
from sia.llm_engine import LlmEngine
class LlmEngineTest(unittest.TestCase):
def setUp(self):
self.model_path = "/root/model"
self.llm_engine = LlmEngine(self.model_path)
def test_initialization(self):
llm_engine = LlmEngine(self.model_path)
@@ -17,9 +18,9 @@ class LlmEngineTest(unittest.TestCase):
def test_infer(self):
main_context = "This is a test"
llm_engine = LlmEngine(self.model_path)
result = llm_engine.infer(test_data.echo_system_prompt, main_context, test_data.echo_action_schema)
self.assertIsInstance(result, InferenceResult)
self.assertIsInstance(result.reasoning, str)
self.assertIsInstance(result.actions, str)
self.assertEqual(result.reasoning, main_context)
self.assertEqual(result.actions, f"<test_tag>{main_context}</test_tag>")
tokens = llm_engine.infer(test_data.echo_system_prompt, main_context)
print_tokens, result_tokens = tee(tokens)
for token in print_tokens:
print(token, end="", flush=True)
result = ''.join(result_tokens)
self.assertEqual(result, f"{main_context}<test_tag>{main_context}</test_tag>")