74 lines
2.6 KiB
Python
74 lines
2.6 KiB
Python
from abc import ABC
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import xml.etree.ElementTree as ET
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from .llm_engine import LlmEngine
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from .response_parser import ResponseParser
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from .system_metrics import SystemMetrics
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from .util import pretty_print_element
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from .working_memory import WorkingMemory
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class BaseAgent(ABC):
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"""
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Abstract base class for SIA agents.
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Provides core functionality for maintaining working memory, system metrics,
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and coordinating components for LLM inference.
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"""
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def __init__(
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self,
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system_prompt: str,
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action_schema: str,
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working_memory: WorkingMemory,
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metrics: SystemMetrics,
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parser: ResponseParser,
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):
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"""
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Initialize agent with required components.
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"""
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self._system_prompt = system_prompt
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self._action_schema = action_schema
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self._working_memory = working_memory
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self._metrics = metrics
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self._parser = parser
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@property
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def system_prompt(self) -> str:
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"""Get the system prompt."""
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return f"{self._system_prompt}\n{self._action_schema}"
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def _compile_context(self, llmEngine: LlmEngine) -> str:
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"""
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Compile the current context for LLM inference.
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Includes system metrics and working memory entries.
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Returns:
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str: Complete context as XML string
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"""
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memory_context = self._working_memory.generate_context()
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metrics_data = self._metrics.get_metrics()
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# Create context element
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context = ET.Element("context")
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context.set("time", metrics_data["timestamp"])
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context.set("memory_used", str(metrics_data["memory_used"]))
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context.set("memory_total", str(metrics_data["memory_total"]))
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context.set("disk_used", str(metrics_data["disk_used"]))
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context.set("disk_total", str(metrics_data["disk_total"]))
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context.set("stdin", str(self._parser.io_buffer.buffer_length()))
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context.set("context", "100%")
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for entry in memory_context:
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context.append(entry)
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context_str = pretty_print_element(context)
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# Calculate token usage percentage
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token_count = llmEngine.token_count(self.system_prompt, context_str)
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token_limit = llmEngine.token_limit()
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context_usage = (float(token_count) / float(token_limit)) * 100.0
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# Update context usage metric
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context.set("context", f"{str(round(context_usage, 2))}%")
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return pretty_print_element(context) |