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https://github.com/crewAIInc/crewAI.git
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d3ecd1d490
* Adding tool caching a loop execution prevention. This adds some guardrails, to both prevent the same tool to be used consecutively and also caching tool's results across the entire crew so it cuts down execution time and eventual LLM calls. This plays a huge role for smaller opensource models that usually fall into those behaviors patterns. It also includes some smaller improvements around the tool prompt and agent tools, all with the same intention of guiding models into better conform with agent instructions.
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
from typing import Any, Dict
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from langchain.callbacks.base import BaseCallbackHandler
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from .cache_handler import CacheHandler
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class ToolsHandler(BaseCallbackHandler):
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"""Callback handler for tool usage."""
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last_used_tool: Dict[str, Any] = {}
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cache: CacheHandler = None
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def __init__(self, cache: CacheHandler = None, **kwargs: Any):
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"""Initialize the callback handler."""
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self.cache = cache
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super().__init__(**kwargs)
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def on_tool_start(
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self, serialized: Dict[str, Any], input_str: str, **kwargs: Any
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) -> Any:
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"""Run when tool starts running."""
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name = serialized.get("name")
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if name not in ["invalid_tool", "_Exception"]:
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tools_usage = {
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"tool": name,
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"input": input_str,
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}
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self.last_used_tool = tools_usage
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def on_tool_end(self, output: str, **kwargs: Any) -> Any:
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"""Run when tool ends running."""
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if (
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"is not a valid tool" not in output
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and "Invalid or incomplete response" not in output
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and "Invalid Format" not in output
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):
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self.cache.add(
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tool=self.last_used_tool["tool"],
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input=self.last_used_tool["input"],
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output=output,
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)
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