mirror of
https://github.com/crewAIInc/crewAI.git
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f04c40babf
Adds async support for tools with tests, async execution in the agent executor, and async operations for memory (with aiosqlite). Improves tool decorator typing, ensures _run backward compatibility, updates docs and docstrings, adds tests, and regenerates lockfiles.
122 lines
3.2 KiB
Python
122 lines
3.2 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING, Any
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from pydantic import BaseModel
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from crewai.rag.embeddings.types import EmbedderConfig
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if TYPE_CHECKING:
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from crewai.agent import Agent
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from crewai.task import Task
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class Memory(BaseModel):
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"""Base class for memory, supporting agent tags and generic metadata."""
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embedder_config: EmbedderConfig | dict[str, Any] | None = None
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crew: Any | None = None
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storage: Any
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_agent: Agent | None = None
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_task: Task | None = None
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def __init__(self, storage: Any, **data: Any):
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super().__init__(storage=storage, **data)
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@property
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def task(self) -> Task | None:
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"""Get the current task associated with this memory."""
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return self._task
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@task.setter
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def task(self, task: Task | None) -> None:
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"""Set the current task associated with this memory."""
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self._task = task
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@property
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def agent(self) -> Agent | None:
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"""Get the current agent associated with this memory."""
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return self._agent
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@agent.setter
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def agent(self, agent: Agent | None) -> None:
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"""Set the current agent associated with this memory."""
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self._agent = agent
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def save(
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self,
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value: Any,
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metadata: dict[str, Any] | None = None,
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) -> None:
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"""Save a value to memory.
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Args:
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value: The value to save.
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metadata: Optional metadata to associate with the value.
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"""
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metadata = metadata or {}
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self.storage.save(value, metadata)
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async def asave(
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self,
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value: Any,
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metadata: dict[str, Any] | None = None,
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) -> None:
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"""Save a value to memory asynchronously.
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Args:
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value: The value to save.
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metadata: Optional metadata to associate with the value.
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"""
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metadata = metadata or {}
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await self.storage.asave(value, metadata)
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def search(
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self,
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query: str,
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limit: int = 5,
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score_threshold: float = 0.6,
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) -> list[Any]:
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"""Search memory for relevant entries.
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Args:
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query: The search query.
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limit: Maximum number of results to return.
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score_threshold: Minimum similarity score for results.
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Returns:
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List of matching memory entries.
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"""
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results: list[Any] = self.storage.search(
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query=query, limit=limit, score_threshold=score_threshold
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)
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return results
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async def asearch(
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self,
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query: str,
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limit: int = 5,
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score_threshold: float = 0.6,
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) -> list[Any]:
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"""Search memory for relevant entries asynchronously.
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Args:
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query: The search query.
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limit: Maximum number of results to return.
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score_threshold: Minimum similarity score for results.
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Returns:
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List of matching memory entries.
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"""
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results: list[Any] = await self.storage.asearch(
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query=query, limit=limit, score_threshold=score_threshold
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)
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return results
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def set_crew(self, crew: Any) -> Memory:
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"""Set the crew for this memory instance."""
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self.crew = crew
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return self
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