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https://github.com/crewAIInc/crewAI.git
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fab86d197a
* Move RAG components to top-level module - Create src/crewai/rag directory structure - Move embeddings configurator from utilities to rag module - Update imports across codebase and documentation - Remove deprecated embedding files * Remove empty knowledge/embedder directory
77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
from abc import ABC, abstractmethod
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from typing import Any, Dict, List, Optional
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class BaseRAGStorage(ABC):
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"""
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Base class for RAG-based Storage implementations.
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"""
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app: Any | None = None
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def __init__(
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self,
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type: str,
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allow_reset: bool = True,
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embedder_config: Optional[Dict[str, Any]] = None,
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crew: Any = None,
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):
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self.type = type
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self.allow_reset = allow_reset
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self.embedder_config = embedder_config
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self.crew = crew
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self.agents = self._initialize_agents()
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def _initialize_agents(self) -> str:
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if self.crew:
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return "_".join(
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[self._sanitize_role(agent.role) for agent in self.crew.agents]
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)
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return ""
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@abstractmethod
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def _sanitize_role(self, role: str) -> str:
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"""Sanitizes agent roles to ensure valid directory names."""
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pass
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@abstractmethod
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def save(self, value: Any, metadata: Dict[str, Any]) -> None:
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"""Save a value with metadata to the storage."""
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pass
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@abstractmethod
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def search(
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self,
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query: str,
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limit: int = 3,
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filter: Optional[dict] = None,
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score_threshold: float = 0.35,
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) -> List[Any]:
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"""Search for entries in the storage."""
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pass
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@abstractmethod
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def reset(self) -> None:
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"""Reset the storage."""
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pass
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@abstractmethod
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def _generate_embedding(
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self, text: str, metadata: Optional[Dict[str, Any]] = None
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) -> Any:
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"""Generate an embedding for the given text and metadata."""
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pass
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@abstractmethod
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def _initialize_app(self):
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"""Initialize the vector db."""
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pass
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def setup_config(self, config: Dict[str, Any]):
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"""Setup the config of the storage."""
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pass
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def initialize_client(self):
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"""Initialize the client of the storage. This should setup the app and the db collection"""
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pass
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