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https://github.com/crewAIInc/crewAI.git
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fa26f6ebae
* Added reset memories function inside crew class * Fixed typos * Refractored the code * Refactor memory reset functionality in Crew class - Improved error handling and logging for memory reset operations - Added private methods to modularize memory reset logic - Enhanced type hints and docstrings - Updated CLI reset memories command to use new Crew method - Added utility function to get crew instance in CLI utils * fix linting issues * knowledge: Add null check in reset method for storage * cli: Update memory reset tests to use Crew's reset_memories method * cli: Enhance memory reset command with improved error handling and validation --------- Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com> Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
import os
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from typing import Any, Dict, List, Optional
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from pydantic import BaseModel, ConfigDict, Field
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from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
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from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
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os.environ["TOKENIZERS_PARALLELISM"] = "false" # removes logging from fastembed
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class Knowledge(BaseModel):
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"""
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Knowledge is a collection of sources and setup for the vector store to save and query relevant context.
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Args:
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sources: List[BaseKnowledgeSource] = Field(default_factory=list)
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storage: Optional[KnowledgeStorage] = Field(default=None)
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embedder: Optional[Dict[str, Any]] = None
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"""
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sources: List[BaseKnowledgeSource] = Field(default_factory=list)
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model_config = ConfigDict(arbitrary_types_allowed=True)
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storage: Optional[KnowledgeStorage] = Field(default=None)
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embedder: Optional[Dict[str, Any]] = None
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collection_name: Optional[str] = None
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def __init__(
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self,
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collection_name: str,
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sources: List[BaseKnowledgeSource],
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embedder: Optional[Dict[str, Any]] = None,
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storage: Optional[KnowledgeStorage] = None,
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**data,
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):
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super().__init__(**data)
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if storage:
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self.storage = storage
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else:
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self.storage = KnowledgeStorage(
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embedder=embedder, collection_name=collection_name
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)
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self.sources = sources
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self.storage.initialize_knowledge_storage()
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self._add_sources()
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def query(self, query: List[str], limit: int = 3) -> List[Dict[str, Any]]:
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"""
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Query across all knowledge sources to find the most relevant information.
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Returns the top_k most relevant chunks.
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Raises:
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ValueError: If storage is not initialized.
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"""
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if self.storage is None:
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raise ValueError("Storage is not initialized.")
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results = self.storage.search(
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query,
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limit,
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)
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return results
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def _add_sources(self):
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try:
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for source in self.sources:
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source.storage = self.storage
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source.add()
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except Exception as e:
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raise e
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def reset(self) -> None:
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if self.storage:
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self.storage.reset()
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else:
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raise ValueError("Storage is not initialized.")
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