28 lines
995 B
Python
28 lines
995 B
Python
import os
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from langchain.tools import tool
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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from langchain_core.documents import Document
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from rag_store import KnowledgeBase
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kb = KnowledgeBase()
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splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
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@tool
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def search_knowledge_base(query: str, max_results: int = 3) -> str:
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"""Search the knowledge base for relevant information."""
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docs = kb.similarity_search(query, k=max_results)
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if not docs:
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return "No results found."
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return "\n\n".join(
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f"Title: {doc.metadata.get('title', 'N/A')}\nContent: {doc.page_content}"
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for doc in docs
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)
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@tool
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def add_to_knowledge_base(content: str, title: str = "Untitled") -> str:
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"""Add content to the knowledge base."""
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chunks = splitter.split_text(content)
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docs = [Document(page_content=chunk, metadata={"title": title}) for chunk in chunks]
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kb.add_documents(docs)
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return f"Added document '{title}'." |