19 lines
663 B
Python
19 lines
663 B
Python
from langchain.tools import tool
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from vector_store import QdrantStore
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from chunker import get_chunks
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store = QdrantStore()
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@tool
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def search_knowledge_base(query: str, max_results: int = 5) -> str:
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"""Semantic search in knowledge base."""
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results = store.search(query, limit=max_results)
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return "\n".join([f"{i+1}. {r['metadata']['title']} – {r['metadata']['content'][:200]}..." for i,r in enumerate(results)])
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@tool
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def add_to_knowledge_base(content: str, title: str) -> str:
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"""Add document to knowledge base."""
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chunks = get_chunks(content, title)
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store.add_documents(chunks)
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return f"Added {len(chunks)} chunks for '{title}'."
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