Files

28 lines
1019 B
Python

import os
from langchain.tools import tool
from langchain_tavily import TavilySearchResults
from langchain_chroma import Chroma
@tool
def search_local_kb(query: str, top_k: int = 3) -> str:
"""Search the local knowledge base for relevant information."""
vectorstore = Chroma(
collection_name="knowledge",
persist_directory="./chroma_db",
)
docs = vectorstore.similarity_search(query, k=top_k)
if not docs:
return "No results found in local knowledge base."
return "\n".join(f\"{i+1}. {doc.page_content[:200]}...\" for i, doc in enumerate(docs))
@tool
def web_search(query: str) -> str:
"""Search the web for up-to-date information."""
tavily = TavilySearchResults(
api_key=os.getenv("TAVILY_API_KEY"),
max_results=3,
)
results = tavily.run(query)
if not results:
return "No results found on the web."
return "\n".join(f\"{i+1}. {res['title']}\\n{res['url']}\\n{res['content'][:200]}...\" for i, res in enumerate(results))