add tools

tools.py

@@ -0,0 +1,20 @@
+from langchain.tools import tool
+from langchain.embeddings.ollama import OllamaEmbeddings
+from langchain.vectorstores import Chroma
+import os
+
+@tool("search_local_kb")
+def search_local_kb(query: str, top_k: int = 3) -> str:
+    """Semantic search in local ChromaDB."""
+    persist_dir = os.getenv("CHROMA_DB_DIR", "./chroma_db")
+    embeddings = OllamaEmbeddings(model="nomic-embed-text")
+    db = Chroma(embedding_function=embeddings, persist_directory=persist_dir)
+    docs = db.similarity_search(query, k=top_k)
+    return "\n".join([d.page_content for d in docs]) + f"\n[Source: chromadb]"
+
+@tool("web_search")
+def web_search(query: str) -> str:
+    from tavily import TavilyClient
+    client = TavilyClient(api_key=os.getenv("TAVILY_API_KEY"))
+    result = client.search(query, max_results=3)
+    return "\n".join([r['content'] for r in result]) + f"\n[Source: tavily]"