From 61170d52342e02df1055242ddf3b155ffb250a48 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=90=D0=B4=D0=B5=D0=BB=D0=B8=D0=BD=D0=B0=20=D0=A1=D0=B0?=
 =?UTF-8?q?=D1=82=D1=82=D0=B0=D1=80=D0=BE=D0=B2=D0=B0?=
 <sattarova2509@gmail.com>
Date: Sun, 31 May 2026 16:21:17 +0000
Subject: [PATCH] Add tools.py

---
 tools.py | 37 +++++++++++++++++++++++++++++++++++++
 1 file changed, 37 insertions(+)
 create mode 100644 tools.py

diff --git a/tools.py b/tools.py
new file mode 100644
index 0000000..bc83a41
--- /dev/null
+++ b/tools.py
@@ -0,0 +1,37 @@
+"""
+Tools for the RAG agent.
+
+- search_local_kb(query, top_k)
+- web_search(query)
+"""
+import os
+from typing import List
+
+from langchain_ollama import OllamaEmbeddings
+from langchain_chroma import Chroma
+from langchain_tavily import TavilySearchResults
+from langchain_core.documents import Document
+
+# Global vectorstore – will be set in init_db or main
+vectorstore: Chroma = None
+
+def search_local_kb(query: str, top_k: int = 3) -> List[Document]:
+    """Semantic search in the local ChromaDB."""
+    if vectorstore is None:
+        raise RuntimeError("Vectorstore not initialized")
+    return vectorstore.similarity_search_with_score(query, k=top_k)
+
+# Tavily client – API key from env
+from tavily import TavilyClient
+import os
+TAVILY_API_KEY = os.getenv("TAVILY_API_KEY", "")
+client = TavilyClient(api_key=TAVILY_API_KEY)
+
+def web_search(query: str, max_results: int = 3) -> List[Document]:
+    """Search the web via Tavily and return Documents."""
+    results = client.search(query=query, max_results=max_results)
+    docs = []
+    for r in results:
+        content = f"{r.title}\n\n{r.content}"
+        docs.append(Document(page_content=content, metadata={"source": "tavily", "url": r.url}))
+    return docs