Доработка: 1. В vectorstore.py заменить импорт Ollama на from langchain

tools.py

@@ -0,0 +1,22 @@
+from langchain.tools import tool
+from langchain_community.vectorstores import Chroma
+from langchain_ollama import OllamaEmbeddings
+from langchain_tavily import TavilySearchResults
+import os
+
+@tool
+def search_local_kb(query: str, top_k: int = 3) -> str:
+    """Поиск в локальной базе знаний (ChromaDB) по запросу."""
+    persist_directory = "./chroma_db"
+    embeddings = OllamaEmbeddings(model="nomic-embed-text")
+    vectorstore = Chroma(persist_directory=persist_directory, embedding_function=embeddings)
+    retriever = vectorstore.as_retriever(search_kwargs={"k": top_k})
+    docs = retriever.get_relevant_documents(query)
+    return "\n\n".join([doc.page_content for doc in docs])
+
+@tool
+def web_search(query: str) -> str:
+    """Поиск в интернете через Tavily."""
+    search = TavilySearchResults()
+    results = search.run(query)
+    return "\n\n".join([result.get("content", "") for result in results])