"""Tool definitions for the RAG agent.

Provides two tools:
- search_local_kb: semantic search over the local ChromaDB vector store.
- web_search: web search via Tavily.
"""

from typing import List, Dict

from langchain.tools import tool
from langchain_ollama import ChatOllama
from langchain_tavily import TavilySearchResults

# Local search tool will be created dynamically in agent.py because it needs the vectorstore.

@tool
def web_search(query: str) -> str:
    """Search the web using Tavily and return a short summary.

    Parameters
    ----------
    query: str
        The search query.

    Returns
    -------
    str
        A concise answer with a source tag.
    """
    tavily = TavilySearchResults(max_results=3, api_key=None)  # API key is taken from env
    results = tavily.run(query)
    # Build a simple summary from the results
    summary = "\n".join([f"{idx+1}. {r['title']}: {r['content'][:200]}" for idx, r in enumerate(results)])
    return f"[Web Search]\n{summary}\nSource: tavily"

# The local search tool will be defined in agent.py where the vectorstore is available.