"""
RAG tools for the agent.

search_knowledge_base and add_to_knowledge_base are decorated with @tool.
"""
import os
from typing import List, Dict

from langchain.tools import tool
from vector_store import vector_store
from chunker import split_text

@tool("Search knowledge base")
def search_knowledge_base(query: str, max_results: int = 5) -> str:
    """Semantic search in the vector store."""
    results = vector_store.similarity_search(query, k=max_results)
    if not results:
        return "No relevant documents found."
    out_lines = []
    for i, res in enumerate(results, 1):
        out_lines.append(f"{i}. {res['content'][:200]}... (distance: {res['distance']:.3f})")
    return "\n".join(out_lines)

@tool("Add document to knowledge base")
def add_to_knowledge_base(content: str, title: str = "document") -> str:
    """Adds a text chunk to the vector store."""
    # Split content into chunks
    chunks = split_text(content)
    docs = []
    for idx, chunk in enumerate(chunks):
        docs.append({"content": chunk, "metadata": {"title": title, "chunk_index": idx}})
    vector_store.add_documents(docs)
    return f"Added {len(chunks)} chunks to the knowledge base."