"""
Utility tools for the LangChain agent.

Two tools are exposed:

* ``search_knowledge_base`` – semantic search in a Qdrant collection.
* ``add_to_knowledge_base`` – add a document to the same collection.

Both use the :mod:`qdrant_store` module defined in this repository.
"""

from __future__ import annotations

import json
from typing import List, Dict

from langchain.tools import tool
from langchain_core.documents import Document

# Import the singleton store instance from qdrant_store.py
from .qdrant_store import store

# ---------------------------------------------------------------------------
@tool
def search_knowledge_base(query: str, max_results: int = 5) -> str:
    """Return a formatted string with the top *max_results* documents.

    The function performs a semantic similarity search using Qdrant and returns
    a human‑readable list.  If no results are found an explanatory message is
    returned.
    """
    docs: List[Document] = store.similarity_search(query, k=max_results)
    if not docs:
        return "No relevant documents found."
    lines: List[str] = []
    for i, doc in enumerate(docs, start=1):
        title = doc.metadata.get("title", f"doc{i}")
        lines.append(f"{i}. {title}:\n{doc.page_content[:200]}{'...' if len(doc.page_content)>200 else ''}")
    return "\n\n".join(lines)

# ---------------------------------------------------------------------------
@tool
def add_to_knowledge_base(content: str, title: str = "document") -> str:
    """Add a document to the knowledge base.

    The function creates a :class:`langchain_core.documents.Document` with the
    supplied ``content`` and optional ``title`` metadata.  It then delegates to
    :func:`qdrant_store.store.add_documents`.
    """
    doc = Document(page_content=content, metadata={"title": title})
    store.add_documents([doc])
    return f"Added '{title}' to the knowledge base."

__all__ = ["search_knowledge_base", "add_to_knowledge_base"]