query.py

"""
CLI helper for issuing ad-hoc questions against the RAG stack.

Used for:
- quick debugging
- manual evaluation
- demo runs
"""

from __future__ import annotations

from config import DEFAULT_HYBRID_ALPHA, DEFAULT_RETRIEVAL_STRATEGY, TOP_K_RESULTS
from context import build_context, generate_answer
from embedding import get_embedder
from retrieval import retrieve_chunks
from db import close_weaviate_client


def ask(
    question: str,
    top_k: int = TOP_K_RESULTS,
    *,
    strategy: str | None = None,
    alpha: float | None = None,
) -> str:
    model = get_embedder()
    print("Retrieving relevant chunks...")
    results = retrieve_chunks(
        model,
        question,
        top_k=top_k,
        strategy=strategy or DEFAULT_RETRIEVAL_STRATEGY,
        alpha=alpha if alpha is not None else DEFAULT_HYBRID_ALPHA,
    )
    context = build_context(results)
    print("CONTEXT USED:\n", context[:800], "...\n")

    print("Generating answer...")
    source_ids = [chunk.get("doc_id") or chunk.get("source_file") for chunk in results]
    answer = generate_answer(question, context, source_ids=source_ids)
    print("ANSWER:\n", answer)
    return answer


if __name__ == "__main__":
    try : 
        # ask("What are the main claims about intellectual property in these documents?")
        # ADD asks here : ask("Summarize the key points related to patent law.")
        ask("How do Drahos and Braithwaite (2002) describe the role of TRIPS and TRIPS-plus agreements in shifting the balance of power over medicines between multinational pharmaceutical companies and developing countries?")
    finally:
        close_weaviate_client()