example_rag.py

"""
This script demonstrates the rag tools available in this project. The rag tool searches the docs directory for a sub directory that matches the domain name and uses the available documents to performa a RAG (Retrieval Augmented Generation) query. By default the search domain of "llama_index" is available.
"""

from dotenv import load_dotenv
import logging

from utils.rag_tools import get_informed_answer

# Set to DEBUG for more verbose logging
logging.basicConfig(level=logging.INFO)

load_dotenv()

STORAGE_DIR = "./storage"
DOCS_DIR = "./docs"

# NOTE: If you run "python example_research.py", most likely you will then be able to set the domain to "autogen" for autogen related queries

domain = "bitsavers_sel_810"
domain_description = "sel computers"

def main():
    question = "Please provide a guide to SEL 810 mnembler programming, specifically operations and syntax"
    
    answer = get_informed_answer(
        question,
        docs_dir=DOCS_DIR,
        storage_dir=STORAGE_DIR,
        domain=domain,
        domain_description=domain_description,
        vector_top_k=25,
        reranker_top_n=5,
        rerank=True,
        fusion=True,
    )

    print("GOT ANSWER: ", answer.response)


if __name__ == "__main__":
    main()