backend/main/run_rag.py

# from classes.rag_application import RAGApplication
# from classes.pdf_extractor import PDFExtractor
# from classes.generative_model import GenerativeModel, GenerativeModelConfig
# from utils import initialize_logger, read_config
# from pathlib import Path
# import logging
#
# logging.basicConfig(level=logging.INFO)
# logger = logging.getLogger(__name__)
#
# logger = initialize_logger()
#
# # Initialize required components from config
# config = read_config("conf/config.yaml")
# pdf_extractor = PDFExtractor(config["pdf_extractor"])
# vector_db = VectorDatabase(config["vector_database"])
#
# # Get PDF path from config
# pdf_path = config["data"]["input_data_path"]
#
# def run(config: dict):
#     """
#     Run the RAG application.
#     :param config: Configuration dictionary
#     """
#     logger.info("Create generative model")
#     generative_model_config = GenerativeModelConfig(model_name=config['generative_model']['model_name'])
#     generative_model = GenerativeModel(generative_model_config)
#
#     logger.info("Create RAG application")
#     rag_app = RAGApplication(vector_db, pdf_extractor, generative_model)
#     rag_app.run(pdf_path, 'Give me a summary of the document')
#     logger.info("RAG application completed")
#
# if __name__ == '__main__':
#     run(config)