app.py

import argparse
import json

from src.gradio_app import run_summarization_model_gradio
from src.model_loading import load_open_ai_llm

parser = argparse.ArgumentParser(description="Defines a configuration")

parser.add_argument(
    "--configuration_file",
    "-cf",
    type=str,
    default="configuration/deployment.json",
    help="Path to the configuration file. The configuration can be used for a single source of configuration.",
)

if __name__ == "__main__":
    args = parser.parse_args()

    # Default configuration for summarization
    # Load configuration from a configuration file
    with open(args.configuration_file, "r") as cgf:
        cgf_kwargs = json.load(cgf)

    summarization_kwargs = cgf_kwargs.get(
        "summarization_kwargs", {"chain_type": "map_reduce"}
    )

    # Load the language model
    llm = load_open_ai_llm(
        model_loading_kwargs=cgf_kwargs.get("language_model_kwargs", {})
    )

    # Run the summarization model in gradio
    run_summarization_model_gradio(
        llm=llm,
        share_gradio_via_link=cgf_kwargs.get("share_gradio_via_link", False),
        summarization_kwargs=summarization_kwargs,
        run_local=cgf_kwargs.get("run_local", True),
    )