main.py

from extract_text import extract_text_from_pdf
from math_summarizer import generate_math_summary
from nlp_summarizer import generate_nlp_summary_and_mindmap
import json
import openai
import dotenv
import time
import os

dotenv.load_dotenv()
API_KEY = os.getenv("API_KEY")
ACCESS_KEY = os.getenv("ACCESS_KEY")

def create_client(api_key):
    client = openai.OpenAI(
        api_key=api_key,
        base_url="https://glhf.chat/api/openai/v1",
    )
    return client

def generate_summary(client, corpus):
    response = {}
    math_summary = generate_math_summary(corpus)
    if not math_summary:
        print("Error generating Math Summary")
        response["summary_status"] = "error"
        response["summary"] = None
        response["mindmap_status"] = "error"
        response["mindmap"] = None
        return response
    else:
        response = generate_nlp_summary_and_mindmap(client, corpus)
        return response

def main(url, id, access_key):
    if access_key != ACCESS_KEY:
        return {"error": "Invalid Access Key", "summary": None, "mindmap": None}
    else:
        corpus = extract_text_from_pdf(url, id)
        start_time = time.time()
        client = create_client(API_KEY)
        response = generate_summary(client, corpus)
        print(f"Total timetaken: {time.time() - start_time} seconds")
        return json.dumps(response, indent=4, ensure_ascii=False)
    
if __name__ == "__main__":
    url = "https://arxiv.org/pdf/2106.01484"
    id = "123"
    access_key = "1234"
    print(main(url, id, access_key))