from math_summarizer import generate_math_summary
from nlp_summarizer import generate_nlp_summary_and_mindmap
import openai
import dotenv
import time
import os

dotenv.load_dotenv()
API_KEY = os.getenv('API_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(corpus):
    start_time = time.time()
    client = create_client(API_KEY)
    response = generate_summary(client, corpus)
    print(f"Total timetaken: {time.time() - start_time} seconds")
    return response