ScientryAPI / main.py
raannakasturi's picture
Refactor summary generation to use Gradio client for TextRank, Luhn, LSA, and LexRank summarizers; improve error handling and logging
c69bbef
raw
history blame
1.05 kB
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