app2.py

from fastapi import FastAPI, Request, Form
from fastapi.templating import Jinja2Templates
import gpt_2_simple as gpt2
from datetime import datetime
import csv

app = FastAPI()
templates = Jinja2Templates(directory="templates")

# Download the GPT-2 model if not already downloaded
gpt2.download_gpt2(model_name="124M")

# Load the GPT-2 model
sess = gpt2.start_tf_sess()
gpt2.load_gpt2(sess, model_name="124M")

async def generate_conversation(prompt):
    try:
        conversation = gpt2.generate(sess, prefix=prompt, length=300, temperature=0.7, return_as_list=True)[0]
        return conversation
    except Exception as e:
        return f"Error: {str(e)}"

def save_to_csv(prompt, conversation):
    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
    filename = f"info.csv"

    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
        csv_writer = csv.writer(csv_file)
        csv_writer.writerow(['Prompt', 'Generated Conversation'])
        csv_writer.writerow([prompt, conversation])

    return filename

@app.get("/")
def read_form(request: Request):
    return templates.TemplateResponse("index.html", {"request": request})

@app.post("/")
async def generate_and_display(request: Request, prompt: str = Form(...)):
    conversation = await generate_conversation(prompt)
    csv_filename = save_to_csv(prompt, conversation)
    return templates.TemplateResponse("index.html", {"request": request, "prompt": prompt, "conversation": conversation, "csv_filename": csv_filename})

if __name__ == "__main__":
    import uvicorn

    uvicorn.run(app, host="127.0.0.1", port=8000)