appp.py

from fastapi import FastAPI, Request, Form
from fastapi.templating import Jinja2Templates
import httpx
import csv
from datetime import datetime
import subprocess

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

async def generate_conversation(prompt):
    try:
        # Introduce slight variations in the prompt
        prompt_variation = prompt + str(hash(prompt))[:3]

        # Adjust temperature for more diverse responses
        async with httpx.AsyncClient() as client:
            response = await client.post('https://api-inference.huggingface.co/models/facebook/blenderbot-400M-distill', json={
                "inputs": prompt_variation,
                "options": {"temperature": 0.8}  # Adjust as needed
            })

        conversation = response.json()["generated_text"]
        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


def run_aamain_script():
    try:
        # Run the AAmain.py script
        subprocess.run(["python", "AAmain.py"], check=True)
        return "AAmain.py script executed successfully"
    except subprocess.CalledProcessError as e:
        return f"Error executing AAmain.py script: {str(e)}"


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

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

@app.post("/run_aamain")
async def run_aamain(request: Request):
    # Handle running AAmain.py script
    result = run_aamain_script()
    return templates.TemplateResponse("index.html", {"request": request, "aamain_result": result})

if __name__ == "__main__":
    import uvicorn

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