appself.py

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

app = FastAPI()

CSV_FILE_PATH0 = 'info.csv'
PYTHON_SCRIPT_PATH0 = 'AAmain.py'

# Set up static files
app.mount("/static", StaticFiles(directory="."), name="static")

templates = Jinja2Templates(directory="templates")

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

        # Adjust temperature for more diverse responses
        with httpx.Client() as client:
            response = 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

@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 = 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})

# New route for running AAmain.py
@app.post("/run_aamain")
async def run_aamain(csv_filename: str = Form(...)):
    subprocess.run(["python", "AAmain.py", csv_filename])  # Adjust arguments as needed
    return {"message": "AAmain.py process started successfully."}

# New route for generating AI
@app.post("/generate_ai")
async def generate_ai(prompt: str = Form(...)):
    conversation = generate_conversation(prompt)
    csv_filename = save_to_csv(prompt, conversation)
    
    return {"prompt": prompt, "conversation": conversation, "csv_filename": csv_filename}

if __name__ == "__main__":
    import uvicorn

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