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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)
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