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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)
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