app.py

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import gradio as gr
import requests
import threading

app = FastAPI()

# Load model and tokenizer once
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")

# In-memory chat history by user
chat_history = {}

@app.get("/")
async def root():
    return {"message": "🟢 API is running. Use /ai?query=Hello&user_id=yourname"}

@app.get("/ai")
async def chat(request: Request):
    query_params = dict(request.query_params)
    user_input = query_params.get("query", "")
    user_id = query_params.get("user_id", "default")

    if not user_input:
        return JSONResponse({"error": "Missing 'query' parameter"}, status_code=400)

    new_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
    user_history = chat_history.get(user_id, [])
    bot_input_ids = torch.cat(user_history + [new_input_ids], dim=-1) if user_history else new_input_ids

    output_ids = model.generate(bot_input_ids, max_new_tokens=100, pad_token_id=tokenizer.eos_token_id)
    response = tokenizer.decode(output_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

    chat_history[user_id] = [bot_input_ids, output_ids]
    return JSONResponse({"reply": response})

# Gradio UI to call your /ai endpoint easily via browser
def gradio_chat(user_input, user_id="default"):
    if not user_input:
        return "Please enter some text."
    url = f"https://Trigger82--API.hf.space/ai?query={user_input}&user_id={user_id}"
    try:
        res = requests.get(url)
        if res.status_code == 200:
            return res.json().get("reply", "No reply")
        return f"Error: {res.status_code}"
    except Exception as e:
        return f"Exception: {e}"

iface = gr.Interface(
    fn=gradio_chat,
    inputs=[gr.Textbox(label="Your Message"), gr.Textbox(label="User ID", value="default")],
    outputs="text",
    title="Chat with DialoGPT API",
    description="Type your message and user id to chat with the model."
)

# Launch Gradio app in a thread alongside FastAPI
def run_gradio():
    iface.launch(server_name="0.0.0.0", server_port=7861, share=False)

threading.Thread(target=run_gradio).start()

# No need for uvicorn.run here on Spaces; it manages startup automatically