main.py

import os
import random
from typing import List, Tuple
from fastapi import FastAPI, Form, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from huggingface_hub import InferenceClient
from deep_translator import GoogleTranslator

# Initialize FastAPI app
app = FastAPI()

# Allow CORS for your frontend application
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Change this to your frontend's URL in production
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Initialize Hugging Face Inference Client
client = InferenceClient("mistralai/Mistral-Nemo-Instruct-2407")

# Initialize Translators
translator_to_en = GoogleTranslator(source='arabic', target='english')
translator_to_ar = GoogleTranslator(source='english', target='arabic')

def format_prompt(message: str, history: List[Tuple[str, str]]) -> str:
    prompt = "<s>"
    for user_prompt, bot_response in history:
        prompt += f"[INST] {user_prompt} [/INST]"
        prompt += f" {bot_response}</s> "
    prompt += f"[INST] {message} [/INST]"
    return prompt

@app.post("/generate/")
async def generate(
    prompt: str = Form(...),
    history: str = Form(...),
    temperature: float = Form(0.9),
    max_new_tokens: int = Form(512),
    top_p: float = Form(0.95),
    repetition_penalty: float = Form(1.0)
):
    try:
        # Parse history from JSON string to list of tuples
        chat_history = eval(history)

        # Translate prompt to English
        translated_prompt = translator_to_en.translate(prompt)
        formatted_prompt = format_prompt(translated_prompt, chat_history)

        generate_kwargs = dict(
            temperature=temperature,
            max_new_tokens=max_new_tokens,
            top_p=top_p,
            repetition_penalty=repetition_penalty,
            do_sample=True,
            seed=random.randint(0, 10**7),
        )

        # Generate text using the model
        stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
        output = ""

        for response in stream:
            output += response.token.text

        # Translate the response back to Arabic
        translated_output = translator_to_ar.translate(output)

        return JSONResponse(content={"response": translated_output})

    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))