main.py

from fastapi import FastAPI, File, UploadFile, Form, HTTPException
from fastapi.responses import HTMLResponse
from transformers import AutoProcessor, AutoModelForImageTextToText
import torch
from PIL import Image
import io
import os

app = FastAPI()

model_id = "gijl/gemma-4-E4B-it"

# --- السطر 13: استبدال الجزء القديم بهذا الجزء الجديد ---
print("جاري تحميل المعالج...")
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)

print("جاري تحميل النموذج (قد يستغرق وقتاً بسبب الحجم)...")
model = AutoModelForImageTextToText.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    low_cpu_mem_usage=True,
    device_map="auto",
    trust_remote_code=True 
)
# -------------------------------------------------------

@app.get("/")
async def read_index():
    with open("index.html", "r", encoding="utf-8") as f:
        return HTMLResponse(content=f.read())

@app.post("/generate")
async def generate_text(image: UploadFile = File(...), text: str = Form(...)):
    try:
        image_data = await image.read()
        pil_image = Image.open(io.BytesIO(image_data)).convert("RGB")
        
        inputs = processor(text=text, images=pil_image, return_tensors="pt")
        inputs = {k: v.to(model.device) for k, v in inputs.items()}
        
        with torch.no_grad():
            generated_ids = model.generate(**inputs, max_new_tokens=100)
        
        generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
        return {"result": generated_text}
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))