Create main.py

main.py

@@ -0,0 +1,46 @@
+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"
+
+# تحميل المعالج والنموذج
+print("جاري تحميل النموذج...")
+processor = AutoProcessor.from_pretrained(model_id)
+model = AutoModelForImageTextToText.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    low_cpu_mem_usage=True,
+    device_map="auto"
+)
+
+# عرض واجهة React عند الدخول للموقع
+@app.get("/")
+async def read_index():
+    with open("index.html", "r", encoding="utf-8") as f:
+        return HTMLResponse(content=f.read())
+
+# نقطة النهاية (Endpoint) لاستقبال الصورة والنص وإرجاع النتيجة
+@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))