Update README.md

README.md

@@ -27,35 +27,38 @@ You should use `tugce` to trigger the image generation.
 ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
 
 ```py
-from diffusers import AutoPipelineForText2Image
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import FileResponse
 import torch
+from diffusers import AutoPipelineForText2Image
+import io
+
+app = FastAPI()
 
 # Model ve LoRA'yı yükle
 pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
 pipeline.load_lora_weights('codermert/tugce2-lora', weight_name='flux_train_replicate.safetensors')
 
-# Farklı boyutlar
-sizes = [
-    (512, 512),  # 1:1
-    (768, 512),  # 3:2
-    (640, 480),  # 4:3
-    (896, 504),  # 16:9
-]
-
-# Prompt
-prompt = "tugce in a beautiful garden"
-
-# Her boyut için görüntü oluştur
-for width, height in sizes:
-    image = pipeline(
-        prompt,
-        width=width,
-        height=height
-    ).images[0]
-    
-    # Görüntüyü kaydet
-    image.save(f"tugce_{width}x{height}.png")
-    print(f"Oluşturuldu: tugce_{width}x{height}.png")
+@app.post("/generate_image")
+async def generate_image(prompt: str, width: int, height: int):
+    try:
+        image = pipeline(
+            prompt,
+            width=width,
+            height=height
+        ).images[0]
+        
+        img_byte_arr = io.BytesIO()
+        image.save(img_byte_arr, format='PNG')
+        img_byte_arr.seek(0)
+        
+        return FileResponse(img_byte_arr, media_type="image/png")
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)
 ```
 
 For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)