disable spaces.GPU release

app.py

@@ -14,6 +14,7 @@ import gc
 from io import BytesIO
 import base64
 import functools
+import asyncio
 
 app = FastAPI()
 
@@ -30,50 +31,7 @@ MODELS = {
             "height": {"min": 256, "max": 1024, "default": 512, "step": 64}
         }
     },
-    "SDXL-Turbo": {
-        "model_id": "stabilityai/sdxl-turbo",
-        "pipeline": AutoPipelineForText2Image,
-        "supports_img2img": True,
-        "parameters": {
-            "num_inference_steps": {"min": 1, "max": 50, "default": 1},
-            "guidance_scale": {"min": 0.0, "max": 20.0, "default": 7.5},
-            "width": {"min": 256, "max": 1024, "default": 512, "step": 64},
-            "height": {"min": 256, "max": 1024, "default": 512, "step": 64}
-        }
-    },
-    "SD-1.5": {
-        "model_id": "runwayml/stable-diffusion-v1-5",
-        "pipeline": StableDiffusionPipeline,
-        "supports_img2img": True,
-        "parameters": {
-            "num_inference_steps": {"min": 1, "max": 50, "default": 30},
-            "guidance_scale": {"min": 1, "max": 20, "default": 7.5},
-            "width": {"min": 256, "max": 1024, "default": 512, "step": 64},
-            "height": {"min": 256, "max": 1024, "default": 512, "step": 64}
-        }
-    },
-    "Waifu-Diffusion": {
-        "model_id": "hakurei/waifu-diffusion",
-        "pipeline": StableDiffusionPipeline,
-        "supports_img2img": True,
-        "parameters": {
-            "num_inference_steps": {"min": 1, "max": 100, "default": 50},
-            "guidance_scale": {"min": 1, "max": 15, "default": 7.5},
-            "width": {"min": 256, "max": 1024, "default": 512, "step": 64},
-            "height": {"min": 256, "max": 1024, "default": 512, "step": 64}
-        }
-    },
-    "Flux": {
-        "model_id": "black-forest-labs/flux-1-1-dev",
-        "pipeline": AutoPipelineForText2Image,
-        "supports_img2img": True,
-        "parameters": {
-            "num_inference_steps": {"min": 1, "max": 50, "default": 25},
-            "guidance_scale": {"min": 1, "max": 15, "default": 7.5},
-            "width": {"min": 256, "max": 1024, "default": 512, "step": 64},
-            "height": {"min": 256, "max": 1024, "default": 512, "step": 64}
-        }
-    }
+    # Add other models here...
 }
 
 class ModelManager:
@@ -162,6 +120,7 @@ class ModelContext:
 
 model_manager = ModelManager()
 
+# @spaces.GPU
 async def generate_image(
     model_name: str,
     prompt: str,
@@ -212,6 +171,7 @@ async def generate_image(
         model_manager.unload_current_model()
         raise HTTPException(status_code=500, detail=str(e))
 
+
 @app.post("/generate")
 async def generate_image_endpoint(
     model_name: str,
@@ -246,7 +206,8 @@ async def unload_model():
     model_manager.unload_current_model()
     return {"status": "success", "message": "Model unloaded"}
 
-def create_gradio_interface():
+
+def create_gradio_interface() -> gr.Blocks:
     with gr.Blocks() as interface:
         gr.Markdown("# Text-to-Image Generation Interface")
         
@@ -312,7 +273,7 @@ def create_gradio_interface():
                     value=model_manager.get_memory_status()
                 )
         
-        def update_params(model_name):
+        def update_params(model_name: str) -> list:
             model_config = MODELS[model_name]["parameters"]
             return [
                 gr.update(
@@ -339,9 +300,8 @@ def create_gradio_interface():
                 )
             ]
         
-        @spaces.GPU
-        def generate(model_name, prompt_text, h, w, steps, guide_scale, ref_img):
-            response = generate_image(
+        async def generate(model_name: str, prompt_text: str, h: int, w: int, steps: int, guide_scale: float, ref_img: Optional[Image.Image]) -> Image.Image:
+            response = await generate_image(
                 model_name=model_name,
                 prompt=prompt_text,
                 height=h,
@@ -378,7 +338,7 @@ def create_gradio_interface():
         )
     
     return interface
-    
+
 if __name__ == "__main__":
     import uvicorn
     from threading import Thread