app

app.py

@@ -63,43 +63,38 @@ def init_pipeline_if_needed():
     
     # 如果设置了 BASE_MODEL_ID，从私有库加载预配置的 pipeline
     if BASE_MODEL:
-        # 下载并导入私有库中的 pipeline 加载脚本
-        pipeline_loader_path = hf_hub_download(
-            repo_id="Cascade-Inc/private_model",
-            filename=BASE_MODEL,  # 例如: "pipeline_loader.py"
-            token=hf_token,
-            repo_type="space"
+        print(f"Loading pipeline from: {BASE_MODEL}")
+        try:
+            # 下载并导入私有库中的 pipeline 加载脚本
+            pipeline_loader_path = hf_hub_download(
+                repo_id="Cascade-Inc/private_model",
+                filename=BASE_MODEL,  # 应该是 .py 文件，例如: "pipeline_loader.py"
+                token=hf_token,
+                repo_type="space"
+            )
+            
+            # 动态导入
+            import importlib.util
+            spec = importlib.util.spec_from_file_location("pipeline_loader", pipeline_loader_path)
+            pipeline_module = importlib.util.module_from_spec(spec)
+            spec.loader.exec_module(pipeline_module)
+            
+            # 调用私有库中的函数获取 pipeline
+            _pipe = pipeline_module.get_pipeline(hf_token)
+        except Exception as e:
+            print(f"❌ Error loading pipeline from {BASE_MODEL}: {e}")
+            raise ValueError(
+                f"Failed to load pipeline loader from BASE_MODEL_ID='{BASE_MODEL}'. "
+                f"Make sure:\n"
+                f"1. The file exists in Cascade-Inc/private_model space\n"
+                f"2. BASE_MODEL_ID should be a .py file name (e.g., 'pipeline_loader.py')\n"
+                f"3. Not the LoRA path (that's MODEL_PATH)"
+            )
+    else:
+        raise ValueError(
+            "BASE_MODEL_ID environment variable is not set.\n"
+            "Please set it to the pipeline loader filename (e.g., 'pipeline_loader.py')"
         )
-        
-        # 动态导入
-        import importlib.util
-        spec = importlib.util.spec_from_file_location("pipeline_loader", pipeline_loader_path)
-        pipeline_module = importlib.util.module_from_spec(spec)
-        spec.loader.exec_module(pipeline_module)
-        
-        # 调用私有库中的函数获取 pipeline
-        _pipe = pipeline_module.get_pipeline(hf_token)
-    # else:
-        
-    #     if use_int8 or get_gpu_memory_gb() < 33:
-    #         transformer_model = FluxTransformer2DModel.from_pretrained(
-    #             INT8_MODEL,
-    #             torch_dtype=torch.bfloat16,
-    #             use_safetensors=False,
-    #             token=hf_token,
-    #         )
-    #         _pipe = FluxPipeline.from_pretrained(
-    #             INT8_MODEL,
-    #             transformer=transformer_model,
-    #             torch_dtype=torch.bfloat16,
-    #             token=hf_token,
-    #         )
-    #     else:
-    #         _pipe = FluxPipeline.from_pretrained(
-    #             INT8_MODEL,
-    #             torch_dtype=torch.bfloat16,
-    #             token=hf_token,
-    #         )
 
     print("📦 Loading model to CUDA...")
     _pipe = _pipe.to("cuda")