chore: ignore pyc and __pycache__

app.py

@@ -138,7 +138,40 @@ def get_pipe() -> FluxFillPipeline:
             "or pre-download to a local cache directory."
         ) from e
 
-    # ……你原有的 LoRA 加载逻辑……
+    # -------- LoRA (stage1) --------
+    lora_dir = CODE_EDIT / "stage1" / "checkpoint-4800"
+    lora_file = "pytorch_lora_weights.safetensors"   # 你的实际文件名
+    adapter_name = "stage1"
+
+    if lora_dir.exists():
+        try:
+            import peft  # just to assert backend is present
+            print(f"[pipe] loading LoRA from: {lora_dir}/{lora_file}")
+            pipe.load_lora_weights(
+                str(lora_dir),
+                weight_name=lora_file,          # 关键：指定文件名
+                adapter_name=adapter_name       # 给一个可切换的名字
+            )
+            # 新版 diffusers：优先 set_adapters
+            try:
+                pipe.set_adapters(adapter_name, scale=1.0)
+                print(f"[pipe] set_adapters('{adapter_name}', scale=1.0)")
+            except Exception as e_set:
+                print(f"[pipe] set_adapters not available ({e_set}); trying fuse_lora()")
+                # 旧版/或不支持 set_adapters 的 pipeline：融合 LoRA
+                try:
+                    pipe.fuse_lora(lora_scale=1.0)
+                    print("[pipe] fuse_lora(lora_scale=1.0) done")
+                except Exception as e_fuse:
+                    print(f"[pipe] fuse_lora failed: {e_fuse}")
+            print("[pipe] LoRA ready ✅")
+        except ImportError:
+            print("[pipe] peft not installed; LoRA will be skipped (add `peft>=0.11` to requirements).")
+        except Exception as e:
+            print(f"[pipe] load_lora_weights failed (continue without): {e}")
+    else:
+        print(f"[pipe] LoRA path not found: {lora_dir} (continue without)")
+
     _PIPE = pipe
     return pipe