Update app_lora.py

app_lora.py

@@ -97,6 +97,46 @@ log(f"USE_CPU_OFFLOAD       : {USE_CPU_OFFLOAD}")
 
 log_system_stats("BEFORE TRANSFORMER LOAD")
 
+# ============================================================
+# LORA  SETTINGS
+# ============================================================
+loaded_loras = {}  # Keep track of which LoRAs are already loaded
+
+def apply_lora(repo_name, lora_filename, strength):
+    global pipe, loaded_loras
+    if pipe is None:
+        return "❌ Pipeline not initialized"
+    if not lora_filename:
+        return "⚠️ No LoRA file selected"
+
+    adapter_name = f"ui_lora_{lora_filename.replace('/', '_')}"  # unique adapter name per file
+
+    try:
+        # Load the LoRA only if not already loaded
+        if adapter_name not in loaded_loras:
+            pipe.load_lora_weights(
+                repo_name,
+                weight_name=lora_filename,
+                adapter_name=adapter_name
+            )
+            loaded_loras[adapter_name] = lora_filename
+            log(f"📥 LoRA loaded into memory: {repo_name}/{lora_filename}")
+        else:
+            log(f"♻️ LoRA already loaded: {repo_name}/{lora_filename}")
+
+        # Activate the adapter
+        pipe.set_adapters([adapter_name], [strength])
+        log(f"✅ Applied LoRA: {repo_name}/{lora_filename} (strength={strength})")
+
+        if hasattr(pipe, "peft_config"):
+            log(f"🎯 Active adapters: {list(pipe.peft_config.keys())}")
+
+        return "LoRA applied"
+
+    except Exception as e:
+        log(f"❌ Failed to apply LoRA: {e}")
+        return f"Failed: {e}"
+
 
 # ============================================================
 # FUNCTION TO CONVERT LATENTS TO IMAGE
@@ -994,6 +1034,9 @@ with gr.Blocks(title="Z-Image-Turbo") as demo:
     # =========================
     # CALLBACKS
     # =========================
+     ------------------------
+    # CALLBACKS
+    # ------------------------
     def refresh_lora_list(repo_name):
         files = list_loras_from_repo(repo_name)
         if not files:
@@ -1005,29 +1048,27 @@ with gr.Blocks(title="Z-Image-Turbo") as demo:
     refresh_lora_btn.click(refresh_lora_list, inputs=[lora_repo], outputs=[lora_file])
 
     def apply_lora(repo_name, lora_filename, strength):
-        global pipe
+        global pipe, loaded_loras
         if pipe is None:
             return "❌ Pipeline not initialized"
         if not lora_filename:
             return "⚠️ No LoRA file selected"
 
+        adapter_name = f"ui_lora_{lora_filename.replace('/', '_')}"
         try:
-            pipe.load_lora_weights(
-                repo_name,
-                weight_name=lora_filename,
-                adapter_name="ui_lora"
-            )
-            pipe.set_adapters(["ui_lora"], [strength])
-            log(f"✅ Applied LoRA: {repo_name}/{lora_filename} (strength={strength})")
-            if hasattr(pipe, "peft_config"):
-                log(f"🎯 Active adapters: {list(pipe.peft_config.keys())}")
-            return "LoRA applied"
+            if adapter_name not in loaded_loras:
+                pipe.load_lora_weights(repo_name, weight_name=lora_filename, adapter_name=adapter_name)
+                loaded_loras[adapter_name] = lora_filename
+                log(f"📥 Loaded LoRA: {lora_filename}")
+
+            pipe.set_adapters([adapter_name], [strength])
+            log(f"✅ Applied LoRA adapter: {adapter_name} (strength={strength})")
+            return f"LoRA applied: {lora_filename}"
+
         except Exception as e:
             log(f"❌ Failed to apply LoRA: {e}")
             return f"Failed: {e}"
 
-    apply_lora_btn.click(apply_lora, inputs=[lora_repo, lora_file, lora_strength], outputs=[logs_box])
-
     def clear_lora():
         global pipe
         if pipe is None: