From 7d8e991c1ffad688728f3e7396beee8eb4eff720 Mon Sep 17 00:00:00 2001 From: Roland Tannous Date: Sat, 14 Feb 2026 17:25:37 +0000 Subject: [PATCH] added print statements for activate_lora_adapter --- studio/backend/core/inference/inference.py | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/studio/backend/core/inference/inference.py b/studio/backend/core/inference/inference.py index ff44777dbd..a4580baa71 100644 --- a/studio/backend/core/inference/inference.py +++ b/studio/backend/core/inference/inference.py @@ -221,25 +221,32 @@ class InferenceBackend: """ model = self.models[base_model_name].get("model") adapter_name_to_load = lora_path.split("/")[-1].replace(".", "_") + print(f"[DEBUG] activate_lora_adapter called. base_model_name='{base_model_name}', lora_path='{lora_path}'") + print(f"[DEBUG] adapter_name_to_load='{adapter_name_to_load}'") + print(f"[DEBUG] Model type BEFORE load_adapter: {model.__class__.__name__}") + print(f"[DEBUG] Has peft_config? {hasattr(model, 'peft_config')}, keys={list(getattr(model, 'peft_config', {}).keys())}") try: # At this point, the model should be clean thanks to revert_to_base_model. # We can now safely load and set the new adapter. # Step 3: Load the new adapter. - logger.info(f"Loading adapter '{adapter_name_to_load}' from '{lora_path}'") + print(f"[DEBUG] Calling model.load_adapter('{lora_path}', adapter_name='{adapter_name_to_load}')...") model.load_adapter(lora_path, adapter_name=adapter_name_to_load) + print(f"[DEBUG] Model type AFTER load_adapter: {model.__class__.__name__}") + print(f"[DEBUG] peft_config keys AFTER load: {list(getattr(model, 'peft_config', {}).keys())}") # Step 4: Set the new adapter as active. - logger.info(f"Setting '{adapter_name_to_load}' as the active adapter.") + print(f"[DEBUG] Calling model.set_adapter('{adapter_name_to_load}')...") model.set_adapter(adapter_name_to_load) + print(f"[DEBUG] activate_lora_adapter SUCCESS. Model type: {model.__class__.__name__}") return True, adapter_name_to_load except Exception as e: # This will catch the "already exists" error if revert_to_base_model failed. - logger.error(f"Failed to activate LoRA adapter '{adapter_name_to_load}': {e}") + print(f"[DEBUG] activate_lora_adapter FAILED: {e}") import traceback - logger.error(traceback.format_exc()) + traceback.print_exc() return False, None pass