fina p3

src/inference_logic.py

@@ -1,4 +1,3 @@
-import torch
 import re
 import ast
 import sys
@@ -9,6 +8,11 @@ import json
 import datetime
 import requests
 
+try:
+    import torch
+except ImportError:
+    torch = None
+
 try:
     from transformers import Qwen3VLForConditionalGeneration, AutoProcessor
     from peft import PeftModel
@@ -72,8 +76,8 @@ def load_models():
     
     if base_model is not None: return
     
-    if not torch.cuda.is_available():
-        logger.warning("CUDA is not available. This application requires a GPU for local models. Switching to LITE_MODE.")
+    if torch is None or not torch.cuda.is_available():
+        logger.warning("CUDA is not available or torch is missing. This application requires a GPU for local models. Switching to LITE_MODE.")
         LITE_MODE = True
         return
     
@@ -107,7 +111,7 @@ def switch_active_model(model_name: str):
 
 def inference_step(video_path, prompt, generation_kwargs, sampling_fps, pred_glue=None):
     global processor, active_model
-    if active_model is None: raise RuntimeError("Models not loaded.")
+    if active_model is None or torch is None: raise RuntimeError("Models not loaded.")
 
     messages =[
         {"role": "user", "content":[
@@ -321,7 +325,7 @@ async def run_gemini_labeling_pipeline(video_path: str, caption: str, transcript
                     
                     macro_prompt = FCOT_MACRO_PROMPT.format(system_persona=system_persona, caption=caption, transcript=transcript)
                     save_debug_log(request_id, 'prompt', macro_prompt, attempt, 'fcot_macro')
-                    inputs1 = [macro_prompt]
+                    inputs1 =[macro_prompt]
                     if uploaded_file: inputs1.insert(0, uploaded_file)
                     res1 = await loop.run_in_executor(None, lambda: chat.send_message(inputs1))
                     macro_hypothesis = res1.text
@@ -713,4 +717,4 @@ async def run_nrp_labeling_pipeline(video_path: str, caption: str, transcript: s
 
     except Exception as e:
         yield f"ERROR: {e}"
-        logger.error("NRP Labeling Error", exc_info=True)
+        logger.error("NRP Labeling Error", exc_info=True)