Deploy model_router.py to backend/ directory

backend/model_router.py

@@ -332,14 +332,29 @@ class ModelRouter:
                 
                 # Format output based on task type
                 if "summarization" in model_key:
+                    if isinstance(model_output, list) and model_output:
+                        summary_text = model_output[0].get("summary_text", "") or model_output[0].get("generated_text", "")
+                        if not summary_text:
+                            summary_text = str(model_output[0])
+                    elif isinstance(model_output, dict):
+                        summary_text = model_output.get("summary_text", "") or model_output.get("generated_text", "")
+                    else:
+                        summary_text = str(model_output)
+                        
                     return {
-                        "summary": model_output[0]["summary_text"] if isinstance(model_output, list) and model_output else "Summary generated",
+                        "summary": summary_text[:500] if summary_text else "Summary generated",
                         "model": task['model_name'],
                         "confidence": 0.85
                     }
                 
                 elif "ner" in model_key:
-                    entities = model_output if isinstance(model_output, list) else []
+                    if isinstance(model_output, list):
+                        entities = model_output
+                    elif isinstance(model_output, dict) and "entities" in model_output:
+                        entities = model_output["entities"]
+                    else:
+                        entities = []
+                    
                     return {
                         "entities": self._format_ner_output(entities),
                         "model": task['model_name'],
@@ -347,9 +362,19 @@ class ModelRouter:
                     }
                 
                 elif "qa" in model_key:
+                    if isinstance(model_output, list) and model_output:
+                        answer = model_output[0].get("answer", "") or str(model_output[0])
+                        score = model_output[0].get("score", 0.75)
+                    elif isinstance(model_output, dict):
+                        answer = model_output.get("answer", "Analysis completed")
+                        score = model_output.get("score", 0.75)
+                    else:
+                        answer = str(model_output)
+                        score = 0.75
+                        
                     return {
-                        "answer": model_output.get("answer", "Analysis completed"),
-                        "score": model_output.get("score", 0.75),
+                        "answer": answer[:500],
+                        "score": score,
                         "model": task['model_name']
                     }