Update app.py

app.py

@@ -43,6 +43,23 @@ async def process_constraints(constraints: InputConstraints):
     result = process_input_from_constraints(constraints.constraints, global_tech, global_tech_embeddings)
     return {"technologies": result}
 
+
+def make_json_serializable(data):
+    """
+    Recursively convert tensors to floats in a data structure
+    so it can be passed to json.dumps.
+    """
+    if isinstance(data, dict):
+        return {k: make_json_serializable(v) for k, v in data.items()}
+    elif isinstance(data, list):
+        return [make_json_serializable(item) for item in data]
+    elif isinstance(data, tuple):
+        return tuple(make_json_serializable(item) for item in data)
+    elif hasattr(data, 'item'):  # torch.Tensor with single value
+        return float(data.item())
+    else:
+        return data
+        
 def process_input_gradio(problem_description: str):
     """
     Processes the input problem description step-by-step for Gradio.
@@ -86,8 +103,14 @@ def process_input_gradio(problem_description: str):
         for item in result_similarities
     }
     
-    best_combinations_display = json.dumps(best_combinations, indent=2)
-    best_technologies_display = json.dumps(best_technologies, indent=2)
+    
+    # Convert to JSON-safe format
+    safe_best_combinations = make_json_serializable(best_combinations)
+    safe_best_technologies = make_json_serializable(best_technologies)
+    
+    # Now this will work safely:
+    best_combinations_display = json.dumps(safe_best_combinations, indent=2)
+    best_technologies_display = json.dumps(safe_best_technologies, indent=2)
 
     return (
         prompt,