Update app.py

app.py

@@ -21,11 +21,11 @@ except Exception as e:
     model_loaded = False
     print(f"Error loading model: {e}")
 
-# --- Core Analysis Function ---
+# --- Core Analysis Function (Final Robust Version) ---
 @spaces.GPU()
 def analyze_symptoms(symptom_image: Image.Image, symptoms_text: str):
     """
-    Analyzes user's symptoms using the definitive calling convention.
+    Analyzes user's symptoms with robust input handling to prevent state-related errors.
     """
     if not model_loaded:
         return "Error: The AI model could not be loaded. Please check the Space logs."
@@ -43,7 +43,10 @@ def analyze_symptoms(symptom_image: Image.Image, symptoms_text: str):
         )
 
         user_content = []
-        user_content.append({"type": "text", "text": symptoms_text})
+        
+        # *** THE FIX: Only add elements to the list if they contain content ***
+        if symptoms_text:
+            user_content.append({"type": "text", "text": symptoms_text})
         
         if symptom_image:
             user_content.append({"type": "image", "image": symptom_image})
@@ -53,17 +56,14 @@ def analyze_symptoms(symptom_image: Image.Image, symptoms_text: str):
             {"role": "user", "content": user_content}
         ]
         
-        # *** THE FIX: Increased the token limit to prevent truncated output ***
         generation_args = {
-            "max_new_tokens": 1024,  # Increased from 512 to 1024
+            "max_new_tokens": 1024,
             "do_sample": True,
             "temperature": 0.7,
         }
         
-        # The entire messages structure is passed to the `text` argument.
         output = pipe(text=messages, **generation_args)
         
-        # Extract the content of the last generated message.
         result = output[0]["generated_text"][-1]["content"]
 
         disclaimer = "\n\n***Disclaimer: I am an AI assistant and not a medical professional. This is not a diagnosis. Please consult a doctor for any health concerns.***"
@@ -112,4 +112,4 @@ with gr.Blocks(theme=gr.themes.Soft(), title="AI Symptom Analyzer") as demo:
 
 if __name__ == "__main__":
     print("Starting Gradio interface...")
-    demo.launch(debug=True)
+    demo.launch(debug=True)