Update app.py

app.py

@@ -80,16 +80,24 @@ def classify_text(input_text, k=20):
 
     # Construct OpenAI prompt
     prompt = f"""
-    You are a mental health specialist. Classify the text into Stress, Anxiety, Depression, or Other:
-    ### Examples:
-    {examples}
-    ### Text to Classify:
+    You are a mental health specialist. Analyze the provided text and classify it into one or more of the following categories: Stress, Anxiety, Depression, or Other.
+
+    Respond **only** in JSON format with the following keys:
+    - Ground_Truth_Stress: 1 or 0
+    - Ground_Truth_Anxiety: 1 or 0
+    - Ground_Truth_Depression: 1 or 0
+    - Ground_Truth_Other_binary: 1 or 0
+
+    Here is the text to classify:
     "{input_text}"
-    ### Output Format:
-    - **Ground_Truth_Stress**: 1 or 0
-    - **Ground_Truth_Anxiety**: 1 or 0
-    - **Ground_Truth_Depression**: 1 or 0
-    - **Ground_Truth_Other_binary**: 1 or 0
+
+    ### Example Response:
+    {{
+      "Ground_Truth_Stress": 0,
+      "Ground_Truth_Anxiety": 1,
+      "Ground_Truth_Depression": 0,
+      "Ground_Truth_Other_binary": 0
+    }}
     """
 
     try:
@@ -101,19 +109,19 @@ def classify_text(input_text, k=20):
             model="gpt-4",
             temperature=0,
         )
-        print("OpenAI Response:", response)
+        content = response.choices[0].message.content.strip()
+        print("Raw Response Content:", content)
         
-        # Extract and parse the content
-        content = response.choices[0].message.content
-        print("Response Content:", content)
+        # Attempt to parse as JSON
         return json.loads(content)
     except json.JSONDecodeError:
-        print("Failed to decode JSON from OpenAI response.")
-        return {"error": f"Invalid JSON response: {content}"}
+        print("Failed to decode JSON. Returning raw content.")
+        return {"error": "Failed to decode JSON", "raw_response": content}
     except Exception as e:
         print(f"Error occurred: {e}")
         return {"error": str(e)}
 
+
 # Gradio Interface
 interface = gr.Interface(
     fn=classify_text,