Update app.py

app.py

@@ -11,10 +11,11 @@ emotion_pipeline = pipeline("text-classification", model="j-hartmann/emotion-eng
 chat_histories = {}
 
 def chatbot_response(message, session_id="default"):
+    """Core function that handles both chat and emotion analysis"""
     if session_id not in chat_histories:
         chat_histories[session_id] = []
 
-    # Generate response
+    # Generate chatbot response
     input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors="pt")
     output = model.generate(input_ids, max_length=200, pad_token_id=tokenizer.eos_token_id)
     response = tokenizer.decode(output[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
@@ -28,16 +29,30 @@ def chatbot_response(message, session_id="default"):
     chat_histories[session_id].append((message, response))
     return response, emotion, score
 
+# ------------------ API Interface ------------------
+def api_predict(message: str, session_id: str = "default"):
+    """Endpoint for /predict that returns JSON"""
+    response, emotion, score = chatbot_response(message, session_id)
+    return {
+        "response": response,
+        "emotion": emotion,
+        "score": score,
+        "session_id": session_id
+    }
+
 # ------------------ Web Interface ------------------
-with gr.Blocks() as demo:
+with gr.Blocks(title="Mental Health Chatbot") as web_interface:
     gr.Markdown("# 🤖 Mental Health Chatbot")
+    
     with gr.Row():
         with gr.Column():
-            chatbot = gr.Chatbot()
-            msg = gr.Textbox(label="Your Message")
-            session_id = gr.Textbox(label="Session ID", value="default")
-            btn = gr.Button("Send")
-            clear_btn = gr.Button("Clear History")
+            chatbot = gr.Chatbot(height=400)
+            msg = gr.Textbox(placeholder="Type your message...", label="You")
+            with gr.Row():
+                session_id = gr.Textbox(label="Session ID", value="default")
+                submit_btn = gr.Button("Send", variant="primary")
+                clear_btn = gr.Button("Clear")
+        
         with gr.Column():
             emotion_out = gr.Textbox(label="Detected Emotion")
             score_out = gr.Number(label="Confidence Score")
@@ -47,19 +62,41 @@ with gr.Blocks() as demo:
         chat_history.append((message, response))
         return "", chat_history, emotion, score
 
-    btn.click(respond, [msg, chatbot, session_id], [msg, chatbot, emotion_out, score_out])
-    msg.submit(respond, [msg, chatbot, session_id], [msg, chatbot, emotion_out, score_out])
-    clear_btn.click(lambda s_id: ([], "", 0.0) if s_id in chat_histories else ([], "", 0.0),
-                    inputs=[session_id],
-                    outputs=[chatbot, emotion_out, score_out])
+    submit_btn.click(
+        respond,
+        [msg, chatbot, session_id],
+        [msg, chatbot, emotion_out, score_out]
+    )
+    msg.submit(
+        respond,
+        [msg, chatbot, session_id],
+        [msg, chatbot, emotion_out, score_out]
+    )
+    clear_btn.click(
+        lambda s_id: ([], "", 0.0) if s_id in chat_histories else ([], "", 0.0),
+        [session_id],
+        [chatbot, emotion_out, score_out]
+    )
+
+# ------------------ Mount Interfaces ------------------
+app = gr.mount_gradio_app(
+    gr.routes.App(),
+    web_interface,
+    path="/"
+)
 
-# ------------------ API Endpoint for /api/predict ------------------
-predict_api = gr.Interface(
-    fn=chatbot_response,
-    inputs=[gr.Textbox(label="Message"), gr.Textbox(label="Session ID")],
-    outputs=[gr.Textbox(label="Response"), gr.Textbox(label="Emotion"), gr.Number(label="Score")]
+app = gr.mount_gradio_app(
+    app,
+    gr.Interface(
+        fn=api_predict,
+        inputs=[gr.Textbox(), gr.Textbox()],
+        outputs=gr.JSON(),
+        title="API Predict",
+        description="Use this endpoint for programmatic access"
+    ),
+    path="/predict"
 )
 
-# ------------------ Launch for Gradio Spaces ------------------
-demo.launch()
-predict_api.launch(inline=False)
+# ------------------ Launch ------------------
+if __name__ == "__main__":
+    app.launch(show_api=False)  # We manually mounted our API