Update app.py

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
-import json
 
 # Load models
 chatbot_model = "microsoft/DialoGPT-medium"
@@ -14,22 +13,22 @@ chat_histories = {}
 def chatbot_response(message, session_id="default"):
     if session_id not in chat_histories:
         chat_histories[session_id] = []
-    
+
     # Generate 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)
-    
+
     # Detect emotion
     emotion_result = emotion_pipeline(message)
     emotion = emotion_result[0]["label"]
     score = float(emotion_result[0]["score"])
-    
+
     # Store history
     chat_histories[session_id].append((message, response))
     return response, emotion, score
 
-# Gradio Interface (Primary for Spaces)
+# ------------------ Web Interface ------------------
 with gr.Blocks() as demo:
     gr.Markdown("# 🤖 Mental Health Chatbot")
     with gr.Row():
@@ -50,10 +49,17 @@ with gr.Blocks() as demo:
 
     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])
+    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])
+
+# ------------------ 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")]
+)
 
-# For Hugging Face Spaces, Gradio must be the main interface
-if __name__ == "__main__":
-    demo.launch()
+# ------------------ Launch for Gradio Spaces ------------------
+demo.launch()
+predict_api.launch(inline=False)