Update app.py

app.py

@@ -2,20 +2,18 @@ import os
 import gradio as gr
 from openai import OpenAI
 
-# ---- Configuration ----
-
 HF_API_KEY = os.getenv("HF_TOKEN")
 
 client = OpenAI(
     base_url="https://router.huggingface.co/v1",
-    api_key=HF_API_KEY
+    api_key=HF_API_KEY,
 )
 
-# ---- Chat function ----
 def chat_with_model(user_message, history):
     if history is None:
         history = []
 
+    # Build the full conversation history for the API
     messages = [{"role": "system", "content": "You are a helpful assistant."}]
     for human, bot in history:
         messages.append({"role": "user", "content": human})
@@ -28,22 +26,27 @@ def chat_with_model(user_message, history):
             model="openai/gpt-oss-20b:nebius",
             messages=messages
         )
+        
+        reply = completion.choices[0].message["content"]
+
+        # Append to history in correct Gradio format (tuple)
+        history.append((user_message, reply))
 
-        assistant_reply = completion.choices[0].message["content"]
-        history.append((user_message, assistant_reply))
-        return assistant_reply, history
+        return history, history
 
     except Exception as e:
-        return f"Error: {str(e)}", history
+        error_msg = f"Error: {str(e)}"
+        history.append((user_message, error_msg))
+        return history, history
 
 
-# ---- Gradio UI ----
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 Chatbot using HuggingFace Router (OpenAI API Compatible)")
-    chatbot = gr.Chatbot(height=450)
-    text_input = gr.Textbox(label="Your message")
-
-    text_input.submit(chat_with_model, [text_input, chatbot], [chatbot])
-    text_input.submit(lambda: "", None, text_input)  # clear input
+    gr.Markdown("# 🤖 Chat with HuggingFace Router (OpenAI Compatible)")
+    
+    chatbot = gr.Chatbot(height=500)
+    text_input = gr.Textbox(label="Type your message")
+    
+    text_input.submit(chat_with_model, [text_input, chatbot], [chatbot, chatbot])
+    text_input.submit(lambda: "", None, text_input)
 
 demo.launch()