Update app.py

app.py

@@ -19,52 +19,27 @@ def respond(
     # Create client for the selected model
     client = get_client(model_name)
     
-    # Check if the model is one of the problematic models
-    if model_name in ["indonlp/cendol-mt5-small-inst", "indonlp/cendol-mt5-small-chat"]:
-        # For these models, we simply concatenate the conversation into a single string
-        history_str = ""
-        for user_msg, assistant_msg in history:
-            if user_msg:
-                history_str += f"{user_msg}\n"
-            if assistant_msg:
-                history_str += f"{assistant_msg}\n"
-        
-        # Add the latest user message
-        history_str += f"{message}\n"
-        
-        # Pass the entire conversation history as a plain text prompt
-        response = client.text_generation(
-            history_str,  # Single string as input
-            max_new_tokens=max_tokens,
-            temperature=temperature,
-            top_p=top_p
-        )
-        
-        # Since response is a string, return it directly
-        full_response = response
-    else:
-        # For other models, we use a structured format with roles
-        messages = [{"role": "system", "content": system_message}]
-        for val in history:
-            if val[0]:
-                messages.append({"role": "user", "content": val[0]})
-            if val[1]:
-                messages.append({"role": "assistant", "content": val[1]})
-        
-        # Add the latest user message
-        messages.append({"role": "user", "content": message})
-        
-        # Make the request
-        response = client.chat_completion(
-            messages,
-            max_tokens=max_tokens,
-            temperature=temperature,
-            top_p=top_p,
-            stream=False
-        )
-        
-        # Extract the full response for chat models
-        full_response = response.choices[0].message["content"]
+    messages = [{"role": "system", "content": system_message}]
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+    
+    # Add the latest user message
+    messages.append({"role": "user", "content": message})
+    
+    # Make the request
+    response = client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        stream=False
+    )
+    
+    # Extract the full response for chat models
+    full_response = response.choices[0].message["content"]
     
     return full_response
 
@@ -74,7 +49,7 @@ demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=2.0, value=1.0, step=0.1, label="Temperature"),
         gr.Slider(
             minimum=0.1,
             maximum=1.0,