Update app.py

app.py

@@ -1,3 +1,58 @@
+# import gradio as gr
+# from huggingface_hub import InferenceClient
+# import os
+
+# client = InferenceClient(
+#     model="mistralai/Mistral-Small-24B-Instruct-2501",
+#     token=os.getenv('HF_TOKEN')
+# )
+
+# def chat_fn(message, system_message, history_str, max_tokens, temperature, top_p):
+#     # Convert history string (optional) to message list
+#     messages = [{"role": "system", "content": system_message}]
+    
+#     if history_str:
+#         # Format: user1||assistant1\nuser2||assistant2
+#         for pair in history_str.split("\n"):
+#             if "||" in pair:
+#                 user_msg, assistant_msg = pair.split("||", 1)
+#                 messages.append({"role": "user", "content": user_msg})
+#                 messages.append({"role": "assistant", "content": assistant_msg})
+    
+#     messages.append({"role": "user", "content": message})
+
+#     # Get response from HF
+#     response = ""
+#     for chunk in client.chat_completion(
+#         messages=messages,
+#         stream=True,
+#         max_tokens=max_tokens,
+#         temperature=temperature,
+#         top_p=top_p,
+#     ):
+#         response += chunk.choices[0].delta.content or ""
+    
+#     return response
+
+# demo = gr.Interface(
+#     fn=chat_fn,
+#     inputs=[
+#         gr.Textbox(lines=2, label="User Message"),
+#         gr.Textbox(value="You are a friendly Chatbot.", label="System Prompt"),
+#         gr.Textbox(lines=4, placeholder="user||bot\nuser2||bot2", label="Conversation History (optional)"),
+#         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
+#         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+#         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
+#     ],
+#     outputs="text",
+#     allow_flagging="never",
+#     title="LLM Budaya",
+#     description="Chatbot menggunakan model HuggingFace Zephyr-7B"
+# )
+
+# if __name__ == "__main__":
+#     demo.launch()
+
 import gradio as gr
 from huggingface_hub import InferenceClient
 import os
@@ -7,47 +62,30 @@ client = InferenceClient(
     token=os.getenv('HF_TOKEN')
 )
 
-def chat_fn(message, system_message, history_str, max_tokens, temperature, top_p):
-    # Convert history string (optional) to message list
-    messages = [{"role": "system", "content": system_message}]
+def simple_chat_fn(message, system_prompt, max_tokens, temperature, top_p):
+    prompt = f"{system_prompt}\n\nUser: {message}\nAssistant:"
     
-    if history_str:
-        # Format: user1||assistant1\nuser2||assistant2
-        for pair in history_str.split("\n"):
-            if "||" in pair:
-                user_msg, assistant_msg = pair.split("||", 1)
-                messages.append({"role": "user", "content": user_msg})
-                messages.append({"role": "assistant", "content": assistant_msg})
-    
-    messages.append({"role": "user", "content": message})
-
-    # Get response from HF
-    response = ""
-    for chunk in client.chat_completion(
-        messages=messages,
-        stream=True,
-        max_tokens=max_tokens,
+    response = client.text_generation(
+        prompt=prompt,
+        max_new_tokens=max_tokens,
         temperature=temperature,
         top_p=top_p,
-    ):
-        response += chunk.choices[0].delta.content or ""
-    
+        stream=False
+    )
     return response
 
 demo = gr.Interface(
-    fn=chat_fn,
+    fn=simple_chat_fn,
     inputs=[
         gr.Textbox(lines=2, label="User Message"),
-        gr.Textbox(value="You are a friendly Chatbot.", label="System Prompt"),
-        gr.Textbox(lines=4, placeholder="user||bot\nuser2||bot2", label="Conversation History (optional)"),
+        gr.Textbox(value="You are a helpful and concise assistant.", label="System Prompt"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
     ],
     outputs="text",
+    title="Mistral 24B Chat (Single Turn)",
     allow_flagging="never",
-    title="LLM Budaya",
-    description="Chatbot menggunakan model HuggingFace Zephyr-7B"
 )
 
 if __name__ == "__main__":