New updates

app.py

@@ -1,12 +1,8 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -16,16 +12,9 @@ def respond(
     top_p,
 ):
     messages = [{"role": "system", "content": system_message}] + history
-    messages.append({"role":"user","content":message})
+    messages.append({"role": "user", "content": message})
 
     response = ""
-
-    # for val in history:
-    #     if val[0]:
-    #         messages.append({"role": "user", "content": val[0]})
-    #     if val[1]:
-    #         messages.append({"role": "assistant", "content": val[1]})
-
     for part in client.chat_completion(
         messages, max_tokens=max_tokens, stream=True, temperature=temperature,
         top_p=top_p
@@ -34,52 +23,13 @@ def respond(
         if token:
             response += token
 
-    history.append({"role":"user", "content": message})
-    history.append({"role":"assistant", "content": response})
-
-    return history,""
+    history.append({"role": "user", "content": message})
+    history.append({"role": "assistant", "content": response})
 
-    # for message in client.chat_completion(
-    #     messages,
-    #     max_tokens=max_tokens,
-    #     stream=True,
-    #     temperature=temperature,
-    #     top_p=top_p,
-    # ):
-    #     token = message.choices[0].delta.content
-
-    #     response += token
-    #     yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-# demo = gr.ChatInterface(
-#     respond,
-#     additional_inputs=[
-#         gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-#         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=1.0,
-#             value=0.95,
-#             step=0.05,
-#             label="Top-p (nucleus sampling)",
-#         ),
-#     ],
-# )
+    return history, ""
 
 with gr.Blocks() as demo:
-    gr.Markdown("## Zephyr Chatbot with Custom UI")
-
-    chatbot = gr.Chatbot(type="messages", label="Chatbot")
-    state = gr.State([])
-
-    with gr.Row():
-        msg = gr.Textbox(label="Type your message...", scale=6)
-        send_btn = gr.Button("Send", scale=1)
+    gr.Markdown("## Zephyr Chatbot Controls")
 
     role_dropdown = gr.Dropdown(choices=["SDE", "BA"], label="Select Role", value="SDE")
 
@@ -92,30 +42,8 @@ with gr.Blocks() as demo:
         clear_btn = gr.Button("Clear Chat")
         dummy_btn = gr.Button("Dummy Action")
 
-    def handle_submit(message, history, system, max_tokens, temperature, top_p):
-        return respond(message, history, system, max_tokens, temperature, top_p)
-        # final_response = ""
-        # for r in response_gen:
-        #     final_response = r
-        # updated_history = history + [(message, final_response)]
-        # return updated_history, updated_history, ""
-
-    send_btn.click(
-        handle_submit,
-        [msg, state, system, max_tokens, temperature, top_p],
-        [chatbot, state, msg],
-    )
-
-    msg.submit(
-        handle_submit,
-        [msg, state, system, max_tokens, temperature, top_p],
-        [chatbot, state, msg],
-    )
-
-    clear_btn.click(lambda: ([], [], ""), None, [chatbot, state, msg])
-
-    dummy_btn.click(lambda: gr.Info("Dummy action clicked!"), None, None)
-
+    clear_btn.click(lambda: gr.Info("Chat cleared!"))
+    dummy_btn.click(lambda: gr.Info("Dummy action clicked!"))
 
 if __name__ == "__main__":
     demo.launch()