Update app.py

app.py

@@ -1,12 +1,15 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# Initialize the 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[dict],  # Use a list of dictionaries instead of tuples
+    history: list[tuple[str, str]],
     system_message,
     max_tokens,
     temperature,
@@ -15,13 +18,15 @@ def respond(
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
-        messages.append({"role": val['role'], "content": val['content']})
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
     messages.append({"role": "user", "content": message})
 
     response = ""
-    
-    # Use chat_completion to get responses
+
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -30,15 +35,17 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
+
         response += token
         yield response
 
-# Create the Gradio Interface for API
-api_interface = gr.Interface(
-    fn=respond,
-    inputs=[
-        gr.Textbox(label="Message"),
-        gr.JSON(label="History"),
+
+"""
+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"),
@@ -50,9 +57,8 @@ api_interface = gr.Interface(
             label="Top-p (nucleus sampling)",
         ),
     ],
-    outputs=gr.Textbox(label="Response"),
 )
 
-# Launch the API
+
 if __name__ == "__main__":
-    api_interface.launch(server_name="0.0.0.0", server_port=7860, share=False)  # Set share=False to avoid Hugging Face Spaces
+    demo.launch(share=True)