Update app.py

app.py

@@ -1,9 +1,7 @@
-import gradio as gr
+"""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")
 
 
@@ -39,9 +37,7 @@ def respond(
         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=[
@@ -59,5 +55,56 @@ demo = gr.ChatInterface(
 )
 
 
+if __name__ == "__main__":
+    demo.launch()
+"""
+
+import os
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Retrieve the API token from the environment variable
+API_TOKEN = os.getenv("HF_READ_TOKEN")
+
+# Initialize the Hugging Face Inference Client
+client = InferenceClient(
+    "mistralai/Mistral-Nemo-Instruct-2407",
+    token=API_TOKEN
+)
+
+# System prompt to define model behavior
+system_prompt = "You are a helpful assistant that provides concise and accurate answers."
+
+# Function to handle the chat completion
+def hf_chat(user_input):
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_input}
+    ]
+    response = ""
+    for message in client.chat_completion(
+        messages=messages,
+        max_tokens=500,
+        stream=True,
+    ):
+        response += message.choices[0].delta.content
+    return response
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Hugging Face Chat Completion")
+    with gr.Row():
+        with gr.Column():
+            user_input = gr.Textbox(
+                label="Enter your message", 
+                placeholder="Ask me anything..."
+            )
+            submit_btn = gr.Button("Submit")
+        with gr.Column():
+            output = gr.Textbox(label="Response")
+
+    submit_btn.click(fn=hf_chat, inputs=user_input, outputs=output)
+
+# Launch Gradio app
 if __name__ == "__main__":
     demo.launch()