Update app.py

app.py

@@ -1,22 +1,19 @@
 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]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, backend):
+    # Force the AI to generate a website with index.html and specified backend
+    forced_instruction = f"""
+You must generate a complete website structure including at least an index.html.
+Use the following backend structure: {backend}.
+Only use {backend} relevant code and structure, and don't include any other type.
+"""
+    system_message = forced_instruction + "\n\n" + system_message
 
+    messages = [{"role": "system", "content": system_message}]
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
@@ -26,7 +23,6 @@ def respond(
     messages.append({"role": "user", "content": message})
 
     response = ""
-
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,30 +31,22 @@ def respond(
         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,
+    fn=respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value="You are a helpful assistant.", 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)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+        gr.Dropdown(choices=["Flask", "Static", "Node.js"], value="Static", label="Website Backend"),
     ],
+    title="WebGen AI",
+    description="Ask the AI to build a website with a specific backend (Flask, Static, or Node.js). It will always include index.html.",
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()