Update app.py

app.py

@@ -4,8 +4,13 @@ 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
 """
+
+# Default client with the first model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Function to switch between models based on selection
+def switch_client(model_name: str):
+    return InferenceClient(model_name)
 
 def respond(
     message,
@@ -14,7 +19,12 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    model_name  # Add this parameter for model selection
 ):
+    # Switch client based on model selection
+    global client
+    client = switch_client(model_name)
+    
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
@@ -39,12 +49,45 @@ def respond(
         response += token
         yield response
 
+    # Adding the model name at the end of the response
+    yield f"\n\n[Response generated by model: {model_name}]"
+
+# Model names and their custom display names
+model_choices = [
+    ("HuggingFaceH4/zephyr-7b-beta", "Lake [Test]"), 
+    ("google/mt5-base", "Lake 1 Base"),
+    ("google/mt5-large", "Lake 1 Advanced")
+]
+
+# Convert model choices into just the model names for the dropdown
+model_names = [model[0] for model in model_choices]
+
+# Function to handle model selection and display name for the model
+def respond_with_model_name(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+    model_name
+):
+    # Find the display name of the selected model
+    model_display_name = dict(model_choices)[model_name]
+    
+    # Call the existing respond function
+    response = list(respond(message, history, system_message, max_tokens, temperature, top_p, model_name))
+    
+    # Add model name at the end of the response
+    response[-1] += f"\n\n[Response generated by: {model_display_name}]"
+    
+    return response
 
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
 demo = gr.ChatInterface(
-    respond,
+    respond_with_model_name,
     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"),
@@ -56,9 +99,9 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)",
         ),
+        gr.Dropdown(model_names, label="Select Model", value=model_names[0])  # Model selection dropdown
     ],
 )
 
-
 if __name__ == "__main__":
     demo.launch()