Update app.py

app.py

@@ -50,9 +50,8 @@ def mmlu_display_question_answer(question, cot, request: gr.Request):
 
     return q["agent_response"]["llama"][0], q["agent_response"]["wizardlm"][0], q["agent_response"]["orca"][0], q["summarization"][0], q["agent_response"]["llama"][1], q["agent_response"]["wizardlm"][1], q["agent_response"]["orca"][1], q["summarization"][1], q["agent_response"]["llama"][2], q["agent_response"]["wizardlm"][2], q["agent_response"]["orca"][2]
     
-warmup_test = ["llama2", "wizardlm", "orca"]
-def warmup(model_list=warmup_test, model_inference_endpoints=inference_endpoint):
-    for model in model_list:
+def warmup(list_model, model_inference_endpoints=inference_endpoint):
+    for model in list_model:
         API_URL = model_inference_endpoints[model]["API_URL"]
         headers = model_inference_endpoints[model]["headers"]
         headers["Authorization"] += HF_TOKEN
@@ -66,6 +65,7 @@ def warmup(model_list=warmup_test, model_inference_endpoints=inference_endpoint)
         
     time.sleep(1)
     return {
+        model_list: gr.update(visible=False)
         options: gr.update(visible=True),
         inputbox: gr.update(visible=True),
         submit: gr.update(visible=True),
@@ -157,8 +157,8 @@ The Math, GSM8K, and MMLU Tabs show the results of the experiment(Llama2, Wizard
 
 Here's how to use LLM Agora!
 
-1. Before starting, click the 'Warm-up LLM Agora 🔥' button and wait until 'LLM Agora Ready!!' appears. (Suggest to go grab a coffee☕ since it takes 5 minutes!)
-2. Choose just 3 models! Neither more nor less!
+1. Before starting, choose just 3 models and click the 'Warm-up LLM Agora 🔥' button and wait until '🤗🔥 Welcome to LLM Agora 🔥🤗' appears. (Suggest to go grab a coffee☕ since it takes 5 minutes!)
+2. Once the interaction space is available, proceed with the following process.
 3. Check the CoT box if you want to utilize the Chain-of-Thought while inferencing.
 4. Please fill in your OpenAI API KEY, it will be used to use ChatGPT to summarize the responses.
 5. Type your question in the Question box and click the 'Submit' button! If you do so, LLM Agora will show you improved answers! 🤗 (It will take roughly a minute! Please wait for an answer!)
@@ -218,11 +218,11 @@ with gr.Blocks() as demo:
     gr.Markdown(INTRODUCTION_TEXT)
     with gr.Column():
         with gr.Tab("Inference"):
+            model_list = gr.CheckboxGroup(["Llama2", "Llama2-Chat", "Vicuna", "Falcon", "Falcon-Instruct", "WizardLM", "Orca"], label="Model Selection", info="Choose 3 LMs to participate in LLM Agora.", type="value", visible=True)
             warmup_button = gr.Button("Warm-up LLM Agora 🔥", visible=True)
             welcome_message = gr.HTML(WELCOME_TEXT, visible=False)
             with gr.Row(visible=False) as options:
                 with gr.Column():
-                    model_list = gr.CheckboxGroup(["Llama2", "Llama2-Chat", "Vicuna", "Falcon", "Falcon-Instruct", "WizardLM", "Orca"], label="Model Selection", info="Choose 3 LMs to participate in LLM Agora.", type="value")
                     cot = gr.Checkbox(label="CoT", info="Do you want to use CoT for inference?")
                 with gr.Column() as inputbox:
                     API_KEY = gr.Textbox(label="OpenAI API Key", value="", info="Please fill in your OpenAI API token.", placeholder="sk..", type="password")
@@ -357,7 +357,5 @@ with gr.Blocks() as demo:
         with gr.Accordion("※ Specific information about LLM Agora", open=False):
             gr.Markdown(SPECIFIC_INFORMATION)
 
-    warmup_button.click(warmup, [], [options, inputbox, submit, warmup_button, welcome_message])
+    warmup_button.click(warmup, [model_list], [model_list, options, inputbox, submit, warmup_button, welcome_message])
     submit.click(inference, [model_list, question, API_KEY, cot], [output_msg, output_col, model1_output1, model2_output1, model3_output1, summarization_text1, model1_output2, model2_output2, model3_output2, summarization_text2, model1_output3, model2_output3, model3_output3])
-
-demo.launch()