Update app.py

app.py

@@ -5,6 +5,8 @@ import os
 from model_inference import Inference
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
+question_selector_map = {}
+
 model_list = ["llama", "llama-chat", "vicuna", "falcon", "falcon-instruct", "orca", "wizardlm"]
 
 with open("src/inference_endpoint.json", "r") as f:
@@ -13,6 +15,16 @@ with open("src/inference_endpoint.json", "r") as f:
 for i in range(len(model_list)):
     inference_endpoint[model_list[i]]["headers"]["Authorization"] += HF_TOKEN
 
+def build_question_selector_map(questions):
+    question_selector_map = {}
+
+    # Build question selector map
+    for q in questions:
+        preview = f"{q['question_id']+1}: " + q["question"][:128] + "..."
+        question_selector_map[preview] = q
+
+    return question_selector_map
+
 def warmup(model_list=model_list, model_inference_endpoints=inference_endpoint):
     for i in range(len(model_list)):
         API_URL = model_inference_endpoints[model_list[i]["API_URL"]]
@@ -81,9 +93,9 @@ def load_questions(math, gsm):
     gsm_questions = []
     # mmlu_questions = []
     for i in range(100):
-        math_questions.append(f"{i+1}. " + math[i]["question"])
-        gsm_questions.append(f"{i+1}. " + gsm[i]["question"])
-        # mmlu_questions.append(f"{i+1}. " + mmlu[i]["question"])
+        math_questions.append(f"{i+1}: " + math[i]["question"][:128] + "...")
+        gsm_questions.append(f"{i+1}: " + gsm[i]["question"][:128] + "...")
+        # mmlu_questions.append(f"{i+1}: " + mmlu[i]["question"][:128] + "...")
 
     return math_questions, gsm_questions#, mmlu_questions
 
@@ -91,6 +103,9 @@ math_result, gsm_result = load_responses()
 
 math_questions, gsm_questions = load_questions(math_result, gsm_result)
 
+math_question_selector_map = build_question_selector_map(math_result)
+gsm_question_selector_map = build_question_selector_map(gsm_result)
+
 TITLE = """<h1 align="center">LLM Agora 🗣️🏦</h1>"""
 
 INTRODUCTION_TEXT = """
@@ -194,11 +209,11 @@ with gr.Blocks() as demo:
         
         with gr.Tab("Math"):
             math_cot = gr.Checkbox(label="CoT", info="If you want to see CoT result, please check the box.")
-            math_question_list = gr.Dropdown(math_questions, label="Math Question", every=0.1, type="index")
+            math_question_list = gr.Dropdown(math_questions, value=math_questions[0], label="Math Question", every=0.1)
 
             with gr.Column():
                 with gr.Row(elem_id="model1_response"):
-                    math_model1_output1 = gr.Textbox(label="Llama2🦙's 1️⃣st response", value=math_result[int(math_question_list)]["agent_response"]["llama"][0])   # value=math_result[math_question_list]["agent_response"]["llama"][0]
+                    math_model1_output1 = gr.Textbox(label="Llama2🦙's 1️⃣st response")   # value=math_result[math_question_list]["agent_response"]["llama"][0]
                     math_model2_output1 = gr.Textbox(label="WizardLM🧙‍♂️'s 1️⃣st response")
                     math_model3_output1 = gr.Textbox(label="Orca🐬's 1️⃣st response")
                 math_summarization_text1 = gr.Textbox(lebel="Summarization 1️⃣")