import gradio as gr
import pandas as pd
file1 = 'basic.csv'
df1 = pd.read_csv(file1)
file2 ='contextual.csv'
df2 = pd.read_csv(file2)
file3 ='Overall.csv'
df3 = pd.read_csv(file3)
def display_table(table_choice):
if table_choice == "Option 1: 大语言模型推理能力综合排名":
return df3
elif table_choice == "Option 2: 基础逻辑能力排名":
return df1
elif table_choice == "Option 3: 情境推理能力排名":
return df2
with gr.Blocks() as demo:
gr.Markdown(
"""
# Evaluating the Reasoning Capabilities of Large Language Models in Chinese-language Contexts / 中文语境下的大语言模型推理能力评测
by Zhenhui(Jack) Jiang1, Yi Lu1, Yifan Wu1, Haozhe Xu2, Zhengyu Wu1, Jiaxin Li1 / 蒋镇辉1,鲁艺1,吴轶凡1,徐昊哲2,武正昱1,李佳欣1
1香港大学经管学院,2西安交通大学管理学院
""")
with gr.Tab("大语言模型推理能力评测"):
with gr.Column():
dropdown = gr.Dropdown(choices=["Option 1: 大语言模型推理能力综合排名",
"Option 2: 基础逻辑能力排名",
"Option 3: 情境推理能力排名"],
label="Select a Leaderboard",
value="Option 1: 大语言模型推理能力综合排名")
output = gr.DataFrame(value=df3, max_height =1800)
dropdown.change(fn=display_table, inputs=dropdown, outputs=output)
demo.launch()