add app.py

app.py

@@ -0,0 +1,63 @@
+import gradio as gr
+import pandas as pd
+
+with gr.Blocks() as demo:
+    dataset_df = {}
+    state = gr.State(value=0)
+    with gr.Row():
+        gr.Markdown("# Distributed Evaluation Parallel 😎")
+    with gr.Row():
+        file = gr.File(label="Upload a file")
+        prev = gr.Button(value="Previous")
+        next = gr.Button(value="Next")
+        download = gr.File(label="Download a file")
+    with gr.Row():
+        with gr.Column():
+            question = gr.Textbox(label="Question")
+        with gr.Column():
+            ground_truth = gr.Textbox(label="GT")
+        with gr.Column():
+            prediction = gr.Textbox(label="Prediction")
+            score = gr.Radio(choices=["Incorrect", "Correct"], label="Score")
+    with gr.Row():
+        todos = gr.DataFrame()
+        done = gr.DataFrame()
+    
+
+    def csv2df(file):
+        df = pd.read_csv(file.name)
+        df['score'] = None
+        df_dict = df.to_dict('records')
+        dataset_df.update(dict(df=df, df_dict=df_dict))
+        return update()
+
+    def prev_func(score):
+        df_dict = dataset_df['df_dict']
+        state.value = max(state.value - 1, 0)
+        score = df_dict[state.value]['score']
+        gr.Info(f"총 {len(dataset_df['df'])}개 중에 {state.value + 1}번째 데이터입니다.")
+        return [*update(), score]
+    
+    def next_func(score):
+        df_dict = dataset_df['df_dict']
+        df_dict[state.value]['score'] = score
+        state.value = min(state.value + 1, len(dataset_df['df']) - 1)
+        score = df_dict[state.value]['score']
+        gr.Info(f"총 {len(dataset_df['df'])}개 중에 {state.value + 1}번째 데이터입니다.")
+        return [*update(), score]
+
+    def update():
+        df_dict = dataset_df['df_dict']
+        q = df_dict[state.value]['question']
+        g = df_dict[state.value]['answer']
+        p = df_dict[state.value]['prediction']
+        df = pd.DataFrame(df_dict)
+        todos = df[df.score.isna()]
+        done = df[df.score.isna() == False]
+        return q, g, p, todos, done, "data_backup.csv"
+    file.upload(csv2df, file, [question, ground_truth, prediction, todos, done, download])
+    prev.click(prev_func, [score], [question, ground_truth, prediction, todos, done, download, score])
+    next.click(next_func, [score], [question, ground_truth, prediction, todos, done, download, score])
+
+demo.queue()
+demo.launch()