Upload app.py

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+
+# Global variable to store the DataFrame
+df = None
+# Global variable to keep track of the current row index
+current_row = 0
+
+def load_csv(file):
+    global df
+    global current_row
+    # import the csv and set the data types to be int, string, string, string, string, string, string
+    df = pd.read_csv(file.name, dtype={'id':int, 'hs': str, 'cs': str, 'topic': str, 'tone': str, 'isCSContextuallyRelevant': str, 'isToneMatch': str})
+    current_row = 0
+    row_dict = df.iloc[current_row].to_dict()
+    return row_dict['id'], row_dict['hs'], row_dict['cs'], row_dict['topic'], row_dict['tone'], row_dict['isCSContextuallyRelevant'], row_dict['isToneMatch']
+
+def annotate_row(isCSContextuallyRelevant, isToneMatch):
+    global df
+    global current_row
+
+    df.at[current_row, 'isCSContextuallyRelevant'] = isCSContextuallyRelevant
+    df.at[current_row, 'isToneMatch'] = isToneMatch
+
+    if current_row < len(df) - 1:
+        current_row += 1
+    else:
+        current_row = 0
+    df.to_csv('annotated_data.csv', index=False)
+    
+    row_dict = df.iloc[current_row].to_dict()
+    return row_dict['id'], row_dict['hs'], row_dict['cs'], row_dict['topic'], row_dict['tone'], row_dict['isCSContextuallyRelevant'], row_dict['isToneMatch'], 'annotated_data.csv'
+
+def navigate(direction):
+    global current_row
+    if direction == "Previous":
+        current_row = max(0, current_row - 1)
+    elif direction == "Next":
+        current_row = min(len(df) - 1, current_row + 1)
+    elif direction == "First Unlabeled":
+        unlabeled_row = df[df['isCSContextuallyRelevant'].isna()].index.min()
+        if not np.isnan(unlabeled_row):
+            current_row = int(unlabeled_row)
+
+    row_dict = df.iloc[current_row].to_dict()
+    return row_dict['id'], row_dict['hs'], row_dict['cs'], row_dict['topic'], row_dict['tone'], row_dict['isCSContextuallyRelevant'], row_dict['isToneMatch']
+
+with gr.Blocks(theme=gr.themes.Soft()) as annotator:
+    gr.Markdown("## Data Annotation")
+    
+    with gr.Row():
+        gr.Markdown("### Upload CSV")
+        file_upload = gr.File()
+        btn_load = gr.Button("Load CSV")
+
+    with gr.Row():
+        gr.Markdown("### Current Row")
+        with gr.Row():
+            idx = gr.Number(label='Index')
+            hs = gr.Textbox(label='HS')
+            cs = gr.Textbox(label='CS')
+
+        with gr.Row():
+            topic = gr.Textbox(label='Topic')
+            tone = gr.Textbox(label='Tone')
+        
+        with gr.Row():
+            isCSContextuallyRelevant = gr.Radio(["1", "0"], label="Contextually Relevant?")
+            isToneMatch = gr.Radio(["1", "0"], label="Tone Match?")
+            btn_annotate = gr.Button("Annotate")
+
+        with gr.Row():
+            btn_previous = gr.Button("Previous")
+            btn_next = gr.Button("Next")
+            btn_first_unlabeled = gr.Button("First Unlabeled")
+
+    with gr.Row():
+        gr.Markdown("### Annotated Data File Download")
+        file_download = gr.File()
+
+    btn_load.click(load_csv, inputs=[file_upload], outputs=[idx, hs, cs, topic, tone, isCSContextuallyRelevant, isToneMatch], scroll_to_output=True)
+    btn_annotate.click(annotate_row, inputs=[isCSContextuallyRelevant, isToneMatch], outputs=[idx, hs, cs, topic, tone, isCSContextuallyRelevant, isToneMatch, file_download])
+    btn_previous.click(navigate, inputs=gr.Textbox("Previous", visible=False), outputs=[idx, hs, cs, topic, tone, isCSContextuallyRelevant, isToneMatch])
+    btn_next.click(navigate, inputs=gr.Textbox("Next", visible=False), outputs=[idx, hs, cs, topic, tone, isCSContextuallyRelevant, isToneMatch])
+    btn_first_unlabeled.click(navigate, inputs=gr.Textbox("First Unlabeled", visible=False), outputs=[idx, hs, cs, topic, tone, isCSContextuallyRelevant, isToneMatch])
+
+annotator.launch()