File size: 6,399 Bytes
9c6961c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 | import gradio as gr
import json
import os
import random
from datetime import datetime
# --- Configuration ---
DATA_PATH = '/home/mshahidul/readctrl/data/extracting_subclaim/extracted_subclaims_syn_data_with_gs_summary_en.json'
SAVE_PATH = 'annotated_subclaims_triplet.json'
with open(DATA_PATH, 'r') as f:
data = json.load(f)
# --- Logic Functions ---
def load_example(index):
if index >= len(data):
return [
gr.update(value="### 🎉 All Done!"),
gr.update(value="You have completed all records in this dataset."),
[], "0%", "0%", "0%",
gr.update(choices=[], value=[]),
gr.update(choices=[], value=[]),
gr.update(choices=[], value=[])
]
record = data[index]
# Randomly select evaluation focus
source_type = random.choice(["Full Original Text", "Gold Summary"])
if source_type == "Full Original Text":
text_content = record['fulltext']
subclaims = record['fulltext_subclaims']
else:
text_content = record['summary']
subclaims = record['summary_subclaims']
source_info = f"### Instance: {index + 1}/{len(data)} | Source: **{source_type}**"
return [
source_info,
text_content,
subclaims,
"0%", "0%", "0%",
gr.update(choices=subclaims, value=[]),
gr.update(choices=subclaims, value=[]),
gr.update(choices=subclaims, value=[])
]
def calc_pct(selected, total_list):
if not total_list or len(total_list) == 0:
return "0%"
return f"{(len(selected)/len(total_list))*100:.1f}%"
def save_and_next(username, index, source_info, low_sel, int_sel, prof_sel, subclaims):
# Validation
if not username or username.strip() == "":
gr.Warning("Please enter your name/username before submitting!")
return [index] + load_example(index)
stype = "Full Original Text" if "Full Original Text" in source_info else "Gold Summary"
# Capture current date and time
now = datetime.now()
timestamp = now.strftime("%Y-%m-%d %H:%M:%S")
result = {
"annotator": username,
"timestamp": timestamp,
"index": index,
"source_type": stype,
"annotations": {
"low": {"subclaims": low_sel, "pct": len(low_sel)/len(subclaims) if subclaims else 0},
"intermediate": {"subclaims": int_sel, "pct": len(int_sel)/len(subclaims) if subclaims else 0},
"proficient": {"subclaims": prof_sel, "pct": len(prof_sel)/len(subclaims) if subclaims else 0}
}
}
# Saving logic
existing = []
if os.path.exists(SAVE_PATH):
try:
with open(SAVE_PATH, 'r') as f: existing = json.load(f)
except: existing = []
existing.append(result)
with open(SAVE_PATH, 'w') as f:
json.dump(existing, f, indent=4)
gr.Info(f"Success! Saved at {timestamp}")
next_idx = index + 1
return [next_idx] + load_example(next_idx)
# --- UI Definition ---
with gr.Blocks(theme=gr.themes.Soft(), title="Health Literacy Annotator") as demo:
index_state = gr.State(0)
subclaim_list_state = gr.State([])
gr.Markdown("# 🏥 Health Literacy Subclaim Annotation\n## Texts labeled as low health literacy include less information than those labeled as intermediate health literacy, and intermediate health literacy texts include less information than proficient health literacy texts.\nSome key information has already been pre-selected to ensure that each label contains a minimum required amount of information. If you believe additional information should be included for a given label, please select the corresponding checkboxes.")
with gr.Row():
# Sidebar
with gr.Column(scale=1, variant="panel"):
user_input = gr.Textbox(label="Annotator Name", placeholder="Enter your name...", interactive=True)
gr.HTML("<hr>")
gr.Markdown("### 📖 Level Guidelines")
with gr.Accordion("1. Low Literacy", open=False):
gr.Markdown("- Simple terms, 'living room' language.\n- High paraphrasing.")
with gr.Accordion("2. Intermediate Literacy", open=False):
gr.Markdown("- News-reading level.\n- Balanced context.")
with gr.Accordion("3. Proficient Literacy", open=False):
gr.Markdown("- Academic/Clinical level.\n- Full technical details.")
gr.HTML("<hr>")
source_display = gr.Markdown("### Initializing...")
text_viewer = gr.Textbox(label="Reference Text Content", interactive=False, lines=12)
# Main Area
with gr.Column(scale=2):
with gr.Row():
with gr.Column():
gr.Markdown("### 🟢 Low")
low_pct = gr.Label(value="0%", label="Coverage")
low_check = gr.CheckboxGroup(label="Subclaims", choices=[])
with gr.Column():
gr.Markdown("### 🟡 Intermediate")
int_pct = gr.Label(value="0%", label="Coverage")
int_check = gr.CheckboxGroup(label="Subclaims", choices=[])
with gr.Column():
gr.Markdown("### 🔴 Proficient")
prof_pct = gr.Label(value="0%", label="Coverage")
prof_check = gr.CheckboxGroup(label="Subclaims", choices=[])
submit_btn = gr.Button("Submit & Next Record", variant="primary", size="lg")
# --- Events ---
demo.load(
load_example,
[index_state],
[source_display, text_viewer, subclaim_list_state, low_pct, int_pct, prof_pct, low_check, int_check, prof_check]
)
low_check.change(calc_pct, [low_check, subclaim_list_state], low_pct)
int_check.change(calc_pct, [int_check, subclaim_list_state], int_pct)
prof_check.change(calc_pct, [prof_check, subclaim_list_state], prof_pct)
submit_btn.click(
save_and_next,
[user_input, index_state, source_display, low_check, int_check, prof_check, subclaim_list_state],
[index_state, source_display, text_viewer, subclaim_list_state, low_pct, int_pct, prof_pct, low_check, int_check, prof_check]
)
if __name__ == "__main__":
demo.launch(share=True) |