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c7a6fe6 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 | import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
import json
import torch
import pickle
import gradio as gr
import textstat
from sentence_transformers import SentenceTransformer, util
# --- Configuration & Paths ---
LANG_CODE = "en"
CHUNKS_PATH = f"/home/mshahidul/readctrl/data/vector_db/db_model/wiki_{LANG_CODE}_chunks.pkl"
EMBS_PATH = f"/home/mshahidul/readctrl/data/vector_db/db_model/wiki_{LANG_CODE}_embs.pt"
TARGET_DOCS_PATH = f"/home/mshahidul/readctrl/data/synthetic_dataset_diff_labels/syn_data_diff_labels_{LANG_CODE}_v1.json"
SAVE_PATH = f"/home/mshahidul/readctrl/data/data_annotator_data/manual_selections_{LANG_CODE}.json"
# --- 1. Load Resources ---
print("Loading Model and Tensors...")
model = SentenceTransformer('all-MiniLM-L6-v2')
with open(CHUNKS_PATH, "rb") as f:
wiki_chunks = pickle.load(f)
device = "cuda" if torch.cuda.is_available() else "cpu"
wiki_embs = torch.load(EMBS_PATH).to(device)
with open(TARGET_DOCS_PATH, "r") as f:
raw_targets = json.load(f)
target_list = []
for item in raw_targets:
for label, text in item['diff_label_texts'].items():
target_list.append({
"index": item['index'],
"label": label,
"text": text
})
# --- 2. Logic Functions ---
def get_candidates(target_text, top_k=20):
query_emb = model.encode(target_text, convert_to_tensor=True).to(device)
hits = util.semantic_search(query_emb, wiki_embs, top_k=top_k)[0]
candidates = []
for hit in hits:
candidates.append(wiki_chunks[hit['corpus_id']])
return candidates
def calculate_stats(text):
if not text: return "N/A"
wc = len(text.split())
fk = textstat.flesch_kincaid_grade(text)
return f"📏 Words: {wc} | 🎓 FKGL: {fk}"
def save_selection(target_idx, label, original_text, selected_wiki):
entry = {
"index": target_idx,
"label": label,
"original_text": original_text,
"selected_wiki_anchor": selected_wiki,
"wiki_fkgl": textstat.flesch_kincaid_grade(selected_wiki),
"doc_fkgl": textstat.flesch_kincaid_grade(original_text)
}
existing_data = []
if os.path.exists(SAVE_PATH):
try:
with open(SAVE_PATH, "r") as f:
existing_data = json.load(f)
except:
existing_data = []
existing_data = [d for d in existing_data if not (d['index'] == target_idx and d['label'] == label)]
existing_data.append(entry)
with open(SAVE_PATH, "w") as f:
json.dump(existing_data, f, indent=2)
gr.Info(f"Successfully saved ID {target_idx} ({label})")
return f"✅ Saved: ID {target_idx} ({label})"
# --- 3. Gradio UI ---
with gr.Blocks(theme=gr.themes.Soft(), title="Wiki Anchor Selector") as demo:
gr.Markdown(f"# 🔍 ReadCtrl: Anchor Selection (Numeric View)")
current_idx = gr.State(0)
with gr.Row():
# Left Panel
with gr.Column(scale=1):
target_info = gr.Markdown("### Loading...")
# Changed from HighlightedText to Textbox for stability
label_display = gr.Textbox(label="Target Readability Level", interactive=False)
display_text = gr.Textbox(label="Medical Text", lines=12, interactive=False)
target_stats = gr.Markdown("Stats: ...")
# Right Panel
with gr.Column(scale=2):
wiki_dropdown = gr.Dropdown(
label="Select Candidate Number",
choices=[],
interactive=True
)
full_wiki_view = gr.Textbox(label="Wikipedia Chunk Preview", lines=12, interactive=False)
wiki_stats = gr.Markdown("Stats: ...")
status_msg = gr.Markdown("### *Status: Ready*")
with gr.Row():
prev_btn = gr.Button("⬅️ Previous")
save_btn = gr.Button("💾 Confirm & Save", variant="primary")
next_btn = gr.Button("Next / Skip ➡️")
# --- UI Logic ---
def load_item(idx):
if not (0 <= idx < len(target_list)):
return "End", "None", "", "", gr.update(choices=[], value=None), "", "", "Finished!"
doc = target_list[idx]
candidates = get_candidates(doc['text'], top_k=20)
info = f"### Document {idx + 1} of {len(target_list)} (ID: {doc['index']})"
t_stats = calculate_stats(doc['text'])
dropdown_choices = [(f"Candidate {i+1}", c) for i, c in enumerate(candidates)]
return (
info,
doc['label'].upper(), # Simple string for the Label Textbox
doc['text'],
t_stats,
gr.update(choices=dropdown_choices, value=candidates[0]),
candidates[0],
calculate_stats(candidates[0]),
""
)
def on_dropdown_change(selected_text):
if not selected_text: return "", ""
return selected_text, calculate_stats(selected_text)
def handle_next(idx):
new_idx = min(len(target_list) - 1, idx + 1)
return [new_idx] + list(load_item(new_idx))
def handle_prev(idx):
new_idx = max(0, idx - 1)
return [new_idx] + list(load_item(new_idx))
# --- Event Bindings ---
demo.load(load_item, inputs=[current_idx],
outputs=[target_info, label_display, display_text, target_stats, wiki_dropdown, full_wiki_view, wiki_stats, status_msg])
wiki_dropdown.change(on_dropdown_change, inputs=wiki_dropdown, outputs=[full_wiki_view, wiki_stats])
save_btn.click(lambda i, t, w: save_selection(target_list[i]['index'], target_list[i]['label'], t, w),
inputs=[current_idx, display_text, wiki_dropdown],
outputs=[status_msg])
next_btn.click(handle_next, inputs=[current_idx], outputs=[current_idx, target_info, label_display, display_text, target_stats, wiki_dropdown, full_wiki_view, wiki_stats, status_msg])
prev_btn.click(handle_prev, inputs=[current_idx], outputs=[current_idx, target_info, label_display, display_text, target_stats, wiki_dropdown, full_wiki_view, wiki_stats, status_msg])
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7861,share=True) |