| import gradio as gr | |
| import spacy | |
| from spacy import displacy | |
| import pandas as pd | |
| df = pd.read_json("cliff_gradio.jsonl", orient="index") | |
| colors = {"ext": "#aa9cfc", "int": "#ff6961", "wor": "#7aecec"} | |
| options = {"colors": colors} | |
| nlp = spacy.blank("en") | |
| def viz(topic_id): | |
| row = df.loc[topic_id] | |
| summary = row["summary"] | |
| labels = row["labels"] | |
| score = row["score"] | |
| ex = [{"text": summary, | |
| "ents": [{"start": token.idx, "end": token.idx + token.__len__() + 1, "label": label[:3]} for token, label in zip(nlp(summary), labels) if label != "correct"], | |
| "title": None}] | |
| return row["article"], displacy.render(ex, style="ent", manual=True, options=options), score | |
| demo = gr.Interface(fn=viz, | |
| inputs=[gr.Dropdown(df.index.tolist(), label="Select Topic Id")], | |
| outputs=[gr.Text(label="Source article"), | |
| gr.HTML(label="summary"), | |
| gr.Number(label="score")]) | |
| demo.launch() | |