| import gradio as gr |
| import plotly.express as px |
| import pandas as pd |
| from transformers import pipeline |
|
|
| |
| classifier = pipeline(task="text-classification", model="AR04/Senti", top_k=None) |
|
|
| id2label = { |
| 0: "admiration", 1: "amusement", 2: "anger", 3: "annoyance", 4: "approval", |
| 5: "caring", 6: "confusion", 7: "curiosity", 8: "desire", 9: "disappointment", |
| 10: "disapproval", 11: "disgust", 12: "embarrassment", 13: "excitement", |
| 14: "fear", 15: "gratitude", 16: "grief", 17: "joy", 18: "love", 19: "nervousness", |
| 20: "optimism", 21: "pride", 22: "realization", 23: "relief", 24: "remorse", |
| 25: "sadness", 26: "surprise", 27: "neutral" |
| } |
|
|
| def classify_and_visualize(text): |
| outputs = classifier([text])[0] |
| |
| df = pd.DataFrame(outputs) |
|
|
| |
| fig = px.line_polar( |
| df, |
| r="score", |
| theta="label", |
| line_close=True, |
| title="Emotion Radar", |
| ) |
| fig.update_traces(fill="toself", line=dict(color="blue")) |
|
|
| return df.to_dict("records"), fig |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("## 🎭 Emotion Radar Chat App") |
| with gr.Row(): |
| with gr.Column(): |
| text_input = gr.Textbox(placeholder="Type a message...", lines=2) |
| submit_btn = gr.Button("Analyze") |
| with gr.Column(): |
| result_json = gr.JSON() |
| result_plot = gr.Plot() |
|
|
| submit_btn.click(fn=classify_and_visualize, inputs=text_input, outputs=[result_json, result_plot]) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
