| <html> | |
| <head> | |
| <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script> | |
| <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" /> | |
| <script type="module"> | |
| import { env, pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers'; | |
| env.allowLocalModels = false; | |
| let sentimentPipe = await pipeline('sentiment-analysis'); | |
| globalThis.sentimentPipe = sentimentPipe; | |
| </script> | |
| <style> | |
| body { | |
| color: black; | |
| background-color: white; | |
| } | |
| @media (prefers-color-scheme: dark) { | |
| body { | |
| color: white; | |
| background-color: #0b0f19; | |
| } | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <gradio-lite> | |
| import gradio as gr | |
| js_predict = """ | |
| async function(input){ | |
| let result = await sentimentPipe(input); | |
| return result | |
| }""" | |
| def greet(name): | |
| return "Hello " + name + "!" | |
| with gr.Blocks() as demo: | |
| gr.Markdown("""## Sentiment Analysis with Transformer.js""") | |
| name = gr.Textbox(label="Input Text") | |
| output = gr.JSON(label="Output Result") | |
| greet_btn = gr.Button("Greet") | |
| greet_btn.click(None, inputs=name, outputs=output, api_name="greet", _js=js_predict) | |
| gr.Examples([ | |
| "I don't feel well", | |
| "What a beautiful day" | |
| ], inputs=name, outputs=output) | |
| demo.launch(show_api=False) | |
| </gradio-lite> | |
| </body> | |
| </html> |