| import torch |
| import gradio as gr |
| from transformers import pipeline |
| import pycountry |
|
|
| |
| language_detector = pipeline( |
| "text-classification", |
| model="papluca/xlm-roberta-base-language-detection", |
| torch_dtype=torch.bfloat16 |
| ) |
|
|
| def detect_language(text: str) -> str: |
| """ |
| Detects the language of the given text and returns |
| both the full language name and its ISO code with confidence. |
| """ |
| result = language_detector(text)[0] |
| code = result["label"] |
| score = result["score"] |
|
|
| |
| try: |
| lang = pycountry.languages.get(alpha_2=code).name |
| except: |
| lang = code.upper() |
|
|
| return f"{lang} ({code}) — {score:.2f}" |
|
|
| |
| with gr.Blocks(theme=gr.themes.Default()) as demo: |
| gr.Markdown( |
| """ |
| # 🌐 Text Language Detector |
| Type or paste text below to detect its language (name + code + confidence). |
| """ |
| ) |
|
|
| with gr.Row(): |
| text_input = gr.Textbox( |
| label="📝 Input Text", |
| placeholder="Type or paste text here...", |
| lines=4, |
| show_copy_button=True |
| ) |
| lang_output = gr.Textbox( |
| label="✅ Detected Language", |
| placeholder="Full language name, ISO code, and confidence will appear here", |
| lines=1, |
| interactive=False |
| ) |
|
|
| detect_btn = gr.Button("🔍 Detect Language") |
| detect_btn.click(fn=detect_language, inputs=text_input, outputs=lang_output) |
|
|
| gr.Markdown( |
| """ |
| --- |
| Built with 🤗 Transformers (`papluca/xlm-roberta-base-language-detection`), |
| `pycountry` for language names, and 🚀 Gradio |
| """ |
| ) |
|
|
| demo.launch() |
