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Running
on
Zero
File size: 4,896 Bytes
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import gradio as gr
model = None
tokenizer = None
# device = 0 if torch.cuda.is_available() else -1
LANGUAGES = {
"Hindi": "hin_Deva",
"Bengali": "ben_Beng",
"Telugu": "tel_Telu",
"Marathi": "mar_Deva",
"Tamil": "tam_Taml",
"Urdu": "urd_Arab",
"Gujarati": "guj_Gujr",
"Kannada": "kan_Knda",
"Odia": "ori_Orya",
"Malayalam": "mal_Mlym",
"Punjabi": "pan_Guru",
"Assamese": "asm_Beng",
"Maithili": "mai_Mith",
"Santali": "sat_Olck",
"Kashmiri": "kas_Arab",
"Nepali": "nep_Deva",
"Sindhi": "snd_Arab",
"Konkani": "kok_Deva",
"Dogri": "dgo_Deva",
"Manipuri": "mni_Beng",
"Bodo": "brx_Deva"
}
def translate(src_lang, text, tgt_lang):
return "Translation output will appear here..."
def store_feedback(rating, feedback_text):
if not rating:
gr.Warning("Please select a rating before submitting feedback.", duration=5)
return None
if not feedback_text or feedback_text.strip() == "":
gr.Warning("Please provide some feedback before submitting.", duration=5)
return None
gr.Info("Feedback submitted successfully!")
return "Thank you for your feedback!"
css = """
#col-container {max-width: 80%; margin-left: auto; margin-right: auto;}
#header {text-align: center;}
.message { font-size: 1.2em; }
#feedback-section { margin-top: 30px; border-top: 1px solid #ddd; padding-top: 20px; }
"""
with gr.Blocks(theme=gr.themes.Default(), css=css) as demo:
gr.Markdown("# IndicTrans3 Demo 🚀", elem_id="header")
gr.Markdown("Translate text between multiple Indic languages using the latest IndicTrans3 model from AI4Bharat. This model is trained on the --- dataset and supports translation to 22 Indic languages. Setting a state-of-the-art benchmark on multiple translation tasks, IndicTrans3 is a powerful model that can handle complex translation tasks with ease.", elem_id="description")
with gr.Column(elem_id="col-container"):
with gr.Row():
with gr.Column():
src_lang = gr.Dropdown(
["English"],
value="English",
label="Translate From",
elem_id="translate-from"
)
text_input = gr.Textbox(
placeholder="Enter text to translate...",
label="",
lines=10,
max_lines=100,
elem_id="input-text"
)
with gr.Column():
tgt_lang = gr.Dropdown(
list(LANGUAGES.keys()),
value="Hindi",
label="Translate To",
elem_id="translate-to"
)
text_output = gr.Textbox(
label="",
lines=10,
max_lines=100,
elem_id="output-text"
)
btn_submit = gr.Button("Translate")
btn_submit.click(fn=translate, inputs=[src_lang, text_input, tgt_lang], outputs=text_output)
gr.Examples(
examples=[
["English", "Hello, how are you today? I hope you're doing well.", "Telugu"],
["English", "Hello, how are you today? I hope you're doing well.", "Punjabi"],
["English", "Hello, how are you today? I hope you're doing well.", "Hindi"],
["English", "Hello, how are you today? I hope you're doing well.", "Marathi"],
["English", "Hello, how are you today? I hope you're doing well.", "Malayalam"]
],
inputs=[src_lang, text_input, tgt_lang],
outputs=text_output,
fn=translate,
cache_examples=True,
examples_per_page=5
)
with gr.Column(elem_id="feedback-section"):
gr.Markdown("## Rate Translation & Provide Feedback 📝")
gr.Markdown("Help us improve the translation quality by providing your feedback and rating.")
with gr.Row():
rating = gr.Radio(
["1", "2", "3", "4", "5"],
label="Translation Rating (1-5)"
)
feedback_text = gr.Textbox(
placeholder="Share your feedback about the translation...",
label="Feedback",
lines=3
)
feedback_submit = gr.Button("Submit Feedback")
feedback_result = gr.Textbox(label="", visible=False)
feedback_submit.click(
fn=store_feedback,
inputs=[rating, feedback_text],
outputs=feedback_result
)
demo.launch()
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