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from transformers import pipeline
import torch
# ----------------------------------------
# Supported Languages
# ----------------------------------------
languages = [
"English",
"Hindi",
"Tamil",
"Telugu",
"Kannada",
"Malayalam",
"Bengali",
"Marathi",
"Gujarati",
"Punjabi",
"Urdu"
]
# ----------------------------------------
# Translation Function
# ----------------------------------------
def translate_text(hf_token, source_lang, target_lang, input_text):
if not hf_token.strip():
return "Please enter Hugging Face Access Token."
if not input_text.strip():
return "Please enter text."
try:
# Load IBM Granite model
pipe = pipeline(
"text-generation",
model="ibm-granite/granite-3.3-2b-base",
token=hf_token,
device_map="auto",
torch_dtype=torch.float16
)
# Translation Prompt
prompt = f"""
You are an expert multilingual translator.
Translate the below text from {source_lang} to {target_lang}.
Only provide translated text.
Text:
{input_text}
"""
# Generate Translation
result = pipe(
prompt,
max_new_tokens=200,
temperature=0.2
)
translated_text = result[0]["generated_text"]
# Remove original prompt if generated
translated_text = translated_text.replace(prompt, "").strip()
return translated_text
except Exception as e:
return f"Error: {str(e)}"
# ----------------------------------------
# Professional UI Styling
# ----------------------------------------
custom_css = """
body {
background: linear-gradient(to right, #0f2027, #203a43, #2c5364);
}
.gradio-container {
font-family: 'Segoe UI', sans-serif;
}
.main-title {
text-align: center;
font-size: 42px;
font-weight: bold;
color: white;
}
.sub-title {
text-align: center;
color: #dfe6e9;
font-size: 18px;
margin-bottom: 20px;
}
textarea {
border-radius: 12px !important;
}
footer {
visibility: hidden;
}
"""
# ----------------------------------------
# Gradio Interface
# ----------------------------------------
with gr.Blocks(
theme=gr.themes.Soft(),
css=custom_css
) as demo:
gr.Markdown(
"""
<div class="main-title">
π AI Multilingual Translator
</div>
<div class="sub-title">
IBM Granite + Hugging Face + Gradio
</div>
"""
)
with gr.Row():
with gr.Column(scale=1):
hf_token = gr.Textbox(
label="π Hugging Face Access Token",
placeholder="Paste your HF token here",
type="password"
)
source_lang = gr.Dropdown(
choices=languages,
value="English",
label="π Source Language"
)
target_lang = gr.Dropdown(
choices=languages,
value="Hindi",
label="π― Target Language"
)
with gr.Column(scale=2):
input_text = gr.Textbox(
label="π Enter Text",
lines=8,
placeholder="Type text to translate..."
)
output_text = gr.Textbox(
label="β
Translated Output",
lines=8
)
translate_btn = gr.Button(
"π Translate",
variant="primary"
)
translate_btn.click(
fn=translate_text,
inputs=[
hf_token,
source_lang,
target_lang,
input_text
],
outputs=output_text
)
# Launch App
demo.launch(share=True)
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