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import os
import gradio as gr
from groq import Groq
# Load API key securely
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
SYSTEM_PROMPT = """
You are a professional English to Urdu translator.
Rules:
- Translate accurately and naturally
- Use proper Urdu grammar
- Do not add explanations
- Output ONLY Urdu text
"""
def translate_to_urdu(english_text):
if not english_text.strip():
return ""
response = client.chat.completions.create(
model="llama-3.3-70b-versatile",
messages=[
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": english_text}
],
temperature=0.2,
max_tokens=500
)
return response.choices[0].message.content.strip()
# Demo click function
def demo_translate(text):
return text, translate_to_urdu(text)
# UI
with gr.Blocks(theme=gr.themes.Soft(), title="English → Urdu Translator") as demo:
gr.Markdown(
"""
# 🌍 English → Urdu Translator Chatbot
**Powered by Groq LLM**
"""
)
input_text = gr.Textbox(
label="English Text",
placeholder="Enter English sentence here...",
lines=4
)
output_text = gr.Textbox(
label="Urdu Translation",
lines=4
)
translate_btn = gr.Button("Translate 🇵🇰")
translate_btn.click(translate_to_urdu, input_text, output_text)
gr.Markdown("### 🔹 Try Demo Examples (Click & Translate)")
demo_sentences = [
"Education is the key to success.",
"Artificial intelligence is changing the world.",
"Please submit your assignment before Friday.",
"Healthcare systems need modern technology.",
"Pakistan is a beautiful country with rich culture.",
"I am learning machine learning and data science."
]
with gr.Row():
for sentence in demo_sentences[:3]:
gr.Button(sentence).click(
demo_translate,
outputs=[input_text, output_text],
inputs=[]
)
with gr.Row():
for sentence in demo_sentences[3:]:
gr.Button(sentence).click(
demo_translate,
outputs=[input_text, output_text],
inputs=[]
)
demo.launch()
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