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import gradio as gr
import whisper
import os
from groq import Groq
# 🔐 Get Groq API key securely from Hugging Face Secrets
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
groq_client = Groq(api_key=GROQ_API_KEY)
MODEL_NAME = "llama3-8b-8192"
# 🎙 Load Whisper
transcriber = whisper.load_model("base")
def transcribe_and_summarize(audio):
# Step 1: Transcribe + Detect Language
result = transcriber.transcribe(audio)
transcript = result["text"]
detected_lang = result["language"]
# Step 2: Summarize in the same language
if detected_lang == "en":
system_prompt = "You are an expert English summarizer."
user_prompt = f"Please summarize the following English text:\n\n{transcript}"
elif detected_lang == "ur":
system_prompt = "آپ ایک ماہر خلاصہ نگار ہیں جو اردو میں خلاصہ فراہم کرتے ہیں۔"
user_prompt = f"براہ کرم مندرجہ ذیل اردو متن کا خلاصہ فراہم کریں:\n\n{transcript}"
else:
system_prompt = "You are a helpful summarizer."
user_prompt = f"Summarize this text:\n\n{transcript}"
response = groq_client.chat.completions.create(
model=MODEL_NAME,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
]
)
summary = response.choices[0].message.content.strip()
lang_label = "English" if detected_lang == "en" else "Urdu" if detected_lang == "ur" else detected_lang.upper()
return f"[{lang_label}] {transcript}", f"[{lang_label}] {summary}"
demo = gr.Interface(
fn=transcribe_and_summarize,
inputs=gr.Audio(type="filepath", label="🎧 Upload Audio (English or Urdu)"),
outputs=[
gr.Textbox(label="📝 Transcript"),
gr.Textbox(label="🧠 Summary")
],
title="🗣️ Multilingual Audio Summarizer",
description="Upload English or Urdu audio. The app transcribes and summarizes in the same language using Whisper + Groq."
)
demo.launch()
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