Create app.py

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import requests
+
+# Function to send audio to Groq API and get transcription
+def transcribe(audio_path):
+    # Read audio file in binary mode
+    with open(audio_path, "rb") as audio_file:
+        audio_data = audio_file.read()
+
+    # Groq API endpoint for audio transcription
+    groq_api_endpoint = "https://api.groq.com/openai/v1/audio/transcriptions"
+
+    # Replace 'YOUR_GROQ_API_KEY' with your actual Groq API key
+    headers = {
+        "Authorization": "Bearer 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",
+    }
+
+    # Prepare the files and data for the request
+    files = {
+        'file': ('audio.wav', audio_data, 'audio/wav'),
+    }
+    data = {
+        'model': 'whisper-large-v3-turbo',  # Specify the model to use
+        'response_format': 'json',          # Desired response format
+        'language': 'en',                   # Language of the audio
+    }
+
+    # Send audio to Groq API
+    response = requests.post(groq_api_endpoint, headers=headers, files=files, data=data)
+
+    # Parse response
+    if response.status_code == 200:
+        result = response.json()
+        return result.get("text", "No transcription available.")
+    else:
+        return f"Error: {response.status_code}, {response.text}"
+
+# Gradio interface
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(type="filepath"),  # Removed 'source' parameter for compatibility
+    outputs="text",
+    title="Voice to Text Converter App",
+    
+)
+
+iface.launch()