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import gradio as gr
import numpy as np
import tempfile
import os
from pathlib import Path
# Mock model for testing when real model can't load
USE_MOCK_MODEL = True
def initialize_model():
"""Initialize model - using mock for testing"""
global USE_MOCK_MODEL
if USE_MOCK_MODEL:
print("🧪 Using mock model for testing (real model has PyTorch compatibility issues)")
return "mock_model", None
return None, None
def transcribe_audio(audio_file):
"""
Transcribe audio using mock model for testing.
"""
if audio_file is None:
return "Please upload an audio file."
try:
# Initialize model if needed
model, processor = initialize_model()
if model is None:
return "❌ Error: Could not load the model. Please try again later."
filename = Path(audio_file).name
print(f"🎵 Processing audio file: {filename}")
# Mock transcription based on sample files
if "sample_1" in filename:
return "Muraho, witwa gute?"
elif "sample_2" in filename:
return "Ndashaka kwiga Ikinyarwanda."
elif "sample_3" in filename:
return "Urakoze cyane kubafasha."
elif "sample_4" in filename:
return "Tugiye gutangiza ikiganiro mu Kinyarwanda."
else:
return f"Mock transcription for {filename}: [This would be the actual Kinyarwanda transcription]"
except Exception as e:
print(f"❌ Transcription error: {e}")
return f"❌ Error during transcription: {str(e)}"
def transcribe_microphone(audio_data):
"""
Transcribe audio from microphone input.
"""
if audio_data is None:
return "Please record some audio first."
try:
sample_rate, audio_array = audio_data
duration = len(audio_array) / sample_rate
print(f"🎙️ Processing microphone input: {duration:.1f} seconds at {sample_rate}Hz")
return f"Mock transcription for {duration:.1f}s audio: [This would be the actual Kinyarwanda transcription]"
except Exception as e:
print(f"❌ Microphone processing error: {e}")
return f"❌ Error processing microphone input: {str(e)}"
# Create a simple Gradio interface
def create_interface():
"""Create a clean, simple Gradio interface."""
with gr.Blocks(title="Wakanda Whisper - Kinyarwanda ASR") as interface:
gr.Markdown("# 🎤 Wakanda Whisper")
gr.Markdown("### Kinyarwanda Automatic Speech Recognition")
gr.Markdown("Upload an audio file or record your voice to get Kinyarwanda transcription")
with gr.Tabs():
# File Upload Tab
with gr.TabItem("📁 Upload Audio File"):
with gr.Row():
with gr.Column():
audio_input = gr.Audio(
label="Choose Audio File",
type="filepath"
)
# Sample audio files
gr.Markdown("**Try these sample Kinyarwanda audio files:**")
with gr.Row():
sample_1 = gr.Button("Sample 1", size="sm")
sample_2 = gr.Button("Sample 2", size="sm")
sample_3 = gr.Button("Sample 3", size="sm")
sample_4 = gr.Button("Sample 4", size="sm")
upload_btn = gr.Button("🎯 Transcribe Audio", variant="primary")
with gr.Column():
upload_output = gr.Textbox(
label="Transcription Result",
placeholder="Your Kinyarwanda transcription will appear here...",
lines=6,
show_copy_button=True
)
# Microphone Tab
with gr.TabItem("🎙️ Record Audio"):
with gr.Row():
with gr.Column():
mic_input = gr.Audio(
label="Record Your Voice",
type="numpy"
)
mic_btn = gr.Button("🎯 Transcribe Recording", variant="primary")
with gr.Column():
mic_output = gr.Textbox(
label="Transcription Result",
placeholder="Your Kinyarwanda transcription will appear here...",
lines=6,
show_copy_button=True
)
# Set up event handlers
upload_btn.click(
fn=transcribe_audio,
inputs=audio_input,
outputs=upload_output,
show_progress=True
)
# Sample audio button handlers
sample_1.click(
fn=lambda: "sample_1.wav",
outputs=audio_input
)
sample_2.click(
fn=lambda: "sample_2.wav",
outputs=audio_input
)
sample_3.click(
fn=lambda: "sample_3.wav",
outputs=audio_input
)
sample_4.click(
fn=lambda: "sample_4.wav",
outputs=audio_input
)
mic_btn.click(
fn=transcribe_microphone,
inputs=mic_input,
outputs=mic_output,
show_progress=True
)
gr.Markdown("---")
gr.Markdown("**Powered by WakandaAI** | Model: [wakanda-whisper-small-rw-v1](https://huggingface.co/WakandaAI/wakanda-whisper-small-rw-v1)")
return interface
# Launch the app
if __name__ == "__main__":
print("🚀 Starting Wakanda Whisper ASR (Mock Mode for Testing)...")
# Create and launch the interface
demo = create_interface()
# Launch configuration - let Gradio find an available port
demo.launch(
server_name="127.0.0.1",
share=False,
show_error=True
)
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