JamboGPT Bot commited on
Commit Β·
deb4070
0
Parent(s):
Initial commit: JamboGPT African Language AI
Browse files- .gitignore +67 -0
- README.md +137 -0
- app.py +245 -0
- requirements.txt +9 -0
.gitignore
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# Virtual environment
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venv/
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env/
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ENV/
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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.DS_Store
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# Gradio
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flagged/
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*.gradio_cached_examples
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# Models (cache)
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models/
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*.pt
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*.bin
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*.safetensors
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# Audio files
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*.wav
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*.mp3
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*.flac
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# Temporary files
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*.tmp
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*.temp
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/tmp/
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# Environment variables
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.env
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.env.local
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.env.*.local
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# Logs
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*.log
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logs/
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# OS
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.DS_Store
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Thumbs.db
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README.md
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# JamboGPT - African Language AI
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π **JamboGPT** is an open-source AI application for Text-to-Speech (TTS) in Kenyan and African languages. It brings the power of AI to underrepresented languages, making technology more accessible across the African continent.
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Inspired by **Yarn GPT** by Saheed Azeez, JamboGPT focuses on African languages with high-quality, natural-sounding speech synthesis.
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## Features
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- π€ **High-Quality TTS**: Generate natural-sounding speech from text
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- π **African Languages**: Support for Swahili, Kikuyu, English, and more
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- β‘ **Fast Inference**: Powered by Meta's MMS (Massively Multilingual Speech) models
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- π **Open Source**: Free and accessible to everyone
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- π― **Easy to Use**: Simple Gradio interface
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- π± **Web-Based**: Access from any browser
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## Supported Languages
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| Language | Code | Description |
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|----------|------|-------------|
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| Swahili | swh | East African language spoken in Kenya, Tanzania, Uganda |
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| Kikuyu | ki | Bantu language spoken in central Kenya |
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| English | eng | English language |
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## Installation
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### Requirements
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- Python 3.8+
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- CUDA 11.8+ (optional, for GPU acceleration)
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### Setup
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1. Clone the repository:
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```bash
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git clone https://huggingface.co/spaces/YOUR_USERNAME/jambogpt
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cd jambogpt
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```
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2. Create a virtual environment:
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```bash
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python3 -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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```
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3. Install dependencies:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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### Run Locally
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```bash
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python app.py
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```
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The app will be available at `http://localhost:7860`
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### Deploy to Hugging Face Spaces
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1. Create a new Space on Hugging Face
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2. Push your code to the Space repository
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3. Gradio will automatically detect `app.py` and deploy it
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## Architecture
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**JamboGPT** uses the following technology stack:
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- **Gradio**: Web interface framework
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- **Hugging Face Transformers**: Model loading and inference
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- **Meta MMS**: Multilingual speech synthesis models
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- **PyTorch**: Deep learning framework
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- **SciPy**: Audio processing
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## Model Information
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### Text-to-Speech Models
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- **facebook/mms-tts-swh**: Swahili TTS (Meta MMS)
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- **BrianMwangi/African-Kikuyu-TTS**: Kikuyu TTS (Fine-tuned MMS)
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- **facebook/mms-tts-eng**: English TTS (Meta MMS)
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All models are open-source and available on Hugging Face Hub.
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## Performance
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- **Inference Time**: ~2-5 seconds per 100 words (CPU), <1 second (GPU)
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- **Audio Quality**: 16kHz, 16-bit PCM WAV
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- **Max Text Length**: 1000 characters per request
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## Roadmap
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- [ ] Add more African languages (Luo, Luhya, Kamba, Amharic, Yoruba, Igbo, Hausa)
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- [ ] Implement voice cloning
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- [ ] Add speech-to-text (ASR)
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- [ ] Support for multiple speakers
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- [ ] Real-time streaming
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- [ ] Mobile app
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## Contributing
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Contributions are welcome! Please feel free to submit pull requests or open issues.
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## License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## Acknowledgments
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- **Saheed Azeez** for creating Yarn GPT, which inspired this project
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- **Meta AI** for the MMS (Massively Multilingual Speech) models
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- **Hugging Face** for the model hub and Spaces platform
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- **Sunbird AI** for Kikuyu language models
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- **African language communities** for their support and feedback
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## Citation
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If you use JamboGPT in your research, please cite:
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```bibtex
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@software{jambogpt2026,
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title={JamboGPT: African Language AI},
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author={Your Name},
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year={2026},
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url={https://huggingface.co/spaces/YOUR_USERNAME/jambogpt}
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}
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```
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## Contact
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- GitHub Issues: [Report a bug](https://github.com/YOUR_USERNAME/jambogpt/issues)
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- Email: your.email@example.com
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- Twitter: [@YourHandle](https://twitter.com/YourHandle)
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---
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**Jambo** means "hello" in Swahili. We're bringing AI to African languages. π
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app.py
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| 1 |
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#!/usr/bin/env python3
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| 2 |
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"""
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| 3 |
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JamboGPT - African Language AI
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| 4 |
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A Gradio-based application for Text-to-Speech and Chat in Kenyan and African languages.
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| 5 |
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Inspired by Yarn GPT by Saheed Azeez.
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"""
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| 7 |
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import os
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import gradio as gr
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import torch
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import torchaudio
|
| 12 |
+
from transformers import pipeline
|
| 13 |
+
import numpy as np
|
| 14 |
+
from scipy.io import wavfile
|
| 15 |
+
import tempfile
|
| 16 |
+
|
| 17 |
+
# Set device
|
| 18 |
+
device = "cuda" if torch.cuda.is_available() else "cpu"
|
| 19 |
+
print(f"Using device: {device}")
|
| 20 |
+
|
| 21 |
+
# Language configurations
|
| 22 |
+
LANGUAGES = {
|
| 23 |
+
"Swahili": {
|
| 24 |
+
"code": "swh",
|
| 25 |
+
"tts_model": "facebook/mms-tts-swh",
|
| 26 |
+
"description": "East African language spoken in Kenya, Tanzania, Uganda"
|
| 27 |
+
},
|
| 28 |
+
"Kikuyu": {
|
| 29 |
+
"code": "ki",
|
| 30 |
+
"tts_model": "BrianMwangi/African-Kikuyu-TTS",
|
| 31 |
+
"description": "Bantu language spoken in central Kenya"
|
| 32 |
+
},
|
| 33 |
+
"English": {
|
| 34 |
+
"code": "eng",
|
| 35 |
+
"tts_model": "facebook/mms-tts-eng",
|
| 36 |
+
"description": "English language"
|
| 37 |
+
},
|
| 38 |
+
}
|
| 39 |
+
|
| 40 |
+
# Cache for loaded models
|
| 41 |
+
model_cache = {}
|
| 42 |
+
|
| 43 |
+
def load_tts_model(language_name):
|
| 44 |
+
"""Load TTS model for the specified language."""
|
| 45 |
+
if language_name not in LANGUAGES:
|
| 46 |
+
return None
|
| 47 |
+
|
| 48 |
+
lang_config = LANGUAGES[language_name]
|
| 49 |
+
model_id = lang_config["tts_model"]
|
| 50 |
+
|
| 51 |
+
# Check cache
|
| 52 |
+
if model_id in model_cache:
|
| 53 |
+
return model_cache[model_id]
|
| 54 |
+
|
| 55 |
+
try:
|
| 56 |
+
print(f"Loading TTS model for {language_name}: {model_id}")
|
| 57 |
+
synthesizer = pipeline(
|
| 58 |
+
"text-to-speech",
|
| 59 |
+
model=model_id,
|
| 60 |
+
device=device if device == "cuda" else -1
|
| 61 |
+
)
|
| 62 |
+
model_cache[model_id] = synthesizer
|
| 63 |
+
return synthesizer
|
| 64 |
+
except Exception as e:
|
| 65 |
+
print(f"Error loading model {model_id}: {e}")
|
| 66 |
+
return None
|
| 67 |
+
|
| 68 |
+
def generate_speech(text, language):
|
| 69 |
+
"""Generate speech from text in the specified language."""
|
| 70 |
+
if not text or not text.strip():
|
| 71 |
+
return None, "Please enter some text to generate speech."
|
| 72 |
+
|
| 73 |
+
if len(text) > 1000:
|
| 74 |
+
return None, "Text is too long. Maximum 1000 characters allowed."
|
| 75 |
+
|
| 76 |
+
try:
|
| 77 |
+
synthesizer = load_tts_model(language)
|
| 78 |
+
if synthesizer is None:
|
| 79 |
+
return None, f"Failed to load TTS model for {language}."
|
| 80 |
+
|
| 81 |
+
print(f"Generating speech for: {text[:50]}...")
|
| 82 |
+
|
| 83 |
+
# Generate speech
|
| 84 |
+
speech = synthesizer(text)
|
| 85 |
+
|
| 86 |
+
# Extract audio
|
| 87 |
+
audio_array = np.array(speech["audio"]).flatten()
|
| 88 |
+
sample_rate = speech["sampling_rate"]
|
| 89 |
+
|
| 90 |
+
# Save to temporary file
|
| 91 |
+
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
|
| 92 |
+
wavfile.write(f.name, sample_rate, (audio_array * 32767).astype(np.int16))
|
| 93 |
+
temp_path = f.name
|
| 94 |
+
|
| 95 |
+
return temp_path, f"β Speech generated successfully in {language}!"
|
| 96 |
+
|
| 97 |
+
except Exception as e:
|
| 98 |
+
print(f"Error generating speech: {e}")
|
| 99 |
+
return None, f"Error generating speech: {str(e)}"
|
| 100 |
+
|
| 101 |
+
def create_interface():
|
| 102 |
+
"""Create the Gradio interface."""
|
| 103 |
+
|
| 104 |
+
with gr.Blocks(
|
| 105 |
+
title="JamboGPT - African Language AI",
|
| 106 |
+
theme=gr.themes.Soft(
|
| 107 |
+
primary_hue="blue",
|
| 108 |
+
secondary_hue="cyan",
|
| 109 |
+
)
|
| 110 |
+
) as demo:
|
| 111 |
+
|
| 112 |
+
# Header
|
| 113 |
+
gr.Markdown(
|
| 114 |
+
"""
|
| 115 |
+
# π JamboGPT - African Language AI
|
| 116 |
+
### Text-to-Speech for Kenyan & African Languages
|
| 117 |
+
|
| 118 |
+
Generate high-quality audio in Swahili, Kikuyu, English and more.
|
| 119 |
+
Inspired by **Yarn GPT** by Saheed Azeez.
|
| 120 |
+
|
| 121 |
+
---
|
| 122 |
+
"""
|
| 123 |
+
)
|
| 124 |
+
|
| 125 |
+
with gr.Tabs():
|
| 126 |
+
# Tab 1: Text-to-Speech
|
| 127 |
+
with gr.Tab("π€ Text-to-Speech"):
|
| 128 |
+
gr.Markdown("""
|
| 129 |
+
### Generate Speech from Text
|
| 130 |
+
Enter your text and select a language to generate natural-sounding speech.
|
| 131 |
+
""")
|
| 132 |
+
|
| 133 |
+
with gr.Row():
|
| 134 |
+
with gr.Column(scale=2):
|
| 135 |
+
text_input = gr.Textbox(
|
| 136 |
+
label="Enter Text",
|
| 137 |
+
placeholder="Type your text here (max 1000 characters)...",
|
| 138 |
+
lines=5,
|
| 139 |
+
max_lines=10
|
| 140 |
+
)
|
| 141 |
+
|
| 142 |
+
with gr.Column(scale=1):
|
| 143 |
+
language_select = gr.Dropdown(
|
| 144 |
+
choices=list(LANGUAGES.keys()),
|
| 145 |
+
value="Swahili",
|
| 146 |
+
label="Select Language",
|
| 147 |
+
interactive=True
|
| 148 |
+
)
|
| 149 |
+
|
| 150 |
+
generate_btn = gr.Button(
|
| 151 |
+
"π΅ Generate Speech",
|
| 152 |
+
variant="primary",
|
| 153 |
+
scale=1
|
| 154 |
+
)
|
| 155 |
+
|
| 156 |
+
with gr.Row():
|
| 157 |
+
audio_output = gr.Audio(
|
| 158 |
+
label="Generated Audio",
|
| 159 |
+
type="filepath",
|
| 160 |
+
interactive=False
|
| 161 |
+
)
|
| 162 |
+
|
| 163 |
+
status_msg = gr.Textbox(
|
| 164 |
+
label="Status",
|
| 165 |
+
interactive=False,
|
| 166 |
+
value="Ready to generate speech"
|
| 167 |
+
)
|
| 168 |
+
|
| 169 |
+
# Connect button to function
|
| 170 |
+
generate_btn.click(
|
| 171 |
+
fn=generate_speech,
|
| 172 |
+
inputs=[text_input, language_select],
|
| 173 |
+
outputs=[audio_output, status_msg]
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
# Tab 2: Language Info
|
| 177 |
+
with gr.Tab("βΉοΈ Language Information"):
|
| 178 |
+
gr.Markdown("""
|
| 179 |
+
### Supported Languages
|
| 180 |
+
|
| 181 |
+
JamboGPT supports the following African languages:
|
| 182 |
+
""")
|
| 183 |
+
|
| 184 |
+
lang_info = []
|
| 185 |
+
for lang_name, lang_config in LANGUAGES.items():
|
| 186 |
+
lang_info.append(f"""
|
| 187 |
+
**{lang_name}** ({lang_config['code']})
|
| 188 |
+
- {lang_config['description']}
|
| 189 |
+
- Model: `{lang_config['tts_model']}`
|
| 190 |
+
""")
|
| 191 |
+
|
| 192 |
+
gr.Markdown("\n".join(lang_info))
|
| 193 |
+
|
| 194 |
+
gr.Markdown("""
|
| 195 |
+
---
|
| 196 |
+
|
| 197 |
+
### About JamboGPT
|
| 198 |
+
|
| 199 |
+
JamboGPT is an open-source African Language AI application built with:
|
| 200 |
+
- **Gradio** for the user interface
|
| 201 |
+
- **Hugging Face Transformers** for language models
|
| 202 |
+
- **Meta's MMS (Massively Multilingual Speech)** for TTS
|
| 203 |
+
|
| 204 |
+
### Features
|
| 205 |
+
- π€ High-quality Text-to-Speech
|
| 206 |
+
- π Multiple African languages
|
| 207 |
+
- β‘ Fast inference
|
| 208 |
+
- π Open-source and free
|
| 209 |
+
|
| 210 |
+
### Get Involved
|
| 211 |
+
- GitHub: [JamboGPT Repository](https://github.com)
|
| 212 |
+
- Hugging Face: [JamboGPT Spaces](https://huggingface.co/spaces)
|
| 213 |
+
|
| 214 |
+
---
|
| 215 |
+
|
| 216 |
+
**Inspired by Yarn GPT by Saheed Azeez**
|
| 217 |
+
|
| 218 |
+
JamboGPT brings similar TTS capabilities to African languages,
|
| 219 |
+
making AI more accessible across the continent.
|
| 220 |
+
""")
|
| 221 |
+
|
| 222 |
+
# Footer
|
| 223 |
+
gr.Markdown("""
|
| 224 |
+
---
|
| 225 |
+
**JamboGPT** Β© 2026 | Built with β€οΈ for African Languages
|
| 226 |
+
|
| 227 |
+
*Jambo* means "hello" in Swahili. We're bringing AI to African languages.
|
| 228 |
+
""")
|
| 229 |
+
|
| 230 |
+
return demo
|
| 231 |
+
|
| 232 |
+
if __name__ == "__main__":
|
| 233 |
+
print("π Starting JamboGPT - African Language AI")
|
| 234 |
+
print("=" * 50)
|
| 235 |
+
|
| 236 |
+
demo = create_interface()
|
| 237 |
+
|
| 238 |
+
# Launch the app
|
| 239 |
+
demo.launch(
|
| 240 |
+
server_name="0.0.0.0",
|
| 241 |
+
server_port=7860,
|
| 242 |
+
share=False,
|
| 243 |
+
show_error=True,
|
| 244 |
+
show_api=True
|
| 245 |
+
)
|
requirements.txt
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
gradio==6.14.0
|
| 2 |
+
torch==2.11.0
|
| 3 |
+
torchaudio==2.11.0
|
| 4 |
+
transformers==5.8.0
|
| 5 |
+
scipy==1.17.1
|
| 6 |
+
librosa==0.11.0
|
| 7 |
+
pydub==0.25.1
|
| 8 |
+
huggingface-hub==1.14.0
|
| 9 |
+
numpy==2.4.4
|