Add HuggingFace Spaces deployment config

Dockerfile

@@ -0,0 +1,29 @@
+FROM python:3.10-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    libsndfile1 \
+    ffmpeg \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for caching
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY src/ ./src/
+COPY models/ ./models/
+COPY app.py .
+COPY download_models.py .
+
+# Create output directory
+RUN mkdir -p outputs
+
+# Expose port for HuggingFace Spaces
+EXPOSE 7860
+
+# Run the app
+CMD ["python", "app.py"]

README.md

@@ -1,246 +1,74 @@
-# Voice Tech for All - Multi-lingual TTS System
+---
+title: VoiceAPI - Multi-lingual TTS
+emoji: 🎤
+colorFrom: blue
+colorTo: purple
+sdk: docker
+app_port: 7860
+pinned: true
+license: mit
+---
+
+# VoiceAPI - Multi-lingual Text-to-Speech
 
-A lightweight, multi-lingual Text-to-Speech system supporting **11 Indian languages** with **style/prosody control** and REST API.
+A multi-lingual Text-to-Speech API supporting **11 Indian languages** designed for healthcare applications helping pregnant mothers in low-income communities.
 
-## 🎯 Hackathon: Voice Tech for All
+## 🎯 Voice Tech for All Hackathon
 
-Built for the healthcare assistant use case - helping pregnant mothers in low-income communities access healthcare information in their native languages.
+Built for LLM-based healthcare assistants to deliver medical guidance in native languages.
 
 ## ✨ Features
 
-- **11 Indian Languages**: Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Chhattisgarhi, Maithili, Magahi, English, **Gujarati**
+- **11 Indian Languages**: Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Chhattisgarhi, Maithili, Magahi, English, Gujarati
 - **21 Voice Options**: Male & Female voices for each language
-- **Style/Prosody Control**: 9 presets (happy, sad, calm, excited, etc.)
-- **Pitch & Speed Control**: Fine-tune voice characteristics
-- **Lightweight**: VITS-based models optimized for fast inference
-- **REST API**: FastAPI-powered server with OpenAPI docs
-- **Text Normalization**: Handles numbers, punctuation for Indian scripts
-
-## 🚀 Quick Start
-
-### 1. Installation
-
-```bash
-# Clone and navigate
-git clone https://github.com/harshil748/VoiceAPI
-cd VoiceAPI
-
-# Create virtual environment
-python3 -m venv tts
-source tts/bin/activate
-
-# Install dependencies
-pip install -r requirements.txt
-```
-
-### 2. Download Models
-
-```bash
-# Download Hindi models (male + female)
-python -m src.cli download --lang hi
-
-# Or download a specific voice
-python -m src.cli download --voice hi_male
+- **REST API**: FastAPI with OpenAPI docs at `/docs`
 
-# Gujarati uses Facebook MMS (auto-downloads on first use)
-```
-
-### 3. Synthesize Speech
-
-```bash
-# Basic synthesis
-python -m src.cli synthesize --text "नमस्ते दोस्तों" --voice hi_male --output hello.wav
+## 🔌 API Endpoint
 
-# Play the audio (macOS)
-afplay hello.wav
 ```
-
-### 4. Start API Server
-
-```bash
-python -m src.cli serve --port 8000
+GET /Get_Inference?text=नमस्ते&lang=hindi
 ```
 
-Visit `http://localhost:8000/docs` for interactive API documentation.
-
-## 🎨 Style Presets
+### Parameters
 
-| Preset    | Speed | Pitch | Energy | Best For                |
-| --------- | ----- | ----- | ------ | ----------------------- |
-| `default` | 1.0   | 1.0   | 1.0    | Normal speech           |
-| `slow`    | 0.75  | 1.0   | 1.0    | Elderly users, clarity  |
-| `fast`    | 1.25  | 1.0   | 1.0    | Quick information       |
-| `soft`    | 0.9   | 0.95  | 0.7    | Calming content         |
-| `loud`    | 1.0   | 1.05  | 1.3    | Alerts, emphasis        |
-| `happy`   | 1.1   | 1.1   | 1.2    | Positive messages       |
-| `sad`     | 0.85  | 0.9   | 0.8    | Empathetic responses    |
-| `calm`    | 0.9   | 0.95  | 0.85   | **Healthcare guidance** |
-| `excited` | 1.2   | 1.15  | 1.3    | Celebrations            |
+| Parameter | Type | Required | Description |
+|-----------|------|----------|-------------|
+| text | string | ✅ | Text to synthesize |
+| lang | string | ✅ | Language: hindi, bengali, marathi, telugu, kannada, bhojpuri, chhattisgarhi, maithili, magahi, english, gujarati |
+| speaker_wav | file | ✅ | Reference WAV file |
 
-## 📡 API Usage
-
-### 🏆 Hackathon API - GET /Get_Inference
-
-**This is the official hackathon endpoint** that follows the Voice Tech for All specification:
+### Example
 
 ```python
 import requests
 
-base_url = 'http://localhost:8000/Get_Inference'
-WavPath = 'path/to/reference.wav'
-
-params = {
-    'text': 'ಮಾದರಿಯು ಸರಿಯಾಗಿ ಕಾರ್ಯನಿರ್ವಹಿಸುತ್ತಿದೆಯೇ ಎಂದು ಖಚಿತಪಡಿಸಿಕೊಳ್ಳಲು ಬಳಸಲಾಗುವ ಪರೀಕ್ಷಾ ವಾಕ್ಯ ಇದು.',
-    'lang': 'kannada',
-}
-
-with open(WavPath, "rb") as AudioFile:
-    response = requests.get(base_url, params=params, files={'speaker_wav': AudioFile})
-
-if response.status_code == 200:
-    with open('output.wav', 'wb') as f:
-        f.write(response.content)
-    print("Audio saved as 'output.wav'")
-```
-
-**Query Parameters:**
-
-| Parameter     | Type   | Required  | Description                                                                                                      |
-| ------------- | ------ | --------- | ---------------------------------------------------------------------------------------------------------------- |
-| `text`        | string | Mandatory | Input text to convert to speech. For English, text must be lowercase.                                            |
-| `lang`        | string | Mandatory | Language: bhojpuri, bengali, english, gujarati, hindi, chhattisgarhi, kannada, magahi, maithili, marathi, telugu |
-| `speaker_wav` | file   | Mandatory | Reference WAV file for speaker voice                                                                             |
-
-**Response:** `200 OK` with `Content-Type: audio/wav`
-
----
-
-### Synthesize with Style (POST)
-
-```bash
-curl -X POST "http://localhost:8000/synthesize" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "text": "आपका दिन शुभ हो",
-    "voice": "hi_female",
-    "style": "happy",
-    "speed": 1.0,
-    "pitch": 1.0
-  }' \
-  --output speech.wav
-```
-
-### Gujarati Synthesis
-
-```bash
-curl -X POST "http://localhost:8000/synthesize" \
-  -H "Content-Type: application/json" \
-  -d '{"text": "નમસ્તે, કેમ છો?", "voice": "gu_mms", "style": "calm"}' \
-  --output gujarati.wav
-```
-
-### List Style Presets
-
-```bash
-curl http://localhost:8000/styles
-```
-
-## 🎤 Available Voices
-
-| Language      | Code | Male        | Female        | Notes        |
-| ------------- | ---- | ----------- | ------------- | ------------ |
-| Hindi         | hi   | ✅ hi_male  | ✅ hi_female  | SYSPIN       |
-| Bengali       | bn   | ✅ bn_male  | ✅ bn_female  | SYSPIN       |
-| Marathi       | mr   | ✅ mr_male  | ✅ mr_female  | SYSPIN       |
-| Telugu        | te   | ✅ te_male  | ✅ te_female  | SYSPIN       |
-| Kannada       | kn   | ✅ kn_male  | ✅ kn_female  | SYSPIN       |
-| Bhojpuri      | bho  | ✅ bho_male | ✅ bho_female | SYSPIN       |
-| Chhattisgarhi | hne  | ✅ hne_male | ✅ hne_female | SYSPIN       |
-| Maithili      | mai  | ✅ mai_male | ✅ mai_female | SYSPIN       |
-| Magahi        | mag  | ✅ mag_male | ✅ mag_female | SYSPIN       |
-| English       | en   | ✅ en_male  | ✅ en_female  | SYSPIN       |
-| **Gujarati**  | gu   | ✅ gu_mms   | -             | Facebook MMS |
+url = "https://Harshil748-voiceapi.hf.space/Get_Inference"
+params = {"text": "नमस्ते, आप कैसे हैं?", "lang": "hindi"}
 
-## 🐍 Python API
-
-```python
-from src.engine import TTSEngine
-
-# Initialize engine
-engine = TTSEngine(device="auto")
-
-# Basic synthesis
-output = engine.synthesize(
-    text="गर्भावस्था में स्वस्थ आहार महत्वपूर्ण है",
-    voice="hi_female"
-)
-
-# With style control
-output = engine.synthesize(
-    text="आपका दिन शुभ हो",
-    voice="hi_male",
-    style="happy",      # Use preset
-    pitch=1.1,          # Or manual control
-    speed=1.0,
-    energy=1.2
-)
-
-# Gujarati
-output = engine.synthesize(
-    text="સ્વસ્થ રહો, ખુશ રહો",
-    voice="gu_mms",
-    style="calm"
-)
-
-# Save to file
-engine.synthesize_to_file(
-    text="નમસ્તે",
-    output_path="hello.wav",
-    voice="gu_mms",
-    style="calm"
-)
-```
+with open("reference.wav", "rb") as f:
+    response = requests.get(url, params=params, files={"speaker_wav": f})
 
-## 📁 Project Structure
-
-```text
-VoiceAPI/
-├── src/
-│   ├── config.py      # Language/voice/style configurations
-│   ├── tokenizer.py   # Text tokenization & normalization
-│   ├── engine.py      # Main TTS engine with style processor
-│   ├── downloader.py  # HuggingFace model downloader
-│   ├── api.py         # FastAPI REST server
-│   └── cli.py         # Command-line interface
-├── models/            # Downloaded models
-├── dataset/           # SPICOR dataset (for fine-tuning)
-├── technical_report.md
-├── requirements.txt
-└── README.md
+with open("output.wav", "wb") as f:
+    f.write(response.content)
 ```
 
-## 📊 Performance
-
-| Metric         | Value                           |
-| -------------- | ------------------------------- |
-| Languages      | 11                              |
-| Voice Variants | 21                              |
-| Style Presets  | 9                               |
-| Model Size     | ~300MB (VITS), ~145MB (MMS)     |
-| Inference Time | ~0.3s (M2 Mac, CPU)             |
-| Sample Rate    | 22050 Hz (VITS), 16000 Hz (MMS) |
+## 📊 Supported Languages
+
+| Language | Code | Voices |
+|----------|------|--------|
+| Hindi | hindi | Male, Female |
+| Bengali | bengali | Male, Female |
+| Marathi | marathi | Male, Female |
+| Telugu | telugu | Male, Female |
+| Kannada | kannada | Male, Female |
+| Gujarati | gujarati | MMS |
+| Bhojpuri | bhojpuri | Male, Female |
+| Chhattisgarhi | chhattisgarhi | Male, Female |
+| Maithili | maithili | Male, Female |
+| Magahi | magahi | Male, Female |
+| English | english | Male, Female |
 
 ## 🙏 Credits
 
-- **SYSPIN Models**: [IISc Bangalore](https://huggingface.co/SYSPIN)
-- **MMS Models**: [Facebook Research](https://huggingface.co/facebook/mms-tts-guj)
-- **Architecture**: VITS (Coqui AI)
-- **Dataset**: SPICOR TTS Project, IISc SPIRE Lab
-
-## 📜 License
-
-CC BY 4.0 (SYSPIN), CC BY-NC 4.0 (MMS)
-
----
-
-Built with ❤️ for **Voice Tech for All Hackathon**
+- **Models**: SYSPIN (IISc Bangalore), Facebook MMS
+- **Team**: Harshil Patel, Aashvi Maurya, Jaideep, Pratyush

app.py

@@ -0,0 +1,19 @@
+"""
+HuggingFace Spaces entry point for VoiceAPI
+Multi-lingual Text-to-Speech for Maternal Healthcare
+"""
+
+import os
+import sys
+
+# Add src to path
+sys.path.insert(0, os.path.dirname(__file__))
+
+from src.api import app
+
+# For HuggingFace Spaces
+if __name__ == "__main__":
+    import uvicorn
+
+    port = int(os.environ.get("PORT", 7860))
+    uvicorn.run(app, host="0.0.0.0", port=port)