app.py

 import gradio as gr
import numpy as np
import subprocess
import tempfile
import os
import json
from pathlib import Path
import base64
import wave

# Install ggwave if not already installed
try:
    import ggwave
except ImportError:
    subprocess.run(["pip", "install", "ggwave"], check=True)
    import ggwave

class GGWaveTransceiver:
    def __init__(self):
        self.sample_rate = 48000
        self.protocols = {
            'Normal': ggwave.GGWAVE_PROTOCOL_AUDIBLE_NORMAL,
            'Fast': ggwave.GGWAVE_PROTOCOL_AUDIBLE_FAST,
            'Fastest': ggwave.GGWAVE_PROTOCOL_AUDIBLE_FASTEST,
            'Ultrasonic': ggwave.GGWAVE_PROTOCOL_ULTRASONIC_NORMAL,
            'DT (Data Transfer)': ggwave.GGWAVE_PROTOCOL_DT_NORMAL,
        }
    
    def encode_text_to_audio(self, text, protocol='Normal', volume=50):
        """Encode text to audio using ggwave"""
        try:
            protocol_id = self.protocols.get(protocol, ggwave.GGWAVE_PROTOCOL_AUDIBLE_NORMAL)
            
            # Create ggwave instance
            instance = ggwave.GGWave(
                sample_rate=self.sample_rate,
                samples_per_frame=1024,
                sound_marker_threshold=0.1,
                marker_duration=0.2
            )
            
            # Encode text to audio
            audio_data = instance.encode(text.encode('utf-8'), protocol_id, volume)
            
            if audio_data is None:
                return None, "Failed to encode text"
            
            # Convert to numpy array
            audio_array = np.frombuffer(audio_data, dtype=np.float32)
            
            # Create temporary WAV file
            with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file:
                with wave.open(tmp_file.name, 'w') as wav_file:
                    wav_file.setnchannels(1)
                    wav_file.setsampwidth(2)
                    wav_file.setframerate(self.sample_rate)
                    
                    # Convert float32 to int16
                    audio_int16 = (audio_array * 32767).astype(np.int16)
                    wav_file.writeframes(audio_int16.tobytes())
                
                return tmp_file.name, f"Successfully encoded: '{text}' using {protocol} protocol"
        
        except Exception as e:
            return None, f"Error encoding: {str(e)}"
    
    def decode_audio_to_text(self, audio_file):
        """Decode audio file to text using ggwave"""
        try:
            if audio_file is None:
                return "No audio file provided"
            
            # Read audio file
            with wave.open(audio_file, 'r') as wav_file:
                frames = wav_file.readframes(wav_file.getnframes())
                audio_data = np.frombuffer(frames, dtype=np.int16)
                
                # Convert to float32
                audio_float = audio_data.astype(np.float32) / 32767.0
            
            # Create ggwave instance
            instance = ggwave.GGWave(
                sample_rate=self.sample_rate,
                samples_per_frame=1024,
                sound_marker_threshold=0.1,
                marker_duration=0.2
            )
            
            # Decode audio
            decoded = instance.decode(audio_float.tobytes())
            
            if decoded:
                return f"Decoded message: {decoded.decode('utf-8')}"
            else:
                return "No valid ggwave signal detected in audio"
                
        except Exception as e:
            return f"Error decoding: {str(e)}"

# Initialize the transceiver
transceiver = GGWaveTransceiver()

# Gradio interface functions
def encode_text(text, protocol, volume):
    """Encode text to audio for Gradio"""
    if not text.strip():
        return None, "Please enter text to encode"
    
    audio_file, message = transceiver.encode_text_to_audio(text, protocol, volume)
    return audio_file, message

def decode_audio(audio_file):
    """Decode audio to text for Gradio"""
    result = transceiver.decode_audio_to_text(audio_file)
    return result

def create_demo_audio():
    """Create a demo audio file"""
    demo_text = "Hello from ggwave!"
    audio_file, _ = transceiver.encode_text_to_audio(demo_text, 'Normal', 50)
    return audio_file

# Phone integration helper functions
def get_twilio_webhook_code():
    """Return sample Twilio webhook code"""
    return '''
# Twilio Webhook Integration Example
from flask import Flask, request
from twilio.twiml import VoiceResponse
import requests

app = Flask(__name__)

@app.route("/webhook", methods=['POST'])
def handle_call():
    """Handle incoming Twilio call"""
    response = VoiceResponse()
    
    # Record the call audio for ggwave processing
    response.record(
        max_length=30,
        action='/process_recording',
        transcribe=False,
        play_beep=False
    )
    
    return str(response)

@app.route("/process_recording", methods=['POST'])
def process_recording():
    """Process recorded audio through ggwave"""
    recording_url = request.form['RecordingUrl']
    
    # Download the recording
    audio_response = requests.get(recording_url)
    
    # Send to your ggwave processing endpoint
    # (This would be your Gradio space or separate service)
    result = process_with_ggwave(audio_response.content)
    
    # Respond back to caller
    response = VoiceResponse()
    response.say(f"Received data: {result}")
    
    return str(response)
'''

def get_deployment_instructions():
    """Return deployment instructions"""
    return '''
# Deployment Instructions for Phone Integration

## Option 1: Twilio Integration
1. Sign up for Twilio account
2. Get a phone number
3. Set up webhook URL pointing to your server
4. Use the provided webhook code to handle calls

## Option 2: Vonage/Nexmo Integration
Similar to Twilio, but with Vonage APIs

## Option 3: Direct SIP Integration
For more advanced users who want direct SIP handling

## Hugging Face Spaces Limitations:
- Spaces don't directly support phone call handling
- You'll need a separate service (like Heroku, Railway, etc.) for telephony
- Use this Space as your ggwave processing engine
- Call it via API from your phone handling service

## Architecture:
Phone Call → Telephony Service → Your Server → HF Space (ggwave) → Response
'''

# Create Gradio interface
with gr.Blocks(title="GGWave Phone Data Transfer", theme=gr.themes.Soft()) as app:
    gr.Markdown("""
    # 🎵 GGWave Phone Data Transfer System
    
    This system demonstrates data transmission over audio using ggwave. Perfect for sending data through phone calls!
    
    **How it works:**
    1. Encode text into audio signals
    2. Play the audio during a phone call
    3. Decode the received audio back to text
    """)
    
    with gr.Tabs():
        # Encoding tab
        with gr.Tab("📤 Encode Text to Audio"):
            with gr.Row():
                with gr.Column():
                    encode_input = gr.Textbox(
                        label="Text to Encode",
                        placeholder="Enter your message here...",
                        lines=3
                    )
                    
                    with gr.Row():
                        protocol_choice = gr.Dropdown(
                            choices=list(transceiver.protocols.keys()),
                            value="Normal",
                            label="Protocol"
                        )
                        volume_slider = gr.Slider(
                            minimum=10,
                            maximum=100,
                            value=50,
                            label="Volume %"
                        )
                    
                    encode_btn = gr.Button("🎵 Generate Audio", variant="primary")
                
                with gr.Column():
                    encoded_audio = gr.Audio(
                        label="Generated Audio",
                        type="filepath"
                    )
                    encode_status = gr.Textbox(
                        label="Status",
                        interactive=False
                    )
        
        # Decoding tab
        with gr.Tab("📥 Decode Audio to Text"):
            with gr.Row():
                with gr.Column():
                    decode_audio_input = gr.Audio(
                        label="Upload Audio File",
                        type="filepath"
                    )
                    decode_btn = gr.Button("🔍 Decode Audio", variant="primary")
                
                with gr.Column():
                    decoded_result = gr.Textbox(
                        label="Decoded Message",
                        interactive=False,
                        lines=5
                    )
        
        # Phone integration tab
        with gr.Tab("📞 Phone Integration"):
            gr.Markdown("""
            ## Setting up Phone Call Integration
            
            Since Hugging Face Spaces can't directly handle phone calls, you'll need to integrate with a telephony service:
            """)
            
            with gr.Accordion("📋 Twilio Webhook Code", open=False):
                twilio_code = gr.Code(
                    value=get_twilio_webhook_code(),
                    language="python",
                    label="Twilio Integration Code"
                )
            
            with gr.Accordion("🚀 Deployment Instructions", open=True):
                deployment_info = gr.Markdown(get_deployment_instructions())
            
            gr.Markdown("""
            ## API Usage
            
            You can call this Space programmatically:
            
            ```python
            import requests
            
            # For encoding
            response = requests.post(
                "https://your-space-url/api/predict",
                json={"data": ["your text", "Normal", 50]}
            )
            
            # Download the generated audio
            audio_url = response.json()["data"][0]
            ```
            """)
        
        # Testing tab
        with gr.Tab("🧪 Test & Demo"):
            gr.Markdown("## Try the Demo")
            
            with gr.Row():
                demo_btn = gr.Button("🎯 Generate Demo Audio", variant="secondary")
                demo_audio = gr.Audio(label="Demo Audio")
            
            gr.Markdown("""
            ## Testing Workflow:
            1. Click "Generate Demo Audio" above
            2. Download the audio file
            3. Go to the "Decode" tab and upload it
            4. Verify it decodes correctly
            
            ## Phone Testing:
            1. Generate audio for your message
            2. Call your phone integration service
            3. Play the audio during the call
            4. Verify the server receives the correct data
            """)
    
    # Event handlers
    encode_btn.click(
        fn=encode_text,
        inputs=[encode_input, protocol_choice, volume_slider],
        outputs=[encoded_audio, encode_status]
    )
    
    decode_btn.click(
        fn=decode_audio,
        inputs=[decode_audio_input],
        outputs=[decoded_result]
    )
    
    demo_btn.click(
        fn=create_demo_audio,
        outputs=[demo_audio]
    )

# Launch the app
if __name__ == "__main__":
    app.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True
    )