Metadata-Version: 2.1
Name: securespeakai-sdk
Version: 1.0.1
Summary: SecureSpeakAI Python SDK for deepfake detection with comprehensive API support
Home-page: https://securespeakai.com
Author: SecureSpeakAI
Author-email: nsharma@securespeakai.com
Project-URL: Documentation, https://securespeakai.com/docs
Project-URL: Homepage, https://securespeakai.com
Project-URL: Support, https://securespeakai.com/support
Keywords: deepfake detection,audio analysis,AI,machine learning,api,sdk
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.25.0
Requires-Dist: websocket-client>=1.2.0
Requires-Dist: typing-extensions>=4.0.0
Requires-Dist: pyaudio>=0.2.11

# SecureSpeak AI Python SDK

The official Python SDK for SecureSpeak AI — Professional deepfake detection.

## Installation

```bash
pip install securespeakai-sdk
```

## Quick Start

```python
from securespeak import SecureSpeakClient

# Initialize client with your API key
client = SecureSpeakClient("your-api-key-here")

# Analyze a local audio file
result = client.analyze_file("suspicious_audio.wav")

# Check if it's a deepfake
if result['label'] == 'AI':
    print(f"DEEPFAKE DETECTED! Confidence: {result['confidence']:.2f}")
else:
    print(f"Authentic audio. Confidence: {result['confidence']:.2f}")
```

## Authentication

The SDK supports two types of authentication:

### 1. API Key Authentication (Required)
```python
from securespeak import SecureSpeakClient

client = SecureSpeakClient("your-api-key-here")
```

### 2. Firebase Authentication (Optional - for billing endpoints)
```python
from securespeak import SecureSpeakClient

client = SecureSpeakClient(
    api_key="your-api-key-here",
    firebase_token="your-firebase-id-token"
)
```

## Core Analysis Methods

### File Analysis
```python
# Analyze local audio files
result = client.analyze_file("audio.wav")
print(f"Result: {result['label']}, Confidence: {result['confidence']:.2f}")
```

### URL Analysis
```python
# Analyze audio from URLs (YouTube, social media, etc.)
result = client.analyze_url("https://youtube.com/watch?v=example")
print(f"Result: {result['label']}, Confidence: {result['confidence']:.2f}")
```

### Live Analysis

**Note:** Live analysis requires `pyaudio` for microphone capture. Install with: `pip install pyaudio`

```python
# Real-time analysis with microphone capture
import pyaudio
import wave
import io

def capture_and_analyze_live():
    # Configure audio settings
    FORMAT = pyaudio.paInt16
    CHANNELS = 1
    RATE = 44100
    CHUNK = 1024
    RECORD_SECONDS = 3  # Analyze every 3 seconds
    
    audio = pyaudio.PyAudio()
    
    # Start recording from microphone
    stream = audio.open(format=FORMAT,
                       channels=CHANNELS,
                       rate=RATE,
                       input=True,
                       frames_per_buffer=CHUNK)
    
    print("Listening for audio...")
    
    while True:
        frames = []
        
        # Record for specified duration
        for _ in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
            data = stream.read(CHUNK)
            frames.append(data)
        
        # Convert to audio file format
        audio_data = io.BytesIO()
        wf = wave.open(audio_data, 'wb')
        wf.setnchannels(CHANNELS)
        wf.setsampwidth(audio.get_sample_size(FORMAT))
        wf.setframerate(RATE)
        wf.writeframes(b''.join(frames))
        wf.close()
        
        # Analyze the captured audio
        try:
            result = client.analyze_live_audio(audio_data.getvalue())
            print(f"Live result: {result['label']}, Confidence: {result['confidence']:.2f}")
        except Exception as e:
            print(f"Analysis error: {e}")
    
    stream.stop_stream()
    stream.close()
    audio.terminate()

# Run live analysis
capture_and_analyze_live()
```

## Billing & Account Management

### Get Account Balance
```python
try:
    balance_info = client.get_balance()
    print(f"Current balance: ${balance_info['balance']:.2f}")
    print(f"Usage: {balance_info['usage']}")
except Exception as e:
    print(f"Error: {e}")
```

### Get Billing Configuration
```python
config = client.get_billing_config()
print(f"Pricing: {config['pricing']}")
```

### Create Payment Intent
```python
try:
    payment_intent = client.create_payment_intent(amount=50.0)
    print(f"Payment intent created: {payment_intent['client_secret']}")
except Exception as e:
    print(f"Error: {e}")
```

## API Key Management

### Get All User Keys
```python
keys = client.get_user_keys()
for key in keys:
    print(f"Key: {key['name']}, Usage: {key['usage_count']}")
```

### Get Key Statistics
```python
stats = client.get_key_stats("your-key-id")
print(f"Total usage: {stats['usage']['total']}")
print(f"AI detected: {stats['usage']['ai_detected']}")
```

### Get Analysis History
```python
history = client.get_analysis_history("your-key-id", limit=10)
for analysis in history['history']:
    print(f"Time: {analysis['timestamp']}, Result: {analysis['label']}")
```

## WebSocket Real-time Analysis

For continuous real-time analysis:

```python
from securespeak import SecureSpeakClient

def on_prediction(result):
    print(f"Real-time result: {result['label']}, Confidence: {result['confidence']:.2f}")

client = SecureSpeakClient("your-api-key-here")
ws_client = client.create_websocket_connection(on_prediction)

try:
    ws_client.connect()
    
    # Send audio frames
    with open("audio_frame.wav", "rb") as f:
        audio_data = f.read()
        ws_client.send_audio_frame(audio_data)
    
    # Keep connection alive
    import time
    time.sleep(10)
    
finally:
    ws_client.close()
```

## Debug & Monitoring

### System Health Check
```python
status = client.keep_alive()
print(f"API Status: {status['status']}")
```

### Model Information
```python
model_info = client.get_model_info()
print(f"Model status: {model_info['status']}")
```

### Environment Information
```python
env_info = client.get_environment_info()
print(f"Python version: {env_info['python_version']}")
print(f"TensorFlow version: {env_info['tensorflow_version']}")
```

## Response Format

All analysis methods return a comprehensive JSON response:

```json
{
  "label": "AI",
  "confidence": 0.95,
  "analysis_time_ms": 1200,
  "file_info": {
    "filename": "audio.wav",
    "format": "wav",
    "source_type": "uploaded_file",
    "size_bytes": 1024000
  },
  "audio_metadata": {
    "duration_sec": 30.5,
    "sample_rate": 44100,
    "channels": 1
  },
  "endpoint": "/analyze_file",
  "timestamp": "2024-01-01T12:00:00Z"
}
```

## Error Handling

The SDK includes comprehensive error handling:

```python
from securespeak import SecureSpeakClient, SecureSpeakAPIError

client = SecureSpeakClient("your-api-key-here")

try:
    result = client.analyze_file("audio.wav")
except SecureSpeakAPIError as e:
    print(f"API Error ({e.status_code}): {e.message}")
    if e.details:
        print(f"Details: {e.details}")
except Exception as e:
    print(f"Unexpected error: {e}")
```

## Pricing

- **File Analysis**: $0.018 per file
- **URL Analysis**: $0.025 per URL
- **Live Analysis**: $0.032 per second

*Enterprise customers may have custom pricing. Check your billing configuration.*

## Requirements

- Python 3.7 or higher
- Valid SecureSpeak AI API key
- Optional: Firebase authentication for billing endpoints

## Dependencies

- `requests>=2.25.0`
- `websocket-client>=1.2.0`
- `typing-extensions>=4.0.0`

## Advanced Usage

### Batch Processing
```python
import os
from securespeak import SecureSpeakClient

client = SecureSpeakClient("your-api-key-here")

# Process multiple files
audio_files = ["file1.wav", "file2.wav", "file3.wav"]
results = []

for file_path in audio_files:
    try:
        result = client.analyze_file(file_path)
        results.append({
            'file': file_path,
            'label': result['label'],
            'confidence': result['confidence']
        })
    except Exception as e:
        print(f"Error processing {file_path}: {e}")

# Print results
for result in results:
    print(f"{result['file']}: {result['label']} ({result['confidence']:.2f})")
```

### Custom Error Handling
```python
from securespeak import SecureSpeakClient, SecureSpeakAPIError

client = SecureSpeakClient("your-api-key-here")

try:
    result = client.analyze_file("audio.wav")
except SecureSpeakAPIError as e:
    if e.status_code == 402:  # Payment Required
        print("Insufficient balance!")
        print(f"Required: ${e.details.get('required_amount', 0):.3f}")
        print(f"Available: ${e.details.get('current_balance', 0):.3f}")
    elif e.status_code == 403:
        print("Invalid API key!")
    else:
        print(f"API Error: {e.message}")
```

## Documentation

For complete documentation, examples, pricing, and API reference, visit: https://securespeakai.com/docs

## Support

- Website: https://securespeakai.com
- Dashboard: https://securespeakai.com/dashboard
- Support: https://securespeakai.com/support

## License

MIT License
