import sagea
 
client = sagea.VoraClient(api_key="your-api-key")
 
# Basic synthesis with emotion
audio = client.synthesize(
    text="Welcome to SAGEA! I'm excited to help you today.",
    model="vora-v1",
    emotion="excited",
    voice="default"
)
 
# Advanced emotion control
audio = client.synthesize(
    text="I understand your concern, and I'm here to help.",
    model="vora-v1",
    emotion="empathetic",
    speaking_rate=0.9,
    pitch_shift=-0.1
)
 
# Multilingual synthesis
audio = client.synthesize(
    text="Bonjour! Comment allez-vous aujourd'hui?",
    model="vora-v1",
    language="fr-FR",
    emotion="friendly"
)

# Edge deployment example
client = sagea.VoraClient(
    model="vora-l1",
    deployment="edge"  # Run locally
)
 
# Batch processing for efficiency
texts = [
    "Good morning!",
    "How can I help you?",
    "Have a great day!"
]
 
audios = client.batch_synthesize(
    texts=texts,
    model="vora-l1",
    emotion="helpful"
)

// React Native example
import { VoraMobile } from '@sagea/react-native';
 
const VoiceComponent = () => {
  const synthesize = async (text) => {
    const audio = await VoraMobile.synthesize({
      text,
      model: 'vora-l1',
      emotion: 'friendly',
      offline: true  // Use cached model
    });
    
    VoraMobile.play(audio);
  };
 
  return (
    <Button onPress={() => synthesize("Hello from mobile!")} />
  );
};

# Real-time conversational AI
import asyncio
 
async def real_time_conversation():
    client = sagea.VoraClient(model="vora-e0")
    
    # Create streaming connection
    stream = await client.create_stream()
    
    # Process user input in real-time
    async for user_input in get_user_audio():
        # Convert speech to text (external)
        text = await speech_to_text(user_input)
        
        # Generate response
        response_text = await generate_response(text)
        
        # Synthesize immediately
        audio_chunk = await stream.synthesize(
            text=response_text,
            emotion="conversational"
        )
        
        # Play without delay
        await play_audio(audio_chunk)

# Language-specific pronunciation
audio = client.synthesize(
    text="Hello, नमस्ते, and Bonjour!",
    model="vora-v1",
    language="mixed",  # Auto-detect and switch
    emotion="welcoming"
)
 
# Regional accents
audio = client.synthesize(
    text="G'day mate, how ya going?",
    model="vora-v1",
    language="en-AU",  # Australian English
    accent="australian"
)

# Create a custom voice with just a few samples
voice_id = client.clone_voice(
    name="custom_voice",
    audio_samples=[
        "sample1.wav",
        "sample2.wav", 
        "sample3.wav"
    ],
    text_transcripts=[
        "This is the first sample text.",
        "Here's another sample for training.",
        "And one more for good measure."
    ]
)
 
# Use the cloned voice
audio = client.synthesize(
    text="Hello! This is my cloned voice speaking.",
    model="vora-v1",
    voice_id=voice_id
)

# Generate watermarked audio
audio = client.synthesize(
    text="This is protected content.",
    model="vora-v1",
    watermark=True,
    watermark_id="unique-content-id"
)
 
# Verify watermark
verification = client.verify_watermark(audio_file="generated.wav")
print(f"Watermark verified: {verification.is_valid}")
print(f"Content ID: {verification.content_id}")

try:
    audio = client.synthesize(
        text="Your message here",
        model="vora-v1"
    )
except sagea.RateLimitError:
    # Handle rate limiting
    time.sleep(1)
    audio = client.synthesize(text, model="vora-l1")
except sagea.ModelError as e:
    # Handle model-specific errors
    print(f"Model error: {e.message}")