Multi-Voice Dialogue

from elevenlabs import ElevenLabs
from elevenlabs.types import DialogueInput

client = ElevenLabs(api_key="YOUR_API_KEY")

# Create a simple dialogue
dialogue = [
    DialogueInput(
        text="Hello! How can I help you today?",
        voice_id="21m00Tcm4TlvDq8ikWAM"  # Rachel
    ),
    DialogueInput(
        text="I'd like to know more about your services.",
        voice_id="AZnzlk1XvdvUeBnXmlld"  # Domi
    )
]

audio = client.text_to_dialogue.convert(inputs=dialogue)

with open("conversation.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)

from elevenlabs import ElevenLabs
from elevenlabs.types import DialogueInput

client = ElevenLabs(api_key="YOUR_API_KEY")

# Define the dialogue
dialogue = [
    DialogueInput(
        text="Welcome to our store! How may I assist you?",
        voice_id="voice_id_1"  # Store employee
    ),
    DialogueInput(
        text="Hi! I'm looking for a birthday gift.",
        voice_id="voice_id_2"  # Customer
    ),
    DialogueInput(
        text="Wonderful! What does the person enjoy?",
        voice_id="voice_id_1"  # Store employee
    ),
    DialogueInput(
        text="They love reading mystery novels.",
        voice_id="voice_id_2"  # Customer
    )
]

# Generate the dialogue
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

with open("conversation.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)

# Audiobook excerpt with narrator and character voices
audiobook_dialogue = [
    DialogueInput(
        text="The detective entered the dimly lit room,",
        voice_id="narrator_voice_id"
    ),
    DialogueInput(
        text="Someone's been here recently,",
        voice_id="detective_voice_id"
    ),
    DialogueInput(
        text="she said, examining the scattered papers.",
        voice_id="narrator_voice_id"
    ),
    DialogueInput(
        text="What are you doing here?",
        voice_id="suspect_voice_id"
    ),
    DialogueInput(
        text="a voice called from the doorway.",
        voice_id="narrator_voice_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=audiobook_dialogue,
    model_id="eleven_v3"
)

# Podcast episode intro
podcast_intro = [
    DialogueInput(
        text="Welcome back to Tech Talk! I'm Sarah.",
        voice_id="host_1_voice_id"
    ),
    DialogueInput(
        text="And I'm Mike. Today we're discussing AI.",
        voice_id="host_2_voice_id"
    ),
    DialogueInput(
        text="That's right! We have an exciting topic.",
        voice_id="host_1_voice_id"
    ),
    DialogueInput(
        text="Let's dive right in!",
        voice_id="host_2_voice_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=podcast_intro,
    model_id="eleven_turbo_v2_5"  # Fast generation
)

# Generate dialogue with timestamp data
result = client.text_to_dialogue.convert_with_timestamps(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

# Access audio data
audio_data = result.audio

# Access timestamp information
for segment in result.voice_segments:
    print(f"Voice {segment.voice_id}:")
    print(f"  Start: {segment.start_time}s")
    print(f"  End: {segment.end_time}s")
    print(f"  Text: {segment.text}")

from elevenlabs import stream

# Stream the dialogue
audio_stream = client.text_to_dialogue.stream(
    inputs=dialogue,
    model_id="eleven_turbo_v2_5"
)

# Play as it generates
stream(audio_stream)

# Or process chunks manually
for chunk in audio_stream:
    # Process each audio chunk
    pass

# Use Eleven v3 for dramatic performances
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_v3"
)

# Use Turbo for faster generation
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_turbo_v2_5"
)

# Use Multilingual v2 for best stability
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

# Specify language for better pronunciation
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    language_code="es",  # Spanish
    model_id="eleven_multilingual_v2"
)

from elevenlabs.types import ModelSettingsResponseModel

# Apply custom settings
settings = ModelSettingsResponseModel(
    stability=0.7,
    similarity_boost=0.8
)

audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    settings=settings,
    model_id="eleven_multilingual_v2"
)

from elevenlabs.types import PronunciationDictionaryVersionLocator

# Use pronunciation dictionary for technical terms
dictionaries = [
    PronunciationDictionaryVersionLocator(
        pronunciation_dictionary_id="dict_id",
        version_id="version_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    pronunciation_dictionary_locators=dictionaries
)

from elevenlabs import AsyncElevenLabs
import asyncio

async def generate_dialogue():
    client = AsyncElevenLabs(api_key="YOUR_API_KEY")
    
    dialogue = [
        {"text": "Hello there!", "voice_id": "voice_1"},
        {"text": "Hi! Nice to meet you.", "voice_id": "voice_2"}
    ]
    
    audio = await client.text_to_dialogue.convert(inputs=dialogue)
    
    chunks = []
    async for chunk in audio:
        chunks.append(chunk)
    
    return b"".join(chunks)

audio_data = asyncio.run(generate_dialogue())

# Create interactive learning content
educational_dialogue = [
    DialogueInput(
        text="Today we'll learn about photosynthesis.",
        voice_id="teacher_voice"
    ),
    DialogueInput(
        text="What is photosynthesis?",
        voice_id="student_voice"
    ),
    DialogueInput(
        text="Great question! It's how plants make food.",
        voice_id="teacher_voice"
    )
]

# Training scenarios
training_scenario = [
    DialogueInput(
        text="Thank you for calling. How can I help you?",
        voice_id="agent_voice"
    ),
    DialogueInput(
        text="I have a problem with my recent order.",
        voice_id="customer_voice"
    ),
    DialogueInput(
        text="I'm sorry to hear that. Let me help you.",
        voice_id="agent_voice"
    )
]

# Choose-your-own-adventure style content
story_dialogue = [
    DialogueInput(
        text="You find yourself at a crossroads.",
        voice_id="narrator_voice"
    ),
    DialogueInput(
        text="Which path will you take?",
        voice_id="narrator_voice"
    )
]