Text-to-Speech

from together import Together

client = Together()

speech_file_path = "speech.mp3"

response = client.audio.speech.create(
    model="canopylabs/orpheus-3b-0.1-ft",
    input="Today is a wonderful day to build something people love!",
    voice="tara",
    response_format="mp3",
)

response.stream_to_file(speech_file_path)

from together import Together

client = Together()

response = client.audio.speech.create(
    model="canopylabs/orpheus-3b-0.1-ft",
    input="The quick brown fox jumps over the lazy dog",
    voice="tara",
    stream=True,
    response_format="raw",  # Required for streaming
    response_encoding="pcm_s16le",  # 16-bit PCM for clean audio
)

# Save the streamed audio to a file
response.stream_to_file("speech_streaming.wav", response_format="wav")

import asyncio
import websockets
import json
import base64
import os


async def generate_speech():
    api_key = os.environ.get("TOGETHER_API_KEY")
    url = "wss://api.together.ai/v1/audio/speech/websocket?model=hexgrad/Kokoro-82M&voice=af_alloy"

    headers = {"Authorization": f"Bearer {api_key}"}

    async with websockets.connect(url, additional_headers=headers) as ws:
        # Wait for session created
        session_msg = await ws.recv()
        session_data = json.loads(session_msg)
        print(f"Session created: {session_data['session']['id']}")

        # Send text for TTS
        text_chunks = [
            "Hello, this is a test.",
            "This is the second sentence.",
            "And this is the final one.",
        ]

        async def send_text():
            for chunk in text_chunks:
                await ws.send(
                    json.dumps(
                        {"type": "input_text_buffer.append", "text": chunk}
                    )
                )
                await asyncio.sleep(0.5)  # Simulate typing

            # Commit to process any remaining text
            await ws.send(json.dumps({"type": "input_text_buffer.commit"}))

        async def receive_audio():
            audio_data = bytearray()
            async for message in ws:
                data = json.loads(message)

                if data["type"] == "conversation.item.input_text.received":
                    print(f"Text received: {data['text']}")
                elif data["type"] == "conversation.item.audio_output.delta":
                    # Decode base64 audio chunk
                    audio_chunk = base64.b64decode(data["delta"])
                    audio_data.extend(audio_chunk)
                    print(f"Received audio chunk for item {data['item_id']}")
                elif data["type"] == "conversation.item.audio_output.done":
                    print(
                        f"Audio generation complete for item {data['item_id']}"
                    )
                elif data["type"] == "conversation.item.tts.failed":
                    error = data.get("error", {})
                    print(f"Error: {error.get('message')}")
                    break

            # Save the audio to a file
            with open("output.wav", "wb") as f:
                f.write(audio_data)
            print("Audio saved to output.wav")

        # Run send and receive concurrently
        await asyncio.gather(send_text(), receive_audio())


asyncio.run(generate_speech())

import requests
import os

url = "https://api.together.xyz/v1/audio/speech"
api_key = os.environ.get("TOGETHER_API_KEY")

headers = {"Authorization": f"Bearer {api_key}"}

data = {
    "input": "This is a test of raw PCM audio output.",
    "voice": "tara",
    "response_format": "raw",
    "response_encoding": "pcm_f32le",
    "sample_rate": 44100,
    "stream": False,
    "model": "canopylabs/orpheus-3b-0.1-ft",
}

response = requests.post(url, headers=headers, json=data)

with open("output_raw.pcm", "wb") as f:
    f.write(response.content)

print(f"✅ Raw PCM audio saved to output_raw.pcm")
print(f"   Size: {len(response.content)} bytes")

from together import Together

client = Together()

# List all available voices
response = client.audio.voices.list()

for model_voices in response.data:
    print(f"Model: {model_voices.model}")
    for voice in model_voices.voices:
        print(f"  - Voice: {voice['name']}")