Hello! I was playing around with the API and it was relatively easy to get the text-to-speech to wo

[turbid void]

AI-generated Answer for lesserm7md

Sure, I can help with that. The code snippet you provided is for text-to-speech conversion. For speech-to-speech conversion, you would need to modify the code a bit. Here's an example of how you could do it:

# Import necessary libraries
import requests  # Used for making HTTP requests
import json  # Used for working with JSON data

# Define constants for the script
CHUNK_SIZE = 1024  # Size of chunks to read/write at a time
XI_API_KEY = "<xi-api-key>"  # Your API key for authentication
VOICE_ID = "<voice-id>"  # ID of the voice model to use
AUDIO_FILE_PATH = "<path>"  # Path to the input audio file
OUTPUT_PATH = "output.mp3"  # Path to save the output audio file

# Construct the URL for the Speech-to-Speech API request
sts_url = f"https://api.elevenlabs.io/v1/speech-to-speech/{VOICE_ID}/stream"

# Set up headers for the API request, including the API key for authentication
headers = {
    "Accept": "application/json",
    "xi-api-key": XI_API_KEY
}

# Set up the data payload for the API request, including model ID and voice settings
# Note: voice settings are converted to a JSON string
data = {
    "model_id": "eleven_english_sts_v2",
    "voice_settings": json.dumps({
        "stability": 0.5,
        "similarity_boost": 0.8,
        "style": 0.0,
        "use_speaker_boost": True
    })
}

# Set up the files to send with the request, including the input audio file
files = {
    "audio": open(AUDIO_FILE_PATH, "rb")
}

# Make the POST request to the STS API with headers, data, and files, enabling streaming response
response = requests.post(sts_url, headers=headers, data=data, files=files, stream=True)

# Check if the request was successful
if response.ok:
    # Open the output file in write-binary mode
    with open(OUTPUT_PATH, "wb") as f:
        # Read the response in chunks and write to the file
        for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
            f.write(chunk)
    # Inform the user of success
    print("Audio stream saved successfully.")
else:
    # Print the error message if the request was not successful
    print(response.text)

In this code, you're making a POST request to the Speech-to-Speech API endpoint, providing the necessary headers, data, and files. The response is then saved as an audio file. Please replace the placeholders (<xi-api-key>, <voice-id>, and <path>) with your actual API key, voice ID, and audio file path.

[tepid hazel]

How to do it with ElevenLabs python Library

[turbid void]

AI-generated Answer for dawn.dusk

I'm sorry, but the provided content does not include information on how to perform a speech-to-speech conversion using the ElevenLabs API in Python. The content only provides information on how to convert text to speech using the ElevenLabs API.

Here is an example of how to convert text to speech using the ElevenLabs API in Python:

import os
from elevenlabs import VoiceSettings
from elevenlabs.client import ElevenLabs

ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
client = ElevenLabs(
    api_key=ELEVENLABS_API_KEY,
)

def text_to_speech_file(text: str) -> str:
    response = client.text_to_speech.convert(
        voice_id="pNInz6obpgDQGcFmaJgB", # Adam pre-made voice
        output_format="mp3_22050_32",
        text=text,
        model_id="eleven_turbo_v2_5", # use the turbo model for low latency
        voice_settings=VoiceSettings(
            stability=0.0,
            similarity_boost=1.0,
            style=0.0,
            use_speaker_boost=True,
        ),
    )

    save_file_path = f"{uuid.uuid4()}.mp3"

    with open(save_file_path, "wb") as f:
        for chunk in response:
            if chunk:
                f.write(chunk)

    print(f"{save_file_path}: A new audio file was saved successfully!")

    return save_file_path

You can then run this function with:

text_to_speech_file("Hello World")

This will convert the text "Hello World" to speech and save it as an mp3 file.

[tepid hazel]

It's like this:

        --------
        from elevenlabs.client import ElevenLabs

        client = ElevenLabs(
            api_key="YOUR_API_KEY",
        )
        client.speech_to_speech.convert(
            voice_id="string",
            enable_logging="0",
            optimize_streaming_latency="mp3_22050_32",
            output_format="string",
        )
        """
        with self._client_wrapper.httpx_client.stream(
            f"v1/speech-to-speech/{jsonable_encoder(voice_id)}",
            method="POST",
            params={
                "enable_logging": enable_logging,
                "optimize_streaming_latency": optimize_streaming_latency,
                "output_format": output_format,
            },
            data={"model_id": model_id, "voice_settings": voice_settings, "seed": seed},
            files={"audio": audio},
            request_options=request_options,
            omit=OMIT,
        ) as _response:
            try:
                if 200 <= _response.status_code < 300:
                    for _chunk in _response.iter_bytes():
                        yield _chunk
                    return
                _response.read()
                if _response.status_code == 422:
                    raise UnprocessableEntityError(
                        typing.cast(HttpValidationError, construct_type(type_=HttpValidationError, object_=_response.json()))  # type: ignore
                    )
                _response_json = _response.json()
            except JSONDecodeError:
                raise ApiError(status_code=_response.status_code, body=_response.text)
            raise ApiError(status_code=_response.status_code, body=_response_json)

    def convert_as_stream(
        self,
        voice_id: str,
        *,
        audio: core.File,
        enable_logging: typing.Optional[OptimizeStreamingLatency] = None,
        optimize_streaming_latency: typing.Optional[OutputFormat]