chore: initial public snapshot for github upload
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"""
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Elevenlabs Text-to-Speech transformation
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Maps OpenAI TTS spec to Elevenlabs TTS API
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"""
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from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
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from urllib.parse import urlencode
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import httpx
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from httpx import Headers
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import litellm
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from litellm.types.utils import all_litellm_params
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from litellm.llms.base_llm.text_to_speech.transformation import (
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BaseTextToSpeechConfig,
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TextToSpeechRequestData,
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)
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from litellm.secret_managers.main import get_secret_str
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from ..common_utils import ElevenLabsException
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if TYPE_CHECKING:
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from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
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from litellm.types.llms.openai import HttpxBinaryResponseContent
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else:
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LiteLLMLoggingObj = Any
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HttpxBinaryResponseContent = Any
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class ElevenLabsTextToSpeechConfig(BaseTextToSpeechConfig):
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"""
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Configuration for ElevenLabs Text-to-Speech
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Reference: https://elevenlabs.io/docs/api-reference/text-to-speech/convert
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"""
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TTS_BASE_URL = "https://api.elevenlabs.io"
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TTS_ENDPOINT_PATH = "/v1/text-to-speech"
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DEFAULT_OUTPUT_FORMAT = "pcm_44100"
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VOICE_MAPPINGS = {
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"alloy": "21m00Tcm4TlvDq8ikWAM", # Rachel
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"amber": "5Q0t7uMcjvnagumLfvZi", # Paul
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"ash": "AZnzlk1XvdvUeBnXmlld", # Domi
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"august": "D38z5RcWu1voky8WS1ja", # Fin
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"blue": "2EiwWnXFnvU5JabPnv8n", # Clyde
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"coral": "9BWtsMINqrJLrRacOk9x", # Aria
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"lily": "EXAVITQu4vr4xnSDxMaL", # Sarah
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"onyx": "29vD33N1CtxCmqQRPOHJ", # Drew
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"sage": "CwhRBWXzGAHq8TQ4Fs17", # Roger
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"verse": "CYw3kZ02Hs0563khs1Fj", # Dave
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}
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# Response format mappings from OpenAI to ElevenLabs
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FORMAT_MAPPINGS = {
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"mp3": "mp3_44100_128",
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"pcm": "pcm_44100",
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"opus": "opus_48000_128",
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# ElevenLabs does not support WAV, AAC, or FLAC formats.
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}
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ELEVENLABS_QUERY_PARAMS_KEY = "__elevenlabs_query_params__"
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ELEVENLABS_VOICE_ID_KEY = "__elevenlabs_voice_id__"
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def get_supported_openai_params(self, model: str) -> list:
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"""
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ElevenLabs TTS supports these OpenAI parameters
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"""
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return ["voice", "response_format", "speed"]
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def _extract_voice_id(self, voice: str) -> str:
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"""
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Normalize the provided voice information into an ElevenLabs voice_id.
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"""
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normalized_voice = voice.strip()
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mapped_voice = self.VOICE_MAPPINGS.get(normalized_voice.lower())
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return mapped_voice or normalized_voice
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def _resolve_voice_id(
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self,
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voice: Optional[Union[str, Dict[str, Any]]],
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params: Dict[str, Any],
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) -> str:
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"""
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Determine the ElevenLabs voice_id based on provided voice input or parameters.
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"""
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mapped_voice: Optional[str] = None
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if isinstance(voice, str) and voice.strip():
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mapped_voice = self._extract_voice_id(voice)
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elif isinstance(voice, dict):
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for key in ("voice_id", "id", "name"):
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candidate = voice.get(key)
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if isinstance(candidate, str) and candidate.strip():
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mapped_voice = self._extract_voice_id(candidate)
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break
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elif voice is not None:
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mapped_voice = self._extract_voice_id(str(voice))
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if mapped_voice is None:
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voice_override = params.pop("voice_id", None)
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if isinstance(voice_override, str) and voice_override.strip():
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mapped_voice = self._extract_voice_id(voice_override)
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if mapped_voice is None:
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raise ValueError(
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"ElevenLabs voice_id is required. Pass `voice` when calling `litellm.speech()`."
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)
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return mapped_voice
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def map_openai_params(
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self,
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model: str,
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optional_params: Dict,
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voice: Optional[Union[str, Dict]] = None,
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drop_params: bool = False,
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kwargs: Optional[Dict[str, Any]] = None,
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) -> Tuple[Optional[str], Dict]:
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"""
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Map OpenAI parameters to ElevenLabs TTS parameters
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"""
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mapped_params: Dict[str, Any] = {}
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query_params: Dict[str, Any] = {}
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# Work on a copy so we don't mutate the caller's dictionary
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params = dict(optional_params) if optional_params else {}
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passthrough_kwargs: Dict[str, Any] = kwargs if kwargs is not None else {}
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# Extract voice identifier
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mapped_voice = self._resolve_voice_id(voice, params)
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# Response/output format → query parameter
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response_format = params.pop("response_format", None)
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if isinstance(response_format, str):
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mapped_format = self.FORMAT_MAPPINGS.get(response_format, response_format)
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query_params["output_format"] = mapped_format
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# ElevenLabs does not support OpenAI speed directly.
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# Drop it to avoid sending unsupported keys unless caller already provided voice_settings.
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speed = params.pop("speed", None)
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if speed is not None:
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speed_value: Optional[float]
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try:
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speed_value = float(speed)
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except (TypeError, ValueError):
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speed_value = None
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if speed_value is not None:
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if isinstance(params.get("voice_settings"), dict):
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params["voice_settings"]["speed"] = speed_value # type: ignore[index]
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else:
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params["voice_settings"] = {"speed": speed_value}
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# Instructions parameter is OpenAI-specific; omit to prevent API errors.
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params.pop("instructions", None)
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self._add_elevenlabs_specific_params(
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mapped_voice=mapped_voice,
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query_params=query_params,
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mapped_params=mapped_params,
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kwargs=passthrough_kwargs,
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remaining_params=params,
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)
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return mapped_voice, mapped_params
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def validate_environment(
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self,
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headers: dict,
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model: str,
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api_key: Optional[str] = None,
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api_base: Optional[str] = None,
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) -> dict:
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"""
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Validate Azure environment and set up authentication headers
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"""
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api_key = (
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api_key
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or litellm.api_key
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or litellm.openai_key
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or get_secret_str("ELEVENLABS_API_KEY")
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)
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if api_key is None:
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raise ValueError(
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"ElevenLabs API key is required. Set ELEVENLABS_API_KEY environment variable."
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)
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headers.update(
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{
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"xi-api-key": api_key,
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"Content-Type": "application/json",
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}
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)
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return headers
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, Headers]
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) -> BaseLLMException:
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return ElevenLabsException(
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message=error_message, status_code=status_code, headers=headers
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)
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def transform_text_to_speech_request(
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self,
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model: str,
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input: str,
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voice: Optional[str],
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optional_params: Dict,
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litellm_params: Dict,
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headers: dict,
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) -> TextToSpeechRequestData:
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"""
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Build the ElevenLabs TTS request payload.
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"""
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params = dict(optional_params) if optional_params else {}
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extra_body = params.pop("extra_body", None)
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request_body: Dict[str, Any] = {
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"text": input,
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"model_id": model,
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}
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for key, value in params.items():
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if value is None:
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continue
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request_body[key] = value
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if isinstance(extra_body, dict):
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for key, value in extra_body.items():
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if value is None:
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continue
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request_body[key] = value
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return TextToSpeechRequestData(
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dict_body=request_body,
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headers={"Content-Type": "application/json"},
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)
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def _add_elevenlabs_specific_params(
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self,
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mapped_voice: str,
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query_params: Dict[str, Any],
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mapped_params: Dict[str, Any],
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kwargs: Optional[Dict[str, Any]],
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remaining_params: Dict[str, Any],
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) -> None:
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if kwargs is None:
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kwargs = {}
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for key, value in remaining_params.items():
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if value is None:
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continue
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mapped_params[key] = value
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reserved_kwarg_keys = set(all_litellm_params) | {
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self.ELEVENLABS_QUERY_PARAMS_KEY,
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self.ELEVENLABS_VOICE_ID_KEY,
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"voice",
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"model",
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"response_format",
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"output_format",
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"extra_body",
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"user",
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}
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extra_body_from_kwargs = kwargs.pop("extra_body", None)
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if isinstance(extra_body_from_kwargs, dict):
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for key, value in extra_body_from_kwargs.items():
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if value is None:
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continue
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mapped_params[key] = value
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for key in list(kwargs.keys()):
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if key in reserved_kwarg_keys:
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continue
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value = kwargs[key]
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if value is None:
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continue
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mapped_params[key] = value
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kwargs.pop(key, None)
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if query_params:
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kwargs[self.ELEVENLABS_QUERY_PARAMS_KEY] = query_params
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else:
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kwargs.pop(self.ELEVENLABS_QUERY_PARAMS_KEY, None)
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kwargs[self.ELEVENLABS_VOICE_ID_KEY] = mapped_voice
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def transform_text_to_speech_response(
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self,
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model: str,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> "HttpxBinaryResponseContent":
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"""
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Wrap ElevenLabs binary audio response.
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"""
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from litellm.types.llms.openai import HttpxBinaryResponseContent
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return HttpxBinaryResponseContent(raw_response)
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def get_complete_url(
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self,
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model: str,
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api_base: Optional[str],
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litellm_params: dict,
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) -> str:
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"""
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Construct the ElevenLabs endpoint URL, including path voice_id and query params.
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"""
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base_url = (
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api_base or get_secret_str("ELEVENLABS_API_BASE") or self.TTS_BASE_URL
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)
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base_url = base_url.rstrip("/")
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voice_id = litellm_params.get(self.ELEVENLABS_VOICE_ID_KEY)
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if not isinstance(voice_id, str) or not voice_id.strip():
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raise ValueError(
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"ElevenLabs voice_id is required. Pass `voice` when calling `litellm.speech()`."
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)
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url = f"{base_url}{self.TTS_ENDPOINT_PATH}/{voice_id}"
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query_params = litellm_params.get(self.ELEVENLABS_QUERY_PARAMS_KEY, {})
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if query_params:
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url = f"{url}?{urlencode(query_params)}"
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return url
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