litellm/litellm/rust_bridge/_native.pyi
2026-09-16 17:50:11 +00:00

113 lines
3.4 KiB
Python

from asyncio import Future
from collections.abc import Coroutine, Mapping
import httpx
from litellm.llms.base_llm.ocr.transformation import OCRResponse
class RustBridgeDeclined(Exception): ...
class RustUpstreamError(Exception): ...
def ocr(
model: str,
document: Mapping[str, object],
api_key: str | None = ...,
api_base: str | None = ...,
timeout: float | httpx.Timeout | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: dict[str, object] | None = ...,
**kwargs: object,
) -> OCRResponse: ...
def aocr(
model: str,
document: Mapping[str, object],
api_key: str | None = ...,
api_base: str | None = ...,
timeout: float | httpx.Timeout | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: dict[str, object] | None = ...,
**kwargs: object,
) -> Coroutine[object, object, OCRResponse]: ...
def transcription(
model: str,
audio: object,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
optional_params: object = ...,
timeout_seconds: float | None = ...,
) -> dict[str, object]: ...
def atranscription(
model: str,
audio: object,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
optional_params: object = ...,
timeout_seconds: float | None = ...,
) -> Future[dict[str, object]]: ...
def messages(
model: str,
body: object,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
timeout_seconds: float | None = ...,
) -> dict[str, object]: ...
def amessages(
model: str,
body: object,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
timeout_seconds: float | None = ...,
) -> Future[dict[str, object]]: ...
def chat_completions(
model: str,
messages: object,
optional_params: object = ...,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
timeout_seconds: float | None = ...,
) -> dict[str, object]: ...
def achat_completions(
model: str,
messages: object,
optional_params: object = ...,
api_key: str | None = ...,
api_base: str | None = ...,
custom_llm_provider: str | None = ...,
extra_headers: object = ...,
timeout_seconds: float | None = ...,
) -> Future[dict[str, object]]: ...
def chat_completions_decline(
model: str,
messages: object,
optional_params: object = ...,
custom_llm_provider: str | None = ...,
) -> str | None: ...
class ResponsesWebSocketConnection:
@classmethod
def connect(
cls, url: str, headers: object = ..., timeout_seconds: float | None = ...
) -> Future[ResponsesWebSocketConnection]: ...
def send_text(self, text: str) -> Future[None]: ...
def recv_text(self) -> Future[str | None]: ...
def close(self) -> Future[None]: ...
class TokenCounter:
def __init__(self, tokenizer_json: str) -> None: ...
@staticmethod
def from_cl100k_ranks(rank_file: str) -> TokenCounter: ...
@staticmethod
def from_o200k_ranks(rank_file: str) -> TokenCounter: ...
def acount_request(self, body: bytes) -> Future[dict[str, object]]: ...
def gil_stats() -> dict[str, int]: ...