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97 lines
3.3 KiB
Python
97 lines
3.3 KiB
Python
"""
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This file contains common utils for anthropic calls.
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"""
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from typing import Optional, Union
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import httpx
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import litellm
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from litellm.llms.base_llm.base_utils import BaseLLMModelInfo
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from litellm.secret_managers.main import get_secret_str
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class AnthropicError(BaseLLMException):
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def __init__(
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self,
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status_code: int,
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message,
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headers: Optional[httpx.Headers] = None,
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):
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super().__init__(status_code=status_code, message=message, headers=headers)
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class AnthropicModelInfo(BaseLLMModelInfo):
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@staticmethod
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def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
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return (
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api_base
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or get_secret_str("ANTHROPIC_API_BASE")
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or "https://api.anthropic.com"
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)
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@staticmethod
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def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
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return api_key or get_secret_str("ANTHROPIC_API_KEY")
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@staticmethod
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def get_base_model(model: Optional[str] = None) -> Optional[str]:
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return model.replace("anthropic/", "") if model else None
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def get_models(
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self, api_key: Optional[str] = None, api_base: Optional[str] = None
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) -> list[str]:
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api_base = AnthropicModelInfo.get_api_base(api_base)
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api_key = AnthropicModelInfo.get_api_key(api_key)
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if api_base is None or api_key is None:
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raise ValueError(
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"ANTHROPIC_API_BASE or ANTHROPIC_API_KEY is not set. Please set the environment variable, to query Anthropic's `/models` endpoint."
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)
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response = litellm.module_level_client.get(
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url=f"{api_base}/v1/models",
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headers={"x-api-key": api_key, "anthropic-version": "2023-06-01"},
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)
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try:
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response.raise_for_status()
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except httpx.HTTPStatusError:
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raise Exception(
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f"Failed to fetch models from Anthropic. Status code: {response.status_code}, Response: {response.text}"
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)
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models = response.json()["data"]
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litellm_model_names = []
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for model in models:
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stripped_model_name = model["id"]
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litellm_model_name = "anthropic/" + stripped_model_name
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litellm_model_names.append(litellm_model_name)
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return litellm_model_names
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def process_anthropic_headers(headers: Union[httpx.Headers, dict]) -> dict:
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openai_headers = {}
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if "anthropic-ratelimit-requests-limit" in headers:
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openai_headers["x-ratelimit-limit-requests"] = headers[
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"anthropic-ratelimit-requests-limit"
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]
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if "anthropic-ratelimit-requests-remaining" in headers:
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openai_headers["x-ratelimit-remaining-requests"] = headers[
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"anthropic-ratelimit-requests-remaining"
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]
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if "anthropic-ratelimit-tokens-limit" in headers:
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openai_headers["x-ratelimit-limit-tokens"] = headers[
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"anthropic-ratelimit-tokens-limit"
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]
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if "anthropic-ratelimit-tokens-remaining" in headers:
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openai_headers["x-ratelimit-remaining-tokens"] = headers[
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"anthropic-ratelimit-tokens-remaining"
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]
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llm_response_headers = {
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"{}-{}".format("llm_provider", k): v for k, v in headers.items()
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}
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additional_headers = {**llm_response_headers, **openai_headers}
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return additional_headers
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