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https://github.com/BerriAI/litellm.git
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9b0f871129
* feat(llm_passthrough_endpoints.py): support mistral passthrough Closes https://github.com/BerriAI/litellm/issues/9051 * feat(llm_passthrough_endpoints.py): initial commit for adding vllm passthrough route * feat(vllm/common_utils.py): add new vllm model info route make it possible to use vllm passthrough route via factory function * fix(llm_passthrough_endpoints.py): add all methods to vllm passthrough route * fix: fix linting error * fix: fix linting error * fix: fix ruff check * fix(proxy/_types.py): add new passthrough routes * docs(config_settings.md): add mistral env vars to docs
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
from typing import List, Optional
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from litellm.secret_managers.main import get_secret_str
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from litellm.types.llms.openai import AllMessageValues
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from ..base_llm.base_utils import BaseLLMModelInfo
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from ..base_llm.chat.transformation import BaseLLMException
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class TopazException(BaseLLMException):
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pass
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class TopazModelInfo(BaseLLMModelInfo):
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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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messages: List[AllMessageValues],
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optional_params: dict,
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litellm_params: dict,
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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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if api_key is None:
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raise ValueError(
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"API key is required for Topaz image variations. Set via `TOPAZ_API_KEY` or `api_key=..`"
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)
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return {
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# "Content-Type": "multipart/form-data",
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"Accept": "image/jpeg",
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"X-API-Key": api_key,
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}
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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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return [
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"topaz/Standard V2",
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"topaz/Low Resolution V2",
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"topaz/CGI",
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"topaz/High Resolution V2",
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"topaz/Text Refine",
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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("TOPAZ_API_KEY")
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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 or get_secret_str("TOPAZ_API_BASE") or "https://api.topazlabs.com"
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)
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@staticmethod
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def get_base_model(model: str) -> str:
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return model
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