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https://github.com/BerriAI/litellm.git
synced 2025-04-24 18:24:20 +00:00
fix: do not use mutable defaults in litellm/main.py
This commit is contained in:
Nilanjan De
parent
f816630f08
commit
cc769ea551
1 changed files with 18 additions and 42 deletions
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@ -313,7 +313,7 @@ class AsyncCompletions:
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async def acompletion(
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model: str,
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# Optional OpenAI params: see https://platform.openai.com/docs/api-reference/chat/create
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messages: List = [],
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messages: Optional[List] = None,
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functions: Optional[List] = None,
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function_call: Optional[str] = None,
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timeout: Optional[Union[float, int]] = None,
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@ -395,6 +395,7 @@ async def acompletion(
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- The `completion` function is called using `run_in_executor` to execute synchronously in the event loop.
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- If `stream` is True, the function returns an async generator that yields completion lines.
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"""
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messages = messages or []
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fallbacks = kwargs.get("fallbacks", None)
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mock_timeout = kwargs.get("mock_timeout", None)
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@ -530,18 +531,14 @@ def _handle_mock_potential_exceptions(
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raise litellm.MockException(
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status_code=getattr(mock_response, "status_code", 500), # type: ignore
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message=getattr(mock_response, "text", str(mock_response)),
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llm_provider=getattr(
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mock_response, "llm_provider", custom_llm_provider or "openai"
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), # type: ignore
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llm_provider=getattr(mock_response, "llm_provider", custom_llm_provider or "openai"), # type: ignore
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model=model, # type: ignore
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request=httpx.Request(method="POST", url="https://api.openai.com/v1/"),
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)
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elif isinstance(mock_response, str) and mock_response == "litellm.RateLimitError":
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raise litellm.RateLimitError(
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message="this is a mock rate limit error",
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llm_provider=getattr(
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mock_response, "llm_provider", custom_llm_provider or "openai"
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), # type: ignore
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llm_provider=getattr(mock_response, "llm_provider", custom_llm_provider or "openai"), # type: ignore
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model=model,
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)
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elif (
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@ -550,9 +547,7 @@ def _handle_mock_potential_exceptions(
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):
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raise litellm.ContextWindowExceededError(
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message="this is a mock context window exceeded error",
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llm_provider=getattr(
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mock_response, "llm_provider", custom_llm_provider or "openai"
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), # type: ignore
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llm_provider=getattr(mock_response, "llm_provider", custom_llm_provider or "openai"), # type: ignore
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model=model,
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)
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elif (
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@ -561,9 +556,7 @@ def _handle_mock_potential_exceptions(
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):
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raise litellm.InternalServerError(
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message="this is a mock internal server error",
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llm_provider=getattr(
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mock_response, "llm_provider", custom_llm_provider or "openai"
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), # type: ignore
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llm_provider=getattr(mock_response, "llm_provider", custom_llm_provider or "openai"), # type: ignore
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model=model,
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)
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elif isinstance(mock_response, str) and mock_response.startswith(
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@ -778,7 +771,7 @@ def mock_completion(
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def completion( # type: ignore # noqa: PLR0915
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model: str,
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# Optional OpenAI params: see https://platform.openai.com/docs/api-reference/chat/create
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messages: List = [],
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messages: Optional[List] = None,
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timeout: Optional[Union[float, str, httpx.Timeout]] = None,
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temperature: Optional[float] = None,
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top_p: Optional[float] = None,
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@ -863,6 +856,7 @@ def completion( # type: ignore # noqa: PLR0915
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- It supports various optional parameters for customizing the completion behavior.
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- If 'mock_response' is provided, a mock completion response is returned for testing or debugging.
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"""
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messages = messages or []
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### VALIDATE Request ###
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if model is None:
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raise ValueError("model param not passed in.")
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@ -945,7 +939,7 @@ def completion( # type: ignore # noqa: PLR0915
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prompt_variables = cast(Optional[dict], kwargs.get("prompt_variables", None))
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### COPY MESSAGES ### - related issue https://github.com/BerriAI/litellm/discussions/4489
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messages = get_completion_messages(
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messages=messages,
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messages=messages or [],
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ensure_alternating_roles=ensure_alternating_roles or False,
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user_continue_message=user_continue_message,
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assistant_continue_message=assistant_continue_message,
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@ -1206,7 +1200,7 @@ def completion( # type: ignore # noqa: PLR0915
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kwargs.pop("mock_timeout", None) # remove for any fallbacks triggered
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return mock_completion(
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model,
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messages,
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messages or [],
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stream=stream,
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n=n,
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mock_response=mock_response,
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@ -1218,7 +1212,8 @@ def completion( # type: ignore # noqa: PLR0915
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mock_timeout=mock_timeout,
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timeout=timeout,
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)
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if messages is None:
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messages = []
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if custom_llm_provider == "azure":
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# azure configs
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## check dynamic params ##
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@ -3283,7 +3278,7 @@ async def aembedding(*args, **kwargs) -> EmbeddingResponse:
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@client
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def embedding( # noqa: PLR0915
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model,
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input=[],
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input: Optional[List] = None,
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# Optional params
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dimensions: Optional[int] = None,
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encoding_format: Optional[str] = None,
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@ -3325,6 +3320,7 @@ def embedding( # noqa: PLR0915
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Raises:
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- exception_type: If an exception occurs during the API call.
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"""
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input = input or []
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azure = kwargs.get("azure", None)
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client = kwargs.pop("client", None)
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max_retries = kwargs.get("max_retries", None)
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@ -3520,12 +3516,7 @@ def embedding( # noqa: PLR0915
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api_base = api_base or litellm.api_base or get_secret("DATABRICKS_API_BASE") # type: ignore
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# set API KEY
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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.databricks_key
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or get_secret("DATABRICKS_API_KEY")
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) # type: ignore
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api_key = api_key or litellm.api_key or litellm.databricks_key or get_secret("DATABRICKS_API_KEY") # type: ignore
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## EMBEDDING CALL
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response = databricks_embedding.embedding(
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@ -3599,12 +3590,7 @@ def embedding( # noqa: PLR0915
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client=client,
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)
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elif custom_llm_provider == "huggingface":
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api_key = (
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api_key
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or litellm.huggingface_key
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or get_secret("HUGGINGFACE_API_KEY")
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or litellm.api_key
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) # type: ignore
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api_key = api_key or litellm.huggingface_key or get_secret("HUGGINGFACE_API_KEY") or litellm.api_key # type: ignore
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response = huggingface_embed.embedding(
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model=model,
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input=input,
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@ -3765,12 +3751,7 @@ def embedding( # noqa: PLR0915
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api_key=api_key,
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)
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elif custom_llm_provider == "ollama":
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api_base = (
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litellm.api_base
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or api_base
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or get_secret_str("OLLAMA_API_BASE")
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or "http://localhost:11434"
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) # type: ignore
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api_base = litellm.api_base or api_base or get_secret_str("OLLAMA_API_BASE") or "http://localhost:11434" # type: ignore
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if isinstance(input, str):
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input = [input]
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@ -5146,12 +5127,7 @@ def transcription(
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custom_llm_provider == "openai"
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or custom_llm_provider in litellm.openai_compatible_providers
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):
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api_base = (
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api_base
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or litellm.api_base
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or get_secret("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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) # type: ignore
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api_base = api_base or litellm.api_base or get_secret("OPENAI_API_BASE") or "https://api.openai.com/v1" # type: ignore
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openai.organization = (
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litellm.organization
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or get_secret("OPENAI_ORGANIZATION")
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