mirror of
https://github.com/BerriAI/litellm.git
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Refactor ProviderConfigManager.get_provider_chat_config for O(1) performance
Replace O(n) if-else chain with O(1) dictionary lookup to eliminate performance bottleneck identified through line profiling. Changes: - Replace 200+ line if-else chain with dictionary-based lookup - Store factory functions with boolean flag for model parameter requirement - Eliminate expensive inspect.signature() calls at runtime (63.2% overhead removed) - Extract complex provider logic into helper methods: * _get_azure_config() - handles Azure model-specific logic * _get_azure_ai_config() - handles Azure AI model checks * _get_vertex_ai_config() - handles Vertex AI model routing * _get_bedrock_config() - delegates to bedrock utility * _get_cohere_config() - handles Cohere route determination * _get_langgraph_config() - handles LangGraph import Performance improvements: - O(1) dictionary lookup vs O(n) linear search - No runtime introspection overhead (inspect.signature removed) - Faster provider resolution, especially for common providers Maintains: - All special case handling (JSON providers, OpenAI O-series/GPT-5 models) - Exact same functionality and behavior - Backward compatibility Based on profiling data showing get_provider_chat_config as bottleneck with 63.2% time spent in inspect.signature() calls.
This commit is contained in:
Alexsander Hamir
parent
10ec499369
commit
08edc900df
1 changed files with 191 additions and 237 deletions
428
litellm/utils.py
428
litellm/utils.py
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@ -7410,15 +7410,184 @@ def validate_chat_completion_tool_choice(
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class ProviderConfigManager:
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# Dictionary mapping for O(1) provider lookup
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# Stores tuples of (factory_function, needs_model_parameter)
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# This is initialized lazily on first access to avoid circular imports
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_PROVIDER_CONFIG_MAP: Optional[dict[LlmProviders, tuple[Callable, bool]]] = None
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@staticmethod
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def _build_provider_config_map() -> dict[LlmProviders, tuple[Callable, bool]]:
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"""Build the provider-to-config mapping dictionary.
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Returns a dict mapping provider to (factory_function, needs_model_parameter).
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This avoids expensive inspect.signature() calls at runtime.
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"""
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return {
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# Most common providers first for readability
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# Format: (factory_function, needs_model_parameter: bool)
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LlmProviders.OPENAI: (lambda: litellm.OpenAIGPTConfig(), False),
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LlmProviders.ANTHROPIC: (lambda: litellm.AnthropicConfig(), False),
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LlmProviders.AZURE: (lambda model: ProviderConfigManager._get_azure_config(model), True),
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LlmProviders.AZURE_AI: (lambda model: ProviderConfigManager._get_azure_ai_config(model), True),
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LlmProviders.VERTEX_AI: (lambda model: ProviderConfigManager._get_vertex_ai_config(model), True),
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LlmProviders.BEDROCK: (lambda model: ProviderConfigManager._get_bedrock_config(model), True),
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LlmProviders.COHERE: (lambda model: ProviderConfigManager._get_cohere_config(model), True),
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LlmProviders.COHERE_CHAT: (lambda model: ProviderConfigManager._get_cohere_config(model), True),
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# Simple provider mappings (no model parameter needed)
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LlmProviders.DEEPSEEK: (lambda: litellm.DeepSeekChatConfig(), False),
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LlmProviders.GROQ: (lambda: litellm.GroqChatConfig(), False),
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LlmProviders.BYTEZ: (lambda: litellm.BytezChatConfig(), False),
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LlmProviders.DATABRICKS: (lambda: litellm.DatabricksConfig(), False),
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LlmProviders.XAI: (lambda: litellm.XAIChatConfig(), False),
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LlmProviders.ZAI: (lambda: litellm.ZAIChatConfig(), False),
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LlmProviders.LAMBDA_AI: (lambda: litellm.LambdaAIChatConfig(), False),
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LlmProviders.LLAMA: (lambda: litellm.LlamaAPIConfig(), False),
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LlmProviders.TEXT_COMPLETION_OPENAI: (lambda: litellm.OpenAITextCompletionConfig(), False),
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LlmProviders.SNOWFLAKE: (lambda: litellm.SnowflakeConfig(), False),
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LlmProviders.CLARIFAI: (lambda: litellm.ClarifaiConfig(), False),
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LlmProviders.ANTHROPIC_TEXT: (lambda: litellm.AnthropicTextConfig(), False),
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LlmProviders.VERTEX_AI_BETA: (lambda: litellm.VertexGeminiConfig(), False),
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LlmProviders.CLOUDFLARE: (lambda: litellm.CloudflareChatConfig(), False),
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LlmProviders.SAGEMAKER_CHAT: (lambda: litellm.SagemakerChatConfig(), False),
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LlmProviders.SAGEMAKER: (lambda: litellm.SagemakerConfig(), False),
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LlmProviders.FIREWORKS_AI: (lambda: litellm.FireworksAIConfig(), False),
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LlmProviders.FRIENDLIAI: (lambda: litellm.FriendliaiChatConfig(), False),
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LlmProviders.WATSONX: (lambda: litellm.IBMWatsonXChatConfig(), False),
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LlmProviders.WATSONX_TEXT: (lambda: litellm.IBMWatsonXAIConfig(), False),
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LlmProviders.EMPOWER: (lambda: litellm.EmpowerChatConfig(), False),
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LlmProviders.MINIMAX: (lambda: litellm.MinimaxChatConfig(), False),
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LlmProviders.GITHUB: (lambda: litellm.GithubChatConfig(), False),
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LlmProviders.COMPACTIFAI: (lambda: litellm.CompactifAIChatConfig(), False),
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LlmProviders.GITHUB_COPILOT: (lambda: litellm.GithubCopilotConfig(), False),
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LlmProviders.GIGACHAT: (lambda: litellm.GigaChatConfig(), False),
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LlmProviders.RAGFLOW: (lambda: litellm.RAGFlowConfig(), False),
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LlmProviders.CUSTOM: (lambda: litellm.OpenAILikeChatConfig(), False),
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LlmProviders.CUSTOM_OPENAI: (lambda: litellm.OpenAILikeChatConfig(), False),
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LlmProviders.OPENAI_LIKE: (lambda: litellm.OpenAILikeChatConfig(), False),
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LlmProviders.AIOHTTP_OPENAI: (lambda: litellm.AiohttpOpenAIChatConfig(), False),
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LlmProviders.HOSTED_VLLM: (lambda: litellm.HostedVLLMChatConfig(), False),
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LlmProviders.LLAMAFILE: (lambda: litellm.LlamafileChatConfig(), False),
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LlmProviders.LM_STUDIO: (lambda: litellm.LMStudioChatConfig(), False),
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LlmProviders.GALADRIEL: (lambda: litellm.GaladrielChatConfig(), False),
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LlmProviders.REPLICATE: (lambda: litellm.ReplicateConfig(), False),
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LlmProviders.HUGGINGFACE: (lambda: litellm.HuggingFaceChatConfig(), False),
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LlmProviders.TOGETHER_AI: (lambda: litellm.TogetherAIConfig(), False),
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LlmProviders.OPENROUTER: (lambda: litellm.OpenrouterConfig(), False),
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LlmProviders.VERCEL_AI_GATEWAY: (lambda: litellm.VercelAIGatewayConfig(), False),
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LlmProviders.COMETAPI: (lambda: litellm.CometAPIConfig(), False),
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LlmProviders.DATAROBOT: (lambda: litellm.DataRobotConfig(), False),
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LlmProviders.GEMINI: (lambda: litellm.GoogleAIStudioGeminiConfig(), False),
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LlmProviders.AI21: (lambda: litellm.AI21ChatConfig(), False),
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LlmProviders.AI21_CHAT: (lambda: litellm.AI21ChatConfig(), False),
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LlmProviders.AZURE_TEXT: (lambda: litellm.AzureOpenAITextConfig(), False),
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LlmProviders.NLP_CLOUD: (lambda: litellm.NLPCloudConfig(), False),
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LlmProviders.OOBABOOGA: (lambda: litellm.OobaboogaConfig(), False),
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LlmProviders.OLLAMA_CHAT: (lambda: litellm.OllamaChatConfig(), False),
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LlmProviders.DEEPINFRA: (lambda: litellm.DeepInfraConfig(), False),
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LlmProviders.PERPLEXITY: (lambda: litellm.PerplexityChatConfig(), False),
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LlmProviders.MISTRAL: (lambda: litellm.MistralConfig(), False),
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LlmProviders.CODESTRAL: (lambda: litellm.MistralConfig(), False),
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LlmProviders.NVIDIA_NIM: (lambda: litellm.NvidiaNimConfig(), False),
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LlmProviders.CEREBRAS: (lambda: litellm.CerebrasConfig(), False),
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LlmProviders.BASETEN: (lambda: litellm.BasetenConfig(), False),
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LlmProviders.VOLCENGINE: (lambda: litellm.VolcEngineConfig(), False),
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LlmProviders.TEXT_COMPLETION_CODESTRAL: (lambda: litellm.CodestralTextCompletionConfig(), False),
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LlmProviders.SAMBANOVA: (lambda: litellm.SambanovaConfig(), False),
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LlmProviders.MARITALK: (lambda: litellm.MaritalkConfig(), False),
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LlmProviders.VLLM: (lambda: litellm.VLLMConfig(), False),
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LlmProviders.OLLAMA: (lambda: litellm.OllamaConfig(), False),
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LlmProviders.PREDIBASE: (lambda: litellm.PredibaseConfig(), False),
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LlmProviders.TRITON: (lambda: litellm.TritonConfig(), False),
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LlmProviders.PETALS: (lambda: litellm.PetalsConfig(), False),
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LlmProviders.SAP_GENERATIVE_AI_HUB: (lambda: litellm.GenAIHubOrchestrationConfig(), False),
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LlmProviders.FEATHERLESS_AI: (lambda: litellm.FeatherlessAIConfig(), False),
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LlmProviders.NOVITA: (lambda: litellm.NovitaConfig(), False),
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LlmProviders.NEBIUS: (lambda: litellm.NebiusConfig(), False),
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LlmProviders.WANDB: (lambda: litellm.WandbConfig(), False),
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LlmProviders.DASHSCOPE: (lambda: litellm.DashScopeChatConfig(), False),
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LlmProviders.MOONSHOT: (lambda: litellm.MoonshotChatConfig(), False),
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LlmProviders.DOCKER_MODEL_RUNNER: (lambda: litellm.DockerModelRunnerChatConfig(), False),
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LlmProviders.V0: (lambda: litellm.V0ChatConfig(), False),
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LlmProviders.MORPH: (lambda: litellm.MorphChatConfig(), False),
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LlmProviders.LITELLM_PROXY: (lambda: litellm.LiteLLMProxyChatConfig(), False),
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LlmProviders.GRADIENT_AI: (lambda: litellm.GradientAIConfig(), False),
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LlmProviders.NSCALE: (lambda: litellm.NscaleConfig(), False),
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LlmProviders.HEROKU: (lambda: litellm.HerokuChatConfig(), False),
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LlmProviders.OCI: (lambda: litellm.OCIChatConfig(), False),
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LlmProviders.HYPERBOLIC: (lambda: litellm.HyperbolicChatConfig(), False),
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LlmProviders.OVHCLOUD: (lambda: litellm.OVHCloudChatConfig(), False),
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LlmProviders.AMAZON_NOVA: (lambda: litellm.AmazonNovaChatConfig(), False),
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LlmProviders.LANGGRAPH: (lambda: ProviderConfigManager._get_langgraph_config(), False),
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}
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@staticmethod
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def _get_azure_config(model: str) -> BaseConfig:
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"""Get Azure config based on model type."""
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if litellm.AzureOpenAIO1Config().is_o_series_model(model=model):
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return litellm.AzureOpenAIO1Config()
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if litellm.AzureOpenAIGPT5Config.is_model_gpt_5_model(model=model):
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return litellm.AzureOpenAIGPT5Config()
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return litellm.AzureOpenAIConfig()
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@staticmethod
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def _get_azure_ai_config(model: str) -> BaseConfig:
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"""Get Azure AI config based on model type."""
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if "claude" in model.lower():
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return litellm.AzureAnthropicConfig()
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return litellm.AzureAIStudioConfig()
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@staticmethod
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def _get_vertex_ai_config(model: str) -> BaseConfig:
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"""Get Vertex AI config based on model type."""
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if "gemini" in model:
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return litellm.VertexGeminiConfig()
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elif "claude" in model:
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return litellm.VertexAIAnthropicConfig()
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elif "gpt-oss" in model:
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from litellm.llms.vertex_ai.vertex_ai_partner_models.gpt_oss.transformation import (
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VertexAIGPTOSSTransformation,
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)
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return VertexAIGPTOSSTransformation()
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elif model in litellm.vertex_mistral_models:
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if "codestral" in model:
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return litellm.CodestralTextCompletionConfig()
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return litellm.MistralConfig()
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elif model in litellm.vertex_ai_ai21_models:
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return litellm.VertexAIAi21Config()
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else:
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return litellm.VertexAILlama3Config()
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@staticmethod
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def _get_bedrock_config(model: str) -> BaseConfig:
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"""Get Bedrock config based on model."""
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from litellm.llms.bedrock.common_utils import get_bedrock_chat_config
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return get_bedrock_chat_config(model=model)
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@staticmethod
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def _get_cohere_config(model: str) -> BaseConfig:
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"""Get Cohere config based on route."""
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CohereModelInfo = getattr(sys.modules[__name__], 'CohereModelInfo')
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route = CohereModelInfo.get_cohere_route(model)
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if route == "v2":
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return litellm.CohereV2ChatConfig()
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return litellm.CohereChatConfig()
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@staticmethod
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def _get_langgraph_config() -> BaseConfig:
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"""Get LangGraph config."""
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from litellm.llms.langgraph.chat.transformation import LangGraphConfig
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return LangGraphConfig()
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@staticmethod
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def get_provider_chat_config( # noqa: PLR0915
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model: str, provider: LlmProviders
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) -> Optional[BaseConfig]:
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"""
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Returns the provider config for a given provider.
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Uses O(1) dictionary lookup for fast provider resolution.
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"""
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# Check JSON providers FIRST
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# Check JSON providers FIRST (these override standard mappings)
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from litellm.llms.openai_like.dynamic_config import create_config_class
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from litellm.llms.openai_like.json_loader import JSONProviderRegistry
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@ -7428,244 +7597,29 @@ class ProviderConfigManager:
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raise ValueError(f"Provider {provider.value} not found")
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return create_config_class(provider_config)()
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if (
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provider == LlmProviders.OPENAI
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and litellm.openaiOSeriesConfig.is_model_o_series_model(model=model)
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):
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return litellm.openaiOSeriesConfig
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elif (
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provider == LlmProviders.OPENAI
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and litellm.OpenAIGPT5Config.is_model_gpt_5_model(model=model)
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):
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return litellm.OpenAIGPT5Config()
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elif litellm.LlmProviders.DEEPSEEK == provider:
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return litellm.DeepSeekChatConfig()
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elif litellm.LlmProviders.GROQ == provider:
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return litellm.GroqChatConfig()
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elif litellm.LlmProviders.BYTEZ == provider:
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return litellm.BytezChatConfig()
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elif litellm.LlmProviders.DATABRICKS == provider:
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return litellm.DatabricksConfig()
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elif litellm.LlmProviders.XAI == provider:
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return litellm.XAIChatConfig()
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elif litellm.LlmProviders.ZAI == provider:
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return litellm.ZAIChatConfig()
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elif litellm.LlmProviders.LAMBDA_AI == provider:
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return litellm.LambdaAIChatConfig()
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elif litellm.LlmProviders.LLAMA == provider:
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return litellm.LlamaAPIConfig()
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elif litellm.LlmProviders.TEXT_COMPLETION_OPENAI == provider:
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return litellm.OpenAITextCompletionConfig()
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elif (
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litellm.LlmProviders.COHERE_CHAT == provider
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or litellm.LlmProviders.COHERE == provider
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):
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CohereModelInfo = getattr(sys.modules[__name__], 'CohereModelInfo')
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route = CohereModelInfo.get_cohere_route(model)
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if route == "v2":
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return litellm.CohereV2ChatConfig()
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else:
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# Handle OpenAI special cases (O-series and GPT-5 models)
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if provider == LlmProviders.OPENAI:
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if litellm.openaiOSeriesConfig.is_model_o_series_model(model=model):
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return litellm.openaiOSeriesConfig
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if litellm.OpenAIGPT5Config.is_model_gpt_5_model(model=model):
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return litellm.OpenAIGPT5Config()
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return litellm.CohereChatConfig()
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elif litellm.LlmProviders.SNOWFLAKE == provider:
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return litellm.SnowflakeConfig()
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elif litellm.LlmProviders.CLARIFAI == provider:
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return litellm.ClarifaiConfig()
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elif litellm.LlmProviders.ANTHROPIC == provider:
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return litellm.AnthropicConfig()
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elif litellm.LlmProviders.ANTHROPIC_TEXT == provider:
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return litellm.AnthropicTextConfig()
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elif litellm.LlmProviders.VERTEX_AI_BETA == provider:
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return litellm.VertexGeminiConfig()
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elif litellm.LlmProviders.VERTEX_AI == provider:
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if "gemini" in model:
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return litellm.VertexGeminiConfig()
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elif "claude" in model:
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return litellm.VertexAIAnthropicConfig()
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elif "gpt-oss" in model:
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from litellm.llms.vertex_ai.vertex_ai_partner_models.gpt_oss.transformation import (
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VertexAIGPTOSSTransformation,
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)
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# Initialize provider config map lazily (avoids circular imports)
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if ProviderConfigManager._PROVIDER_CONFIG_MAP is None:
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ProviderConfigManager._PROVIDER_CONFIG_MAP = ProviderConfigManager._build_provider_config_map()
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return VertexAIGPTOSSTransformation()
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elif model in litellm.vertex_mistral_models:
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if "codestral" in model:
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return litellm.CodestralTextCompletionConfig()
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else:
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return litellm.MistralConfig()
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elif model in litellm.vertex_ai_ai21_models:
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return litellm.VertexAIAi21Config()
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else: # use generic openai-like param mapping
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return litellm.VertexAILlama3Config()
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elif litellm.LlmProviders.CLOUDFLARE == provider:
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return litellm.CloudflareChatConfig()
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elif litellm.LlmProviders.SAGEMAKER_CHAT == provider:
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return litellm.SagemakerChatConfig()
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elif litellm.LlmProviders.SAGEMAKER == provider:
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return litellm.SagemakerConfig()
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elif litellm.LlmProviders.FIREWORKS_AI == provider:
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return litellm.FireworksAIConfig()
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elif litellm.LlmProviders.FRIENDLIAI == provider:
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return litellm.FriendliaiChatConfig()
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elif litellm.LlmProviders.WATSONX == provider:
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return litellm.IBMWatsonXChatConfig()
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elif litellm.LlmProviders.WATSONX_TEXT == provider:
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return litellm.IBMWatsonXAIConfig()
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elif litellm.LlmProviders.EMPOWER == provider:
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return litellm.EmpowerChatConfig()
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elif litellm.LlmProviders.MINIMAX == provider:
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return litellm.MinimaxChatConfig()
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elif litellm.LlmProviders.GITHUB == provider:
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return litellm.GithubChatConfig()
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elif litellm.LlmProviders.COMPACTIFAI == provider:
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return litellm.CompactifAIChatConfig()
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elif litellm.LlmProviders.GITHUB_COPILOT == provider:
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return litellm.GithubCopilotConfig()
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elif litellm.LlmProviders.GIGACHAT == provider:
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return litellm.GigaChatConfig()
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elif litellm.LlmProviders.RAGFLOW == provider:
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return litellm.RAGFlowConfig()
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elif (
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litellm.LlmProviders.CUSTOM == provider
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or litellm.LlmProviders.CUSTOM_OPENAI == provider
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or litellm.LlmProviders.OPENAI_LIKE == provider
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):
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return litellm.OpenAILikeChatConfig()
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elif litellm.LlmProviders.AIOHTTP_OPENAI == provider:
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return litellm.AiohttpOpenAIChatConfig()
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elif litellm.LlmProviders.HOSTED_VLLM == provider:
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return litellm.HostedVLLMChatConfig()
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elif litellm.LlmProviders.LLAMAFILE == provider:
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return litellm.LlamafileChatConfig()
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elif litellm.LlmProviders.LM_STUDIO == provider:
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return litellm.LMStudioChatConfig()
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elif litellm.LlmProviders.GALADRIEL == provider:
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return litellm.GaladrielChatConfig()
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elif litellm.LlmProviders.REPLICATE == provider:
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return litellm.ReplicateConfig()
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elif litellm.LlmProviders.HUGGINGFACE == provider:
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||||
return litellm.HuggingFaceChatConfig()
|
||||
elif litellm.LlmProviders.TOGETHER_AI == provider:
|
||||
return litellm.TogetherAIConfig()
|
||||
elif litellm.LlmProviders.OPENROUTER == provider:
|
||||
return litellm.OpenrouterConfig()
|
||||
elif litellm.LlmProviders.VERCEL_AI_GATEWAY == provider:
|
||||
return litellm.VercelAIGatewayConfig()
|
||||
elif litellm.LlmProviders.COMETAPI == provider:
|
||||
return litellm.CometAPIConfig()
|
||||
elif litellm.LlmProviders.DATAROBOT == provider:
|
||||
return litellm.DataRobotConfig()
|
||||
elif litellm.LlmProviders.GEMINI == provider:
|
||||
return litellm.GoogleAIStudioGeminiConfig()
|
||||
elif (
|
||||
litellm.LlmProviders.AI21 == provider
|
||||
or litellm.LlmProviders.AI21_CHAT == provider
|
||||
):
|
||||
return litellm.AI21ChatConfig()
|
||||
elif litellm.LlmProviders.AZURE == provider:
|
||||
if litellm.AzureOpenAIO1Config().is_o_series_model(model=model):
|
||||
return litellm.AzureOpenAIO1Config()
|
||||
if litellm.AzureOpenAIGPT5Config.is_model_gpt_5_model(model=model):
|
||||
return litellm.AzureOpenAIGPT5Config()
|
||||
return litellm.AzureOpenAIConfig()
|
||||
elif litellm.LlmProviders.AZURE_AI == provider:
|
||||
if "claude" in model.lower():
|
||||
return litellm.AzureAnthropicConfig()
|
||||
return litellm.AzureAIStudioConfig()
|
||||
elif litellm.LlmProviders.AZURE_TEXT == provider:
|
||||
return litellm.AzureOpenAITextConfig()
|
||||
elif litellm.LlmProviders.HOSTED_VLLM == provider:
|
||||
return litellm.HostedVLLMChatConfig()
|
||||
elif litellm.LlmProviders.NLP_CLOUD == provider:
|
||||
return litellm.NLPCloudConfig()
|
||||
elif litellm.LlmProviders.OOBABOOGA == provider:
|
||||
return litellm.OobaboogaConfig()
|
||||
elif litellm.LlmProviders.OLLAMA_CHAT == provider:
|
||||
return litellm.OllamaChatConfig()
|
||||
elif litellm.LlmProviders.DEEPINFRA == provider:
|
||||
return litellm.DeepInfraConfig()
|
||||
elif litellm.LlmProviders.PERPLEXITY == provider:
|
||||
return litellm.PerplexityChatConfig()
|
||||
elif (
|
||||
litellm.LlmProviders.MISTRAL == provider
|
||||
or litellm.LlmProviders.CODESTRAL == provider
|
||||
):
|
||||
return litellm.MistralConfig()
|
||||
elif litellm.LlmProviders.NVIDIA_NIM == provider:
|
||||
return litellm.NvidiaNimConfig()
|
||||
elif litellm.LlmProviders.CEREBRAS == provider:
|
||||
return litellm.CerebrasConfig()
|
||||
elif litellm.LlmProviders.BASETEN == provider:
|
||||
return litellm.BasetenConfig()
|
||||
elif litellm.LlmProviders.VOLCENGINE == provider:
|
||||
return litellm.VolcEngineConfig()
|
||||
elif litellm.LlmProviders.TEXT_COMPLETION_CODESTRAL == provider:
|
||||
return litellm.CodestralTextCompletionConfig()
|
||||
elif litellm.LlmProviders.SAMBANOVA == provider:
|
||||
return litellm.SambanovaConfig()
|
||||
elif litellm.LlmProviders.MARITALK == provider:
|
||||
return litellm.MaritalkConfig()
|
||||
elif litellm.LlmProviders.CLOUDFLARE == provider:
|
||||
return litellm.CloudflareChatConfig()
|
||||
elif litellm.LlmProviders.ANTHROPIC_TEXT == provider:
|
||||
return litellm.AnthropicTextConfig()
|
||||
elif litellm.LlmProviders.VLLM == provider:
|
||||
return litellm.VLLMConfig()
|
||||
elif litellm.LlmProviders.OLLAMA == provider:
|
||||
return litellm.OllamaConfig()
|
||||
elif litellm.LlmProviders.PREDIBASE == provider:
|
||||
return litellm.PredibaseConfig()
|
||||
elif litellm.LlmProviders.TRITON == provider:
|
||||
return litellm.TritonConfig()
|
||||
elif litellm.LlmProviders.PETALS == provider:
|
||||
return litellm.PetalsConfig()
|
||||
elif litellm.LlmProviders.SAP_GENERATIVE_AI_HUB == provider:
|
||||
return litellm.GenAIHubOrchestrationConfig()
|
||||
elif litellm.LlmProviders.FEATHERLESS_AI == provider:
|
||||
return litellm.FeatherlessAIConfig()
|
||||
elif litellm.LlmProviders.NOVITA == provider:
|
||||
return litellm.NovitaConfig()
|
||||
elif litellm.LlmProviders.NEBIUS == provider:
|
||||
return litellm.NebiusConfig()
|
||||
elif litellm.LlmProviders.WANDB == provider:
|
||||
return litellm.WandbConfig()
|
||||
elif litellm.LlmProviders.DASHSCOPE == provider:
|
||||
return litellm.DashScopeChatConfig()
|
||||
elif litellm.LlmProviders.MOONSHOT == provider:
|
||||
return litellm.MoonshotChatConfig()
|
||||
elif litellm.LlmProviders.DOCKER_MODEL_RUNNER == provider:
|
||||
return litellm.DockerModelRunnerChatConfig()
|
||||
elif litellm.LlmProviders.V0 == provider:
|
||||
return litellm.V0ChatConfig()
|
||||
elif litellm.LlmProviders.MORPH == provider:
|
||||
return litellm.MorphChatConfig()
|
||||
elif litellm.LlmProviders.BEDROCK == provider:
|
||||
from litellm.llms.bedrock.common_utils import get_bedrock_chat_config
|
||||
# O(1) dictionary lookup
|
||||
config_entry = ProviderConfigManager._PROVIDER_CONFIG_MAP.get(provider)
|
||||
if config_entry is None:
|
||||
return None
|
||||
|
||||
return get_bedrock_chat_config(model=model)
|
||||
elif litellm.LlmProviders.LITELLM_PROXY == provider:
|
||||
return litellm.LiteLLMProxyChatConfig()
|
||||
elif litellm.LlmProviders.OPENAI == provider:
|
||||
return litellm.OpenAIGPTConfig()
|
||||
elif litellm.LlmProviders.GRADIENT_AI == provider:
|
||||
return litellm.GradientAIConfig()
|
||||
elif litellm.LlmProviders.NSCALE == provider:
|
||||
return litellm.NscaleConfig()
|
||||
elif litellm.LlmProviders.HEROKU == provider:
|
||||
return litellm.HerokuChatConfig()
|
||||
elif litellm.LlmProviders.OCI == provider:
|
||||
return litellm.OCIChatConfig()
|
||||
elif litellm.LlmProviders.HYPERBOLIC == provider:
|
||||
return litellm.HyperbolicChatConfig()
|
||||
elif litellm.LlmProviders.OVHCLOUD == provider:
|
||||
return litellm.OVHCloudChatConfig()
|
||||
elif litellm.LlmProviders.AMAZON_NOVA == provider:
|
||||
return litellm.AmazonNovaChatConfig()
|
||||
elif litellm.LlmProviders.LANGGRAPH == provider:
|
||||
from litellm.llms.langgraph.chat.transformation import LangGraphConfig
|
||||
|
||||
return LangGraphConfig()
|
||||
return None
|
||||
# Unpack factory function and whether it needs model parameter
|
||||
# This avoids expensive inspect.signature() calls at runtime
|
||||
config_factory, needs_model = config_entry
|
||||
if needs_model:
|
||||
return config_factory(model) # type: ignore
|
||||
else:
|
||||
return config_factory() # type: ignore
|
||||
|
||||
@staticmethod
|
||||
def get_provider_embedding_config(
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue