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fix: route llm model syntax to litellm
* fix: route llm model syntax to litellm * wip: add list of supported models
This commit is contained in:
Greyson LaLonde
@@ -38,6 +38,13 @@ from crewai.events.types.tool_usage_events import (
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ToolUsageStartedEvent,
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)
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from crewai.llms.base_llm import BaseLLM
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from crewai.llms.constants import (
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ANTHROPIC_MODELS,
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AZURE_MODELS,
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BEDROCK_MODELS,
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GEMINI_MODELS,
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OPENAI_MODELS,
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)
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from crewai.utilities import InternalInstructor
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from crewai.utilities.exceptions.context_window_exceeding_exception import (
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LLMContextLengthExceededError,
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@@ -323,18 +330,64 @@ class LLM(BaseLLM):
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completion_cost: float | None = None
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def __new__(cls, model: str, is_litellm: bool = False, **kwargs: Any) -> LLM:
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"""Factory method that routes to native SDK or falls back to LiteLLM."""
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"""Factory method that routes to native SDK or falls back to LiteLLM.
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Routing priority:
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1. If 'provider' kwarg is present, use that provider with constants
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2. If only 'model' kwarg, use constants to infer provider
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3. If "/" in model name:
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- Check if prefix is a native provider (openai/anthropic/azure/bedrock/gemini)
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- If yes, validate model against constants
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- If valid, route to native SDK; otherwise route to LiteLLM
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"""
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if not model or not isinstance(model, str):
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raise ValueError("Model must be a non-empty string")
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provider = model.partition("/")[0] if "/" in model else "openai"
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explicit_provider = kwargs.get("provider")
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native_class = cls._get_native_provider(provider)
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if explicit_provider:
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provider = explicit_provider
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use_native = True
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model_string = model
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elif "/" in model:
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prefix, _, model_part = model.partition("/")
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provider_mapping = {
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"openai": "openai",
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"anthropic": "anthropic",
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"claude": "anthropic",
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"azure": "azure",
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"azure_openai": "azure",
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"google": "gemini",
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"gemini": "gemini",
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"bedrock": "bedrock",
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"aws": "bedrock",
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}
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canonical_provider = provider_mapping.get(prefix.lower())
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if canonical_provider and cls._validate_model_in_constants(
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model_part, canonical_provider
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):
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provider = canonical_provider
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use_native = True
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model_string = model_part
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else:
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provider = prefix
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use_native = False
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model_string = model_part
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else:
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provider = cls._infer_provider_from_model(model)
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use_native = True
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model_string = model
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native_class = cls._get_native_provider(provider) if use_native else None
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if native_class and not is_litellm and provider in SUPPORTED_NATIVE_PROVIDERS:
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try:
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model_string = model.partition("/")[2] if "/" in model else model
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# Remove 'provider' from kwargs if it exists to avoid duplicate keyword argument
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kwargs_copy = {k: v for k, v in kwargs.items() if k != 'provider'}
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return cast(
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Self, native_class(model=model_string, provider=provider, **kwargs)
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Self, native_class(model=model_string, provider=provider, **kwargs_copy)
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)
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except NotImplementedError:
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raise
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@@ -351,6 +404,63 @@ class LLM(BaseLLM):
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instance.is_litellm = True
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return instance
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@classmethod
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def _validate_model_in_constants(cls, model: str, provider: str) -> bool:
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"""Validate if a model name exists in the provider's constants.
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Args:
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model: The model name to validate
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provider: The provider to check against (canonical name)
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Returns:
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True if the model exists in the provider's constants, False otherwise
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"""
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if provider == "openai":
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return model in OPENAI_MODELS
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if provider == "anthropic" or provider == "claude":
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return model in ANTHROPIC_MODELS
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if provider == "gemini":
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return model in GEMINI_MODELS
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if provider == "bedrock":
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return model in BEDROCK_MODELS
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if provider == "azure":
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# azure does not provide a list of available models, determine a better way to handle this
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return True
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return False
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@classmethod
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def _infer_provider_from_model(cls, model: str) -> str:
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"""Infer the provider from the model name.
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Args:
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model: The model name without provider prefix
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Returns:
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The inferred provider name, defaults to "openai"
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"""
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if model in OPENAI_MODELS:
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return "openai"
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if model in ANTHROPIC_MODELS:
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return "anthropic"
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if model in GEMINI_MODELS:
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return "gemini"
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if model in BEDROCK_MODELS:
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return "bedrock"
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if model in AZURE_MODELS:
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return "azure"
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return "openai"
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@classmethod
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def _get_native_provider(cls, provider: str) -> type | None:
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"""Get native provider class if available."""
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558
lib/crewai/src/crewai/llms/constants.py
Normal file
558
lib/crewai/src/crewai/llms/constants.py
Normal file
@@ -0,0 +1,558 @@
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from typing import Literal, TypeAlias
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OpenAIModels: TypeAlias = Literal[
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"gpt-3.5-turbo",
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"gpt-3.5-turbo-0125",
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"gpt-3.5-turbo-0301",
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"gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-1106",
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"gpt-3.5-turbo-16k",
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"gpt-3.5-turbo-16k-0613",
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"gpt-3.5-turbo-instruct",
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"gpt-3.5-turbo-instruct-0914",
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"gpt-4",
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"gpt-4-0125-preview",
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"gpt-4-0314",
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"gpt-4-0613",
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"gpt-4-1106-preview",
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"gpt-4-32k",
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"gpt-4-32k-0314",
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"gpt-4-32k-0613",
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"gpt-4-turbo",
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"gpt-4-turbo-2024-04-09",
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"gpt-4-turbo-preview",
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"gpt-4-vision-preview",
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"gpt-4.1",
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"gpt-4.1-2025-04-14",
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"gpt-4.1-mini",
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"gpt-4.1-mini-2025-04-14",
|
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"gpt-4.1-nano",
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"gpt-4.1-nano-2025-04-14",
|
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"gpt-4o",
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"gpt-4o-2024-05-13",
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"gpt-4o-2024-08-06",
|
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"gpt-4o-2024-11-20",
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"gpt-4o-audio-preview",
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"gpt-4o-audio-preview-2024-10-01",
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"gpt-4o-audio-preview-2024-12-17",
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"gpt-4o-audio-preview-2025-06-03",
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"gpt-4o-mini",
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"gpt-4o-mini-2024-07-18",
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"gpt-4o-mini-audio-preview",
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"gpt-4o-mini-audio-preview-2024-12-17",
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"gpt-4o-mini-realtime-preview",
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"gpt-4o-mini-realtime-preview-2024-12-17",
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"gpt-4o-mini-search-preview",
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"gpt-4o-mini-search-preview-2025-03-11",
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"gpt-4o-mini-transcribe",
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"gpt-4o-mini-tts",
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"gpt-4o-realtime-preview",
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"gpt-4o-realtime-preview-2024-10-01",
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"gpt-4o-realtime-preview-2024-12-17",
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"gpt-4o-realtime-preview-2025-06-03",
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"gpt-4o-search-preview",
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"gpt-4o-search-preview-2025-03-11",
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"gpt-4o-transcribe",
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"gpt-4o-transcribe-diarize",
|
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"gpt-5",
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"gpt-5-2025-08-07",
|
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"gpt-5-chat",
|
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"gpt-5-chat-latest",
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"gpt-5-codex",
|
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"gpt-5-mini",
|
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"gpt-5-mini-2025-08-07",
|
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"gpt-5-nano",
|
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"gpt-5-nano-2025-08-07",
|
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"gpt-5-pro",
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"gpt-5-pro-2025-10-06",
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"gpt-5-search-api",
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"gpt-5-search-api-2025-10-14",
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"gpt-audio",
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"gpt-audio-2025-08-28",
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"gpt-audio-mini",
|
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"gpt-audio-mini-2025-10-06",
|
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"gpt-image-1",
|
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"gpt-image-1-mini",
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"gpt-realtime",
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"gpt-realtime-2025-08-28",
|
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"gpt-realtime-mini",
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"gpt-realtime-mini-2025-10-06",
|
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"o1",
|
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"o1-preview",
|
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"o1-2024-12-17",
|
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"o1-mini",
|
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"o1-mini-2024-09-12",
|
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"o1-pro",
|
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"o1-pro-2025-03-19",
|
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"o3-mini",
|
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"o3",
|
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"o4-mini",
|
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"whisper-1",
|
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]
|
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OPENAI_MODELS: list[OpenAIModels] = [
|
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"gpt-3.5-turbo",
|
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"gpt-3.5-turbo-0125",
|
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"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
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"gpt-3.5-turbo-1106",
|
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"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
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"gpt-3.5-turbo-instruct",
|
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"gpt-3.5-turbo-instruct-0914",
|
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"gpt-4",
|
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"gpt-4-0125-preview",
|
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"gpt-4-0314",
|
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"gpt-4-0613",
|
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"gpt-4-1106-preview",
|
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"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
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"gpt-4-32k-0613",
|
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"gpt-4-turbo",
|
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"gpt-4-turbo-2024-04-09",
|
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"gpt-4-turbo-preview",
|
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"gpt-4-vision-preview",
|
||||
"gpt-4.1",
|
||||
"gpt-4.1-2025-04-14",
|
||||
"gpt-4.1-mini",
|
||||
"gpt-4.1-mini-2025-04-14",
|
||||
"gpt-4.1-nano",
|
||||
"gpt-4.1-nano-2025-04-14",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-audio-preview",
|
||||
"gpt-4o-audio-preview-2024-10-01",
|
||||
"gpt-4o-audio-preview-2024-12-17",
|
||||
"gpt-4o-audio-preview-2025-06-03",
|
||||
"gpt-4o-mini",
|
||||
"gpt-4o-mini-2024-07-18",
|
||||
"gpt-4o-mini-audio-preview",
|
||||
"gpt-4o-mini-audio-preview-2024-12-17",
|
||||
"gpt-4o-mini-realtime-preview",
|
||||
"gpt-4o-mini-realtime-preview-2024-12-17",
|
||||
"gpt-4o-mini-search-preview",
|
||||
"gpt-4o-mini-search-preview-2025-03-11",
|
||||
"gpt-4o-mini-transcribe",
|
||||
"gpt-4o-mini-tts",
|
||||
"gpt-4o-realtime-preview",
|
||||
"gpt-4o-realtime-preview-2024-10-01",
|
||||
"gpt-4o-realtime-preview-2024-12-17",
|
||||
"gpt-4o-realtime-preview-2025-06-03",
|
||||
"gpt-4o-search-preview",
|
||||
"gpt-4o-search-preview-2025-03-11",
|
||||
"gpt-4o-transcribe",
|
||||
"gpt-4o-transcribe-diarize",
|
||||
"gpt-5",
|
||||
"gpt-5-2025-08-07",
|
||||
"gpt-5-chat",
|
||||
"gpt-5-chat-latest",
|
||||
"gpt-5-codex",
|
||||
"gpt-5-mini",
|
||||
"gpt-5-mini-2025-08-07",
|
||||
"gpt-5-nano",
|
||||
"gpt-5-nano-2025-08-07",
|
||||
"gpt-5-pro",
|
||||
"gpt-5-pro-2025-10-06",
|
||||
"gpt-5-search-api",
|
||||
"gpt-5-search-api-2025-10-14",
|
||||
"gpt-audio",
|
||||
"gpt-audio-2025-08-28",
|
||||
"gpt-audio-mini",
|
||||
"gpt-audio-mini-2025-10-06",
|
||||
"gpt-image-1",
|
||||
"gpt-image-1-mini",
|
||||
"gpt-realtime",
|
||||
"gpt-realtime-2025-08-28",
|
||||
"gpt-realtime-mini",
|
||||
"gpt-realtime-mini-2025-10-06",
|
||||
"o1",
|
||||
"o1-preview",
|
||||
"o1-2024-12-17",
|
||||
"o1-mini",
|
||||
"o1-mini-2024-09-12",
|
||||
"o1-pro",
|
||||
"o1-pro-2025-03-19",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
"whisper-1",
|
||||
]
|
||||
|
||||
|
||||
AnthropicModels: TypeAlias = Literal[
|
||||
"claude-3-7-sonnet-latest",
|
||||
"claude-3-7-sonnet-20250219",
|
||||
"claude-3-5-haiku-latest",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-haiku-4-5",
|
||||
"claude-haiku-4-5-20251001",
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-sonnet-4-0",
|
||||
"claude-4-sonnet-20250514",
|
||||
"claude-sonnet-4-5",
|
||||
"claude-sonnet-4-5-20250929",
|
||||
"claude-3-5-sonnet-latest",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-opus-4-0",
|
||||
"claude-opus-4-20250514",
|
||||
"claude-4-opus-20250514",
|
||||
"claude-opus-4-1",
|
||||
"claude-opus-4-1-20250805",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-haiku-latest",
|
||||
"claude-3-haiku-20240307",
|
||||
]
|
||||
ANTHROPIC_MODELS: list[AnthropicModels] = [
|
||||
"claude-3-7-sonnet-latest",
|
||||
"claude-3-7-sonnet-20250219",
|
||||
"claude-3-5-haiku-latest",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-haiku-4-5",
|
||||
"claude-haiku-4-5-20251001",
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-sonnet-4-0",
|
||||
"claude-4-sonnet-20250514",
|
||||
"claude-sonnet-4-5",
|
||||
"claude-sonnet-4-5-20250929",
|
||||
"claude-3-5-sonnet-latest",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-opus-4-0",
|
||||
"claude-opus-4-20250514",
|
||||
"claude-4-opus-20250514",
|
||||
"claude-opus-4-1",
|
||||
"claude-opus-4-1-20250805",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-haiku-latest",
|
||||
"claude-3-haiku-20240307",
|
||||
]
|
||||
|
||||
GeminiModels: TypeAlias = Literal[
|
||||
"gemini-2.5-pro",
|
||||
"gemini-2.5-pro-preview-03-25",
|
||||
"gemini-2.5-pro-preview-05-06",
|
||||
"gemini-2.5-pro-preview-06-05",
|
||||
"gemini-2.5-flash",
|
||||
"gemini-2.5-flash-preview-05-20",
|
||||
"gemini-2.5-flash-preview-04-17",
|
||||
"gemini-2.5-flash-image",
|
||||
"gemini-2.5-flash-image-preview",
|
||||
"gemini-2.5-flash-lite",
|
||||
"gemini-2.5-flash-lite-preview-06-17",
|
||||
"gemini-2.5-flash-preview-09-2025",
|
||||
"gemini-2.5-flash-lite-preview-09-2025",
|
||||
"gemini-2.5-flash-preview-tts",
|
||||
"gemini-2.5-pro-preview-tts",
|
||||
"gemini-2.5-computer-use-preview-10-2025",
|
||||
"gemini-2.0-flash",
|
||||
"gemini-2.0-flash-001",
|
||||
"gemini-2.0-flash-exp",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.0-flash-lite",
|
||||
"gemini-2.0-flash-lite-001",
|
||||
"gemini-2.0-flash-lite-preview",
|
||||
"gemini-2.0-flash-lite-preview-02-05",
|
||||
"gemini-2.0-flash-preview-image-generation",
|
||||
"gemini-2.0-flash-thinking-exp",
|
||||
"gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini-2.0-flash-thinking-exp-1219",
|
||||
"gemini-2.0-pro-exp",
|
||||
"gemini-2.0-pro-exp-02-05",
|
||||
"gemini-exp-1206",
|
||||
"gemini-1.5-pro",
|
||||
"gemini-1.5-flash",
|
||||
"gemini-1.5-flash-8b",
|
||||
"gemini-flash-latest",
|
||||
"gemini-flash-lite-latest",
|
||||
"gemini-pro-latest",
|
||||
"gemini-2.0-flash-live-001",
|
||||
"gemini-live-2.5-flash-preview",
|
||||
"gemini-2.5-flash-live-preview",
|
||||
"gemini-robotics-er-1.5-preview",
|
||||
"gemini-gemma-2-27b-it",
|
||||
"gemini-gemma-2-9b-it",
|
||||
"gemma-3-1b-it",
|
||||
"gemma-3-4b-it",
|
||||
"gemma-3-12b-it",
|
||||
"gemma-3-27b-it",
|
||||
"gemma-3n-e2b-it",
|
||||
"gemma-3n-e4b-it",
|
||||
"learnlm-2.0-flash-experimental",
|
||||
]
|
||||
GEMINI_MODELS: list[GeminiModels] = [
|
||||
"gemini-2.5-pro",
|
||||
"gemini-2.5-pro-preview-03-25",
|
||||
"gemini-2.5-pro-preview-05-06",
|
||||
"gemini-2.5-pro-preview-06-05",
|
||||
"gemini-2.5-flash",
|
||||
"gemini-2.5-flash-preview-05-20",
|
||||
"gemini-2.5-flash-preview-04-17",
|
||||
"gemini-2.5-flash-image",
|
||||
"gemini-2.5-flash-image-preview",
|
||||
"gemini-2.5-flash-lite",
|
||||
"gemini-2.5-flash-lite-preview-06-17",
|
||||
"gemini-2.5-flash-preview-09-2025",
|
||||
"gemini-2.5-flash-lite-preview-09-2025",
|
||||
"gemini-2.5-flash-preview-tts",
|
||||
"gemini-2.5-pro-preview-tts",
|
||||
"gemini-2.5-computer-use-preview-10-2025",
|
||||
"gemini-2.0-flash",
|
||||
"gemini-2.0-flash-001",
|
||||
"gemini-2.0-flash-exp",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.0-flash-lite",
|
||||
"gemini-2.0-flash-lite-001",
|
||||
"gemini-2.0-flash-lite-preview",
|
||||
"gemini-2.0-flash-lite-preview-02-05",
|
||||
"gemini-2.0-flash-preview-image-generation",
|
||||
"gemini-2.0-flash-thinking-exp",
|
||||
"gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini-2.0-flash-thinking-exp-1219",
|
||||
"gemini-2.0-pro-exp",
|
||||
"gemini-2.0-pro-exp-02-05",
|
||||
"gemini-exp-1206",
|
||||
"gemini-1.5-pro",
|
||||
"gemini-1.5-flash",
|
||||
"gemini-1.5-flash-8b",
|
||||
"gemini-flash-latest",
|
||||
"gemini-flash-lite-latest",
|
||||
"gemini-pro-latest",
|
||||
"gemini-2.0-flash-live-001",
|
||||
"gemini-live-2.5-flash-preview",
|
||||
"gemini-2.5-flash-live-preview",
|
||||
"gemini-robotics-er-1.5-preview",
|
||||
"gemini-gemma-2-27b-it",
|
||||
"gemini-gemma-2-9b-it",
|
||||
"gemma-3-1b-it",
|
||||
"gemma-3-4b-it",
|
||||
"gemma-3-12b-it",
|
||||
"gemma-3-27b-it",
|
||||
"gemma-3n-e2b-it",
|
||||
"gemma-3n-e4b-it",
|
||||
"learnlm-2.0-flash-experimental",
|
||||
]
|
||||
|
||||
|
||||
AzureModels: TypeAlias = Literal[
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-35-turbo",
|
||||
"gpt-35-turbo-0125",
|
||||
"gpt-35-turbo-1106",
|
||||
"gpt-35-turbo-16k-0613",
|
||||
"gpt-35-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-vision",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-mini",
|
||||
"gpt-5",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-preview",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
]
|
||||
AZURE_MODELS: list[AzureModels] = [
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-35-turbo",
|
||||
"gpt-35-turbo-0125",
|
||||
"gpt-35-turbo-1106",
|
||||
"gpt-35-turbo-16k-0613",
|
||||
"gpt-35-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-vision",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-mini",
|
||||
"gpt-5",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-preview",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
]
|
||||
|
||||
|
||||
BedrockModels: TypeAlias = Literal[
|
||||
"ai21.jamba-1-5-large-v1:0",
|
||||
"ai21.jamba-1-5-mini-v1:0",
|
||||
"amazon.nova-lite-v1:0",
|
||||
"amazon.nova-lite-v1:0:24k",
|
||||
"amazon.nova-lite-v1:0:300k",
|
||||
"amazon.nova-micro-v1:0",
|
||||
"amazon.nova-micro-v1:0:128k",
|
||||
"amazon.nova-micro-v1:0:24k",
|
||||
"amazon.nova-premier-v1:0",
|
||||
"amazon.nova-premier-v1:0:1000k",
|
||||
"amazon.nova-premier-v1:0:20k",
|
||||
"amazon.nova-premier-v1:0:8k",
|
||||
"amazon.nova-premier-v1:0:mm",
|
||||
"amazon.nova-pro-v1:0",
|
||||
"amazon.nova-pro-v1:0:24k",
|
||||
"amazon.nova-pro-v1:0:300k",
|
||||
"amazon.titan-text-express-v1",
|
||||
"amazon.titan-text-express-v1:0:8k",
|
||||
"amazon.titan-text-lite-v1",
|
||||
"amazon.titan-text-lite-v1:0:4k",
|
||||
"amazon.titan-tg1-large",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-7-sonnet-20250219-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:200k",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:48k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:12k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:28k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:28k",
|
||||
"anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
"anthropic.claude-instant-v1:2:100k",
|
||||
"anthropic.claude-opus-4-1-20250805-v1:0",
|
||||
"anthropic.claude-opus-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-5-20250929-v1:0",
|
||||
"anthropic.claude-v2:0:100k",
|
||||
"anthropic.claude-v2:0:18k",
|
||||
"anthropic.claude-v2:1:18k",
|
||||
"anthropic.claude-v2:1:200k",
|
||||
"cohere.command-r-plus-v1:0",
|
||||
"cohere.command-r-v1:0",
|
||||
"cohere.rerank-v3-5:0",
|
||||
"deepseek.r1-v1:0",
|
||||
"meta.llama3-1-70b-instruct-v1:0",
|
||||
"meta.llama3-1-8b-instruct-v1:0",
|
||||
"meta.llama3-2-11b-instruct-v1:0",
|
||||
"meta.llama3-2-1b-instruct-v1:0",
|
||||
"meta.llama3-2-3b-instruct-v1:0",
|
||||
"meta.llama3-2-90b-instruct-v1:0",
|
||||
"meta.llama3-3-70b-instruct-v1:0",
|
||||
"meta.llama3-70b-instruct-v1:0",
|
||||
"meta.llama3-8b-instruct-v1:0",
|
||||
"meta.llama4-maverick-17b-instruct-v1:0",
|
||||
"meta.llama4-scout-17b-instruct-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.pixtral-large-2502-v1:0",
|
||||
"openai.gpt-oss-120b-1:0",
|
||||
"openai.gpt-oss-20b-1:0",
|
||||
"qwen.qwen3-32b-v1:0",
|
||||
"qwen.qwen3-coder-30b-a3b-v1:0",
|
||||
"twelvelabs.pegasus-1-2-v1:0",
|
||||
]
|
||||
BEDROCK_MODELS: list[BedrockModels] = [
|
||||
"ai21.jamba-1-5-large-v1:0",
|
||||
"ai21.jamba-1-5-mini-v1:0",
|
||||
"amazon.nova-lite-v1:0",
|
||||
"amazon.nova-lite-v1:0:24k",
|
||||
"amazon.nova-lite-v1:0:300k",
|
||||
"amazon.nova-micro-v1:0",
|
||||
"amazon.nova-micro-v1:0:128k",
|
||||
"amazon.nova-micro-v1:0:24k",
|
||||
"amazon.nova-premier-v1:0",
|
||||
"amazon.nova-premier-v1:0:1000k",
|
||||
"amazon.nova-premier-v1:0:20k",
|
||||
"amazon.nova-premier-v1:0:8k",
|
||||
"amazon.nova-premier-v1:0:mm",
|
||||
"amazon.nova-pro-v1:0",
|
||||
"amazon.nova-pro-v1:0:24k",
|
||||
"amazon.nova-pro-v1:0:300k",
|
||||
"amazon.titan-text-express-v1",
|
||||
"amazon.titan-text-express-v1:0:8k",
|
||||
"amazon.titan-text-lite-v1",
|
||||
"amazon.titan-text-lite-v1:0:4k",
|
||||
"amazon.titan-tg1-large",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-7-sonnet-20250219-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:200k",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:48k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:12k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:28k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:28k",
|
||||
"anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
"anthropic.claude-instant-v1:2:100k",
|
||||
"anthropic.claude-opus-4-1-20250805-v1:0",
|
||||
"anthropic.claude-opus-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-5-20250929-v1:0",
|
||||
"anthropic.claude-v2:0:100k",
|
||||
"anthropic.claude-v2:0:18k",
|
||||
"anthropic.claude-v2:1:18k",
|
||||
"anthropic.claude-v2:1:200k",
|
||||
"cohere.command-r-plus-v1:0",
|
||||
"cohere.command-r-v1:0",
|
||||
"cohere.rerank-v3-5:0",
|
||||
"deepseek.r1-v1:0",
|
||||
"meta.llama3-1-70b-instruct-v1:0",
|
||||
"meta.llama3-1-8b-instruct-v1:0",
|
||||
"meta.llama3-2-11b-instruct-v1:0",
|
||||
"meta.llama3-2-1b-instruct-v1:0",
|
||||
"meta.llama3-2-3b-instruct-v1:0",
|
||||
"meta.llama3-2-90b-instruct-v1:0",
|
||||
"meta.llama3-3-70b-instruct-v1:0",
|
||||
"meta.llama3-70b-instruct-v1:0",
|
||||
"meta.llama3-8b-instruct-v1:0",
|
||||
"meta.llama4-maverick-17b-instruct-v1:0",
|
||||
"meta.llama4-scout-17b-instruct-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.pixtral-large-2502-v1:0",
|
||||
"openai.gpt-oss-120b-1:0",
|
||||
"openai.gpt-oss-20b-1:0",
|
||||
"qwen.qwen3-32b-v1:0",
|
||||
"qwen.qwen3-coder-30b-a3b-v1:0",
|
||||
"twelvelabs.pegasus-1-2-v1:0",
|
||||
]
|
||||
@@ -36,7 +36,7 @@ def test_anthropic_completion_is_used_when_claude_provider():
|
||||
|
||||
from crewai.llms.providers.anthropic.completion import AnthropicCompletion
|
||||
assert isinstance(llm, AnthropicCompletion)
|
||||
assert llm.provider == "claude"
|
||||
assert llm.provider == "anthropic"
|
||||
assert llm.model == "claude-3-5-sonnet-20241022"
|
||||
|
||||
|
||||
|
||||
@@ -39,7 +39,7 @@ def test_azure_completion_is_used_when_azure_openai_provider():
|
||||
|
||||
from crewai.llms.providers.azure.completion import AzureCompletion
|
||||
assert isinstance(llm, AzureCompletion)
|
||||
assert llm.provider == "azure_openai"
|
||||
assert llm.provider == "azure"
|
||||
assert llm.model == "gpt-4"
|
||||
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ def test_gemini_completion_is_used_when_google_provider():
|
||||
llm = LLM(model="google/gemini-2.0-flash-001")
|
||||
|
||||
assert llm.__class__.__name__ == "GeminiCompletion"
|
||||
assert llm.provider == "google"
|
||||
assert llm.provider == "gemini"
|
||||
assert llm.model == "gemini-2.0-flash-001"
|
||||
|
||||
|
||||
|
||||
@@ -154,7 +154,7 @@ class TestGeminiProviderInterceptor:
|
||||
# Gemini provider should raise NotImplementedError
|
||||
with pytest.raises(NotImplementedError) as exc_info:
|
||||
LLM(
|
||||
model="gemini/gemini-pro",
|
||||
model="gemini/gemini-2.5-pro",
|
||||
interceptor=interceptor,
|
||||
api_key="test-gemini-key",
|
||||
)
|
||||
@@ -169,7 +169,7 @@ class TestGeminiProviderInterceptor:
|
||||
|
||||
with pytest.raises(NotImplementedError) as exc_info:
|
||||
LLM(
|
||||
model="gemini/gemini-pro",
|
||||
model="gemini/gemini-2.5-pro",
|
||||
interceptor=interceptor,
|
||||
api_key="test-gemini-key",
|
||||
)
|
||||
@@ -181,7 +181,7 @@ class TestGeminiProviderInterceptor:
|
||||
def test_gemini_without_interceptor_works(self) -> None:
|
||||
"""Test that Gemini LLM works without interceptor."""
|
||||
llm = LLM(
|
||||
model="gemini/gemini-pro",
|
||||
model="gemini/gemini-2.5-pro",
|
||||
api_key="test-gemini-key",
|
||||
)
|
||||
|
||||
@@ -231,7 +231,7 @@ class TestUnsupportedProviderMessages:
|
||||
|
||||
with pytest.raises(NotImplementedError) as exc_info:
|
||||
LLM(
|
||||
model="gemini/gemini-pro",
|
||||
model="gemini/gemini-2.5-pro",
|
||||
interceptor=interceptor,
|
||||
api_key="test-gemini-key",
|
||||
)
|
||||
@@ -282,7 +282,7 @@ class TestProviderSupportMatrix:
|
||||
# Gemini - NOT SUPPORTED
|
||||
with pytest.raises(NotImplementedError):
|
||||
LLM(
|
||||
model="gemini/gemini-pro",
|
||||
model="gemini/gemini-2.5-pro",
|
||||
interceptor=interceptor,
|
||||
api_key="test",
|
||||
)
|
||||
@@ -315,5 +315,5 @@ class TestProviderSupportMatrix:
|
||||
assert not hasattr(bedrock_llm, 'interceptor') or bedrock_llm.interceptor is None
|
||||
|
||||
# Gemini - doesn't have interceptor attribute
|
||||
gemini_llm = LLM(model="gemini/gemini-pro", api_key="test")
|
||||
assert not hasattr(gemini_llm, 'interceptor') or gemini_llm.interceptor is None
|
||||
gemini_llm = LLM(model="gemini/gemini-2.5-pro", api_key="test")
|
||||
assert not hasattr(gemini_llm, 'interceptor') or gemini_llm.interceptor is None
|
||||
|
||||
@@ -16,7 +16,7 @@ def test_openai_completion_is_used_when_openai_provider():
|
||||
"""
|
||||
Test that OpenAICompletion from completion.py is used when LLM uses provider 'openai'
|
||||
"""
|
||||
llm = LLM(model="openai/gpt-4o")
|
||||
llm = LLM(model="gpt-4o")
|
||||
|
||||
assert llm.__class__.__name__ == "OpenAICompletion"
|
||||
assert llm.provider == "openai"
|
||||
@@ -70,7 +70,7 @@ def test_openai_completion_module_is_imported():
|
||||
del sys.modules[module_name]
|
||||
|
||||
# Create LLM instance - this should trigger the import
|
||||
LLM(model="openai/gpt-4o")
|
||||
LLM(model="gpt-4o")
|
||||
|
||||
# Verify the module was imported
|
||||
assert module_name in sys.modules
|
||||
@@ -97,7 +97,7 @@ def test_native_openai_raises_error_when_initialization_fails():
|
||||
|
||||
# This should raise ImportError, not fall back to LiteLLM
|
||||
with pytest.raises(ImportError) as excinfo:
|
||||
LLM(model="openai/gpt-4o")
|
||||
LLM(model="gpt-4o")
|
||||
|
||||
assert "Error importing native provider" in str(excinfo.value)
|
||||
assert "Native SDK failed" in str(excinfo.value)
|
||||
@@ -108,7 +108,7 @@ def test_openai_completion_initialization_parameters():
|
||||
Test that OpenAICompletion is initialized with correct parameters
|
||||
"""
|
||||
llm = LLM(
|
||||
model="openai/gpt-4o",
|
||||
model="gpt-4o",
|
||||
temperature=0.7,
|
||||
max_tokens=1000,
|
||||
api_key="test-key"
|
||||
@@ -311,7 +311,7 @@ def test_openai_completion_call_returns_usage_metrics():
|
||||
role="Research Assistant",
|
||||
goal="Find information about the population of Tokyo",
|
||||
backstory="You are a helpful research assistant.",
|
||||
llm=LLM(model="openai/gpt-4o"),
|
||||
llm=LLM(model="gpt-4o"),
|
||||
verbose=True,
|
||||
)
|
||||
|
||||
@@ -331,6 +331,7 @@ def test_openai_completion_call_returns_usage_metrics():
|
||||
assert result.token_usage.cached_prompt_tokens == 0
|
||||
|
||||
|
||||
@pytest.mark.skip(reason="Allow for litellm")
|
||||
def test_openai_raises_error_when_model_not_supported():
|
||||
"""Test that OpenAICompletion raises ValueError when model not supported"""
|
||||
|
||||
@@ -354,7 +355,7 @@ def test_openai_client_setup_with_extra_arguments():
|
||||
Test that OpenAICompletion is initialized with correct parameters
|
||||
"""
|
||||
llm = LLM(
|
||||
model="openai/gpt-4o",
|
||||
model="gpt-4o",
|
||||
temperature=0.7,
|
||||
max_tokens=1000,
|
||||
top_p=0.5,
|
||||
@@ -391,7 +392,7 @@ def test_extra_arguments_are_passed_to_openai_completion():
|
||||
"""
|
||||
Test that extra arguments are passed to OpenAICompletion
|
||||
"""
|
||||
llm = LLM(model="openai/gpt-4o", temperature=0.7, max_tokens=1000, top_p=0.5, max_retries=3)
|
||||
llm = LLM(model="gpt-4o", temperature=0.7, max_tokens=1000, top_p=0.5, max_retries=3)
|
||||
|
||||
with patch.object(llm.client.chat.completions, 'create') as mock_create:
|
||||
mock_create.return_value = MagicMock(
|
||||
|
||||
@@ -710,7 +710,7 @@ def test_native_provider_raises_error_when_supported_but_fails():
|
||||
mock_get_native.return_value = mock_provider
|
||||
|
||||
with pytest.raises(ImportError) as excinfo:
|
||||
LLM(model="openai/gpt-4", is_litellm=False)
|
||||
LLM(model="gpt-4", is_litellm=False)
|
||||
|
||||
assert "Error importing native provider" in str(excinfo.value)
|
||||
assert "Native provider initialization failed" in str(excinfo.value)
|
||||
@@ -725,3 +725,113 @@ def test_native_provider_falls_back_to_litellm_when_not_in_supported_list():
|
||||
# Should fall back to LiteLLM
|
||||
assert llm.is_litellm is True
|
||||
assert llm.model == "groq/llama-3.1-70b-versatile"
|
||||
|
||||
|
||||
def test_prefixed_models_with_valid_constants_use_native_sdk():
|
||||
"""Test that models with native provider prefixes use native SDK when model is in constants."""
|
||||
# Test openai/ prefix with actual OpenAI model in constants → Native SDK
|
||||
with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
|
||||
llm = LLM(model="openai/gpt-4o", is_litellm=False)
|
||||
assert llm.is_litellm is False
|
||||
assert llm.provider == "openai"
|
||||
|
||||
# Test anthropic/ prefix with Claude model in constants → Native SDK
|
||||
with patch.dict(os.environ, {"ANTHROPIC_API_KEY": "test-key"}):
|
||||
llm2 = LLM(model="anthropic/claude-opus-4-0", is_litellm=False)
|
||||
assert llm2.is_litellm is False
|
||||
assert llm2.provider == "anthropic"
|
||||
|
||||
# Test gemini/ prefix with Gemini model in constants → Native SDK
|
||||
with patch.dict(os.environ, {"GOOGLE_API_KEY": "test-key"}):
|
||||
llm3 = LLM(model="gemini/gemini-2.5-pro", is_litellm=False)
|
||||
assert llm3.is_litellm is False
|
||||
assert llm3.provider == "gemini"
|
||||
|
||||
|
||||
def test_prefixed_models_with_invalid_constants_use_litellm():
|
||||
"""Test that models with native provider prefixes use LiteLLM when model is NOT in constants."""
|
||||
# Test openai/ prefix with non-OpenAI model (not in OPENAI_MODELS) → LiteLLM
|
||||
llm = LLM(model="openai/gemini-2.5-flash", is_litellm=False)
|
||||
assert llm.is_litellm is True
|
||||
assert llm.model == "openai/gemini-2.5-flash"
|
||||
|
||||
# Test openai/ prefix with unknown future model → LiteLLM
|
||||
llm2 = LLM(model="openai/gpt-future-6", is_litellm=False)
|
||||
assert llm2.is_litellm is True
|
||||
assert llm2.model == "openai/gpt-future-6"
|
||||
|
||||
# Test anthropic/ prefix with non-Anthropic model → LiteLLM
|
||||
llm3 = LLM(model="anthropic/gpt-4o", is_litellm=False)
|
||||
assert llm3.is_litellm is True
|
||||
assert llm3.model == "anthropic/gpt-4o"
|
||||
|
||||
|
||||
def test_prefixed_models_with_non_native_providers_use_litellm():
|
||||
"""Test that models with non-native provider prefixes always use LiteLLM."""
|
||||
# Test groq/ prefix (not a native provider) → LiteLLM
|
||||
llm = LLM(model="groq/llama-3.3-70b", is_litellm=False)
|
||||
assert llm.is_litellm is True
|
||||
assert llm.model == "groq/llama-3.3-70b"
|
||||
|
||||
# Test together/ prefix (not a native provider) → LiteLLM
|
||||
llm2 = LLM(model="together/qwen-2.5-72b", is_litellm=False)
|
||||
assert llm2.is_litellm is True
|
||||
assert llm2.model == "together/qwen-2.5-72b"
|
||||
|
||||
|
||||
def test_unprefixed_models_use_native_sdk():
|
||||
"""Test that unprefixed models use native SDK when model is in constants."""
|
||||
# gpt-4o is in OPENAI_MODELS → Native OpenAI SDK
|
||||
with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
|
||||
llm = LLM(model="gpt-4o", is_litellm=False)
|
||||
assert llm.is_litellm is False
|
||||
assert llm.provider == "openai"
|
||||
|
||||
# claude-opus-4-0 is in ANTHROPIC_MODELS → Native Anthropic SDK
|
||||
with patch.dict(os.environ, {"ANTHROPIC_API_KEY": "test-key"}):
|
||||
llm2 = LLM(model="claude-opus-4-0", is_litellm=False)
|
||||
assert llm2.is_litellm is False
|
||||
assert llm2.provider == "anthropic"
|
||||
|
||||
# gemini-2.5-pro is in GEMINI_MODELS → Native Gemini SDK
|
||||
with patch.dict(os.environ, {"GOOGLE_API_KEY": "test-key"}):
|
||||
llm3 = LLM(model="gemini-2.5-pro", is_litellm=False)
|
||||
assert llm3.is_litellm is False
|
||||
assert llm3.provider == "gemini"
|
||||
|
||||
|
||||
def test_explicit_provider_kwarg_takes_priority():
|
||||
"""Test that explicit provider kwarg takes priority over model name inference."""
|
||||
# Explicit provider=openai should use OpenAI even if model name suggests otherwise
|
||||
with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
|
||||
llm = LLM(model="gpt-4o", provider="openai", is_litellm=False)
|
||||
assert llm.is_litellm is False
|
||||
assert llm.provider == "openai"
|
||||
|
||||
# Explicit provider for a model with "/" should still use that provider
|
||||
with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
|
||||
llm2 = LLM(model="gpt-4o", provider="openai", is_litellm=False)
|
||||
assert llm2.is_litellm is False
|
||||
assert llm2.provider == "openai"
|
||||
|
||||
|
||||
def test_validate_model_in_constants():
|
||||
"""Test the _validate_model_in_constants method."""
|
||||
# OpenAI models
|
||||
assert LLM._validate_model_in_constants("gpt-4o", "openai") is True
|
||||
assert LLM._validate_model_in_constants("gpt-future-6", "openai") is False
|
||||
|
||||
# Anthropic models
|
||||
assert LLM._validate_model_in_constants("claude-opus-4-0", "claude") is True
|
||||
assert LLM._validate_model_in_constants("claude-future-5", "claude") is False
|
||||
|
||||
# Gemini models
|
||||
assert LLM._validate_model_in_constants("gemini-2.5-pro", "gemini") is True
|
||||
assert LLM._validate_model_in_constants("gemini-future", "gemini") is False
|
||||
|
||||
# Azure models
|
||||
assert LLM._validate_model_in_constants("gpt-4o", "azure") is True
|
||||
assert LLM._validate_model_in_constants("gpt-35-turbo", "azure") is True
|
||||
|
||||
# Bedrock models
|
||||
assert LLM._validate_model_in_constants("anthropic.claude-opus-4-1-20250805-v1:0", "bedrock") is True
|
||||
|
||||
Reference in New Issue
Block a user