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Support discovering gemini, anthropic, xai models by calling their /v1/model endpoint (#9530)

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* fix: initial commit for adding provider model discovery to gemini

* feat(gemini/): add model discovery for gemini/ route

* docs(set_keys.md): update docs to show you can check available gemini models as well

* feat(anthropic/): add model discovery for anthropic api key

* feat(xai/): add model discovery for XAI

enables checking what models an xai key can call

* ci: bump ci config yml

* fix(topaz/common_utils.py): fix linting error

* fix: fix linting error for python38
This commit is contained in:
Krish Dholakia 2025-03-27 22:50:48 -07:00 • committed by GitHub
parent ff4419e5ee
commit 3543b2a808
9 changed files with 223 additions and 6 deletions
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24
litellm/utils.py
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@ -5744,13 +5744,15 @@ def trim_messages(
return messages
def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
def get_valid_models(
check_provider_endpoint: bool = False, custom_llm_provider: Optional[str] = None
) -> List[str]:
"""
Returns a list of valid LLMs based on the set environment variables
Args:
check_provider_endpoint: If True, will check the provider's endpoint for valid models.
custom_llm_provider: If provided, will only check the provider's endpoint for valid models.
Returns:
A list of valid LLMs
"""
@ -5762,6 +5764,9 @@ def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
valid_models = []
for provider in litellm.provider_list:
if custom_llm_provider and provider != custom_llm_provider:
continue
# edge case litellm has together_ai as a provider, it should be togetherai
env_provider_1 = provider.replace("_", "")
env_provider_2 = provider
@ -5783,10 +5788,17 @@ def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
provider=LlmProviders(provider),
)
if custom_llm_provider and provider != custom_llm_provider:
continue
if provider == "azure":
valid_models.append("Azure-LLM")
elif provider_config is not None and check_provider_endpoint:
valid_models.extend(provider_config.get_models())
try:
models = provider_config.get_models()
valid_models.extend(models)
except Exception as e:
verbose_logger.debug(f"Error getting valid models: {e}")
else:
models_for_provider = litellm.models_by_provider.get(provider, [])
valid_models.extend(models_for_provider)
@ -6400,10 +6412,16 @@ class ProviderConfigManager:
return litellm.FireworksAIConfig()
elif LlmProviders.OPENAI == provider:
return litellm.OpenAIGPTConfig()
elif LlmProviders.GEMINI == provider:
return litellm.GeminiModelInfo()
elif LlmProviders.LITELLM_PROXY == provider:
return litellm.LiteLLMProxyChatConfig()
elif LlmProviders.TOPAZ == provider:
return litellm.TopazModelInfo()
elif LlmProviders.ANTHROPIC == provider:
return litellm.AnthropicModelInfo()
elif LlmProviders.XAI == provider:
return litellm.XAIModelInfo()
return None