Add SiliconFlow as an OpenAI-compatible chat provider

SiliconFlow exposes an OpenAI-compatible API and has been requested
several times (#12888, #8263). This wires it in as a first-class
provider: a SiliconFlowConfig subclass of OpenAIGPTConfig, registration
in the provider enum and OpenAI-compatible provider/endpoint lists, and
api_base/api_key resolution (default https://api.siliconflow.com/v1,
overridable via SILICONFLOW_API_BASE for the mainland endpoint).

Adds mocked unit tests covering config precedence and end-to-end
provider resolution.

litellm/__init__.py

@@ -616,6 +616,7 @@ snowflake_models: Set = set()
 gradient_ai_models: Set = set()
 llama_models: Set = set()
 nscale_models: Set = set()
+siliconflow_models: Set = set()
 nebius_models: Set = set()
 nebius_embedding_models: Set = set()
 aiml_models: Set = set()
@@ -805,6 +806,8 @@ def add_known_models(model_cost_map: Optional[Dict] = None):
             llama_models.add(key)
         elif value.get("litellm_provider") == "nscale":
             nscale_models.add(key)
+        elif value.get("litellm_provider") == "siliconflow":
+            siliconflow_models.add(key)
         elif value.get("litellm_provider") == "azure_ai":
             azure_ai_models.add(key)
         elif value.get("litellm_provider") == "voyage":
@@ -1009,6 +1012,7 @@ model_list = list(
     | llama_models
     | featherless_ai_models
     | nscale_models
+    | siliconflow_models
     | deepgram_models
     | elevenlabs_models
     | dashscope_models
@@ -1107,6 +1111,7 @@ models_by_provider: dict = {
     "gradient_ai": gradient_ai_models,
     "meta_llama": llama_models,
     "nscale": nscale_models,
+    "siliconflow": siliconflow_models,
     "featherless_ai": featherless_ai_models,
     "deepgram": deepgram_models,
     "elevenlabs": elevenlabs_models,
@@ -1787,6 +1792,9 @@ if TYPE_CHECKING:
         PerplexityChatConfig as _PerplexityChatConfig,
     )
     from .llms.nscale.chat.transformation import NscaleConfig as _NscaleConfig
+    from .llms.siliconflow.chat.transformation import (
+        SiliconFlowConfig as _SiliconFlowConfig,
+    )
     from .llms.watsonx.chat.transformation import (
         IBMWatsonXChatConfig as _IBMWatsonXChatConfig,
     )
@@ -1821,6 +1829,7 @@ if TYPE_CHECKING:
     AzureOpenAIO1Config: Type[_AzureOpenAIO1Config]
     PerplexityChatConfig: Type[_PerplexityChatConfig]
     NscaleConfig: Type[_NscaleConfig]
+    SiliconFlowConfig: Type[_SiliconFlowConfig]
     IBMWatsonXChatConfig: Type[_IBMWatsonXChatConfig]
     IBMWatsonXAIConfig: Type[_IBMWatsonXAIConfig]
     LiteLLMProxyChatConfig: Type[_LiteLLMProxyChatConfig]

litellm/_lazy_imports_registry.py

@@ -285,6 +285,7 @@ LLM_CONFIG_NAMES = (
     "LMStudioChatConfig",
     "LmStudioEmbeddingConfig",
     "NscaleConfig",
+    "SiliconFlowConfig",
     "PerplexityChatConfig",
     "AzureOpenAIO1Config",
     "IBMWatsonXAIConfig",
@@ -1088,6 +1089,10 @@ _LLM_CONFIGS_IMPORT_MAP = {
         "LmStudioEmbeddingConfig",
     ),
     "NscaleConfig": (".llms.nscale.chat.transformation", "NscaleConfig"),
+    "SiliconFlowConfig": (
+        ".llms.siliconflow.chat.transformation",
+        "SiliconFlowConfig",
+    ),
     "PerplexityChatConfig": (
         ".llms.perplexity.chat.transformation",
         "PerplexityChatConfig",

litellm/constants.py

@@ -611,6 +611,7 @@ LITELLM_CHAT_PROVIDERS = [
     "meta_llama",
     "featherless_ai",
     "nscale",
+    "siliconflow",
     "nebius",
     "dashscope",
     "moonshot",
@@ -766,6 +767,7 @@ openai_compatible_endpoints: List = [
     "api.llama.com/compat/v1/",
     "api.featherless.ai/v1",
     "inference.api.nscale.com/v1",
+    "api.siliconflow.com/v1",
     "api.studio.nebius.ai/v1",
     "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
     "https://api.moonshot.ai/v1",
@@ -826,6 +828,7 @@ openai_compatible_providers: List = [
     "chutes",  # Chutes - JSON-configured provider
     "featherless_ai",
     "nscale",
+    "siliconflow",
     "nebius",
     "dashscope",
     "moonshot",

litellm/litellm_core_utils/get_llm_provider_logic.py

@@ -311,6 +311,9 @@ def get_llm_provider(  # noqa: PLR0915
                     elif endpoint == litellm.NscaleConfig.API_BASE_URL:
                         custom_llm_provider = "nscale"
                         dynamic_api_key = litellm.NscaleConfig.get_api_key()
+                    elif endpoint == "api.siliconflow.com/v1":
+                        custom_llm_provider = "siliconflow"
+                        dynamic_api_key = litellm.SiliconFlowConfig.get_api_key()
                     elif endpoint == "dashscope-intl.aliyuncs.com/compatible-mode/v1":
                         custom_llm_provider = "dashscope"
                         dynamic_api_key = get_secret_str("DASHSCOPE_API_KEY")
@@ -881,6 +884,13 @@ def _get_openai_compatible_provider_info(  # noqa: PLR0915
         ) = litellm.NscaleConfig()._get_openai_compatible_provider_info(
             api_base=api_base, api_key=api_key
         )
+    elif custom_llm_provider == "siliconflow":
+        (
+            api_base,
+            dynamic_api_key,
+        ) = litellm.SiliconFlowConfig()._get_openai_compatible_provider_info(
+            api_base=api_base, api_key=api_key
+        )
     elif custom_llm_provider == "heroku":
         (
             api_base,

litellm/litellm_core_utils/get_supported_openai_params.py

@@ -261,6 +261,8 @@ def get_supported_openai_params(  # noqa: PLR0915
         return litellm.PerplexityChatConfig().get_supported_openai_params(model=model)
     elif custom_llm_provider == "nscale":
         return litellm.NscaleConfig().get_supported_openai_params(model=model)
+    elif custom_llm_provider == "siliconflow":
+        return litellm.SiliconFlowConfig().get_supported_openai_params(model=model)
     elif custom_llm_provider == "anyscale":
         return [
             "temperature",

litellm/llms/siliconflow/chat/transformation.py

@@ -0,0 +1,59 @@
+from typing import Optional, Tuple
+
+from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
+from litellm.secret_managers.main import get_secret_str
+
+
+class SiliconFlowConfig(OpenAIGPTConfig):
+    """
+    Reference: SiliconFlow is OpenAI compatible.
+
+    API Key: SILICONFLOW_API_KEY
+    Default API Base: https://api.siliconflow.com/v1
+
+    Users on the China mainland endpoint can set
+    SILICONFLOW_API_BASE=https://api.siliconflow.cn/v1
+    """
+
+    API_BASE_URL = "https://api.siliconflow.com/v1"
+
+    @property
+    def custom_llm_provider(self) -> Optional[str]:
+        return "siliconflow"
+
+    @staticmethod
+    def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
+        return api_key or get_secret_str("SILICONFLOW_API_KEY")
+
+    @staticmethod
+    def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
+        return (
+            api_base
+            or get_secret_str("SILICONFLOW_API_BASE")
+            or SiliconFlowConfig.API_BASE_URL
+        )
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        resolved_api_base = SiliconFlowConfig.get_api_base(api_base)
+        resolved_api_key = SiliconFlowConfig.get_api_key(api_key)
+        return resolved_api_base, resolved_api_key
+
+    def get_supported_openai_params(self, model: str) -> list:
+        return [
+            "max_tokens",
+            "n",
+            "temperature",
+            "top_p",
+            "stream",
+            "logprobs",
+            "top_logprobs",
+            "frequency_penalty",
+            "presence_penalty",
+            "response_format",
+            "stop",
+            "logit_bias",
+            "tools",
+            "tool_choice",
+        ]

litellm/types/utils.py

@@ -3335,6 +3335,7 @@ class LlmProviders(str, Enum):
     GRADIENT_AI = "gradient_ai"
     LLAMA = "meta_llama"
     NSCALE = "nscale"
+    SILICONFLOW = "siliconflow"
     PG_VECTOR = "pg_vector"
     S3_VECTORS = "s3_vectors"
     HELICONE = "helicone"

litellm/utils.py

@@ -8331,6 +8331,10 @@ class ProviderConfigManager:
             ),
             LlmProviders.GRADIENT_AI: (lambda: litellm.GradientAIConfig(), False),
             LlmProviders.NSCALE: (lambda: litellm.NscaleConfig(), False),
+            LlmProviders.SILICONFLOW: (
+                lambda: litellm.SiliconFlowConfig(),
+                False,
+            ),
             LlmProviders.HEROKU: (lambda: litellm.HerokuChatConfig(), False),
             LlmProviders.OCI: (lambda: litellm.OCIChatConfig(), False),
             LlmProviders.HYPERBOLIC: (lambda: litellm.HyperbolicChatConfig(), False),

tests/test_litellm/llms/siliconflow/chat/test_siliconflow_chat_transformation.py

@@ -0,0 +1,100 @@
+import os
+import sys
+from unittest.mock import patch
+
+sys.path.insert(0, os.path.abspath("../../../../.."))
+
+import litellm
+from litellm import get_llm_provider, get_supported_openai_params
+from litellm.llms.siliconflow.chat.transformation import SiliconFlowConfig
+
+
+class TestSiliconFlowConfig:
+    def setup_method(self):
+        self.config = SiliconFlowConfig()
+
+    def test_custom_llm_provider(self):
+        assert self.config.custom_llm_provider == "siliconflow"
+
+    def test_get_api_key(self):
+        assert self.config.get_api_key("test-key") == "test-key"
+
+        with patch(
+            "litellm.llms.siliconflow.chat.transformation.get_secret_str",
+            return_value="env-key",
+        ):
+            assert self.config.get_api_key() == "env-key"
+
+        with patch.dict(os.environ, {"SILICONFLOW_API_KEY": "env-key"}, clear=False):
+            assert self.config.get_api_key() == "env-key"
+
+    def test_get_api_base_precedence(self):
+        # Explicit argument wins over everything.
+        assert (
+            self.config.get_api_base("https://custom-base.com/v1")
+            == "https://custom-base.com/v1"
+        )
+
+        # SILICONFLOW_API_BASE override (e.g. the China mainland endpoint).
+        with patch(
+            "litellm.llms.siliconflow.chat.transformation.get_secret_str",
+            return_value="https://api.siliconflow.cn/v1",
+        ):
+            assert self.config.get_api_base() == "https://api.siliconflow.cn/v1"
+
+        # Falls back to the default global endpoint.
+        with patch(
+            "litellm.llms.siliconflow.chat.transformation.get_secret_str",
+            return_value=None,
+        ):
+            assert self.config.get_api_base() == SiliconFlowConfig.API_BASE_URL
+            assert SiliconFlowConfig.API_BASE_URL == "https://api.siliconflow.com/v1"
+
+    def test_get_openai_compatible_provider_info(self):
+        with patch.dict(os.environ, {"SILICONFLOW_API_KEY": "sk-secret"}, clear=False):
+            api_base, api_key = self.config._get_openai_compatible_provider_info(
+                api_base=None, api_key=None
+            )
+        assert api_base == "https://api.siliconflow.com/v1"
+        assert api_key == "sk-secret"
+
+    def test_supported_params_include_tools(self):
+        params = self.config.get_supported_openai_params(
+            model="deepseek-ai/DeepSeek-V3"
+        )
+        for expected in ("temperature", "stream", "tools", "tool_choice"):
+            assert expected in params
+
+
+class TestSiliconFlowProviderResolution:
+    def test_get_llm_provider_resolves_prefixed_model(self):
+        with patch.dict(os.environ, {"SILICONFLOW_API_KEY": "sk-secret"}, clear=False):
+            model, provider, api_key, api_base = get_llm_provider(
+                model="siliconflow/deepseek-ai/DeepSeek-V3"
+            )
+        assert model == "deepseek-ai/DeepSeek-V3"
+        assert provider == "siliconflow"
+        assert api_key == "sk-secret"
+        assert api_base == "https://api.siliconflow.com/v1"
+
+    def test_get_llm_provider_detects_provider_from_api_base(self):
+        _, provider, _, _ = get_llm_provider(
+            model="deepseek-ai/DeepSeek-V3",
+            api_base="https://api.siliconflow.com/v1",
+            api_key="sk-secret",
+        )
+        assert provider == "siliconflow"
+
+    def test_get_supported_openai_params_routes_to_config(self):
+        params = get_supported_openai_params(
+            model="deepseek-ai/DeepSeek-V3", custom_llm_provider="siliconflow"
+        )
+        assert params is not None
+        assert "tools" in params
+
+    def test_provider_registered_in_enum_and_lists(self):
+        from litellm.types.utils import LlmProviders
+
+        assert LlmProviders.SILICONFLOW.value == "siliconflow"
+        assert "siliconflow" in litellm.openai_compatible_providers
+        assert "api.siliconflow.com/v1" in litellm.openai_compatible_endpoints