refactor(crusoe): simplify to JSON-based provider registration

Replace hand-written CrusoeChatConfig class and manual registrations
across constants.py, __init__.py, get_llm_provider_logic.py, and
_lazy_imports_registry.py with a single entry in
litellm/llms/openai_like/providers.json, consistent with the
recommended pattern for OpenAI-compatible providers.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

litellm/__init__.py

@@ -577,7 +577,6 @@ publicai_models: Set = set()
 v0_models: Set = set()
 morph_models: Set = set()
 lambda_ai_models: Set = set()
-crusoe_models: Set = set()
 hyperbolic_models: Set = set()
 black_forest_labs_models: Set = set()
 recraft_models: Set = set()
@@ -825,8 +824,6 @@ def add_known_models(model_cost_map: Optional[Dict] = None):
             morph_models.add(key)
         elif value.get("litellm_provider") == "lambda_ai":
             lambda_ai_models.add(key)
-        elif value.get("litellm_provider") == "crusoe":
-            crusoe_models.add(key)
         elif value.get("litellm_provider") == "hyperbolic":
             hyperbolic_models.add(key)
         elif value.get("litellm_provider") == "black_forest_labs":
@@ -1062,7 +1059,6 @@ models_by_provider: dict = {
     "v0": v0_models,
     "morph": morph_models,
     "lambda_ai": lambda_ai_models,
-    "crusoe": crusoe_models,
     "hyperbolic": hyperbolic_models,
     "black_forest_labs": black_forest_labs_models,
     "recraft": recraft_models,

litellm/_lazy_imports_registry.py

@@ -1135,7 +1135,6 @@ _LLM_CONFIGS_IMPORT_MAP = {
     "MorphChatConfig": (".llms.morph.chat.transformation", "MorphChatConfig"),
     "RAGFlowConfig": (".llms.ragflow.chat.transformation", "RAGFlowConfig"),
     "LambdaAIChatConfig": (".llms.lambda_ai.chat.transformation", "LambdaAIChatConfig"),
-    "CrusoeChatConfig": (".llms.crusoe.chat.transformation", "CrusoeChatConfig"),
     "HyperbolicChatConfig": (
         ".llms.hyperbolic.chat.transformation",
         "HyperbolicChatConfig",

litellm/constants.py

@@ -560,7 +560,6 @@ LITELLM_CHAT_PROVIDERS = [
     "oci",
     "morph",
     "lambda_ai",
-    "crusoe",
     "vercel_ai_gateway",
     "wandb",
     "ovhcloud",
@@ -719,7 +718,6 @@ openai_compatible_endpoints: List = [
     "https://api.v0.dev/v1",
     "https://api.morphllm.com/v1",
     "https://api.lambda.ai/v1",
-    "https://managed-inference-api-proxy.crusoecloud.com/v1/",
     "https://api.hyperbolic.xyz/v1",
     "https://ai-gateway.helicone.ai/",
     "https://ai-gateway.vercel.sh/v1",
@@ -775,7 +773,6 @@ openai_compatible_providers: List = [
     "helicone",
     "morph",
     "lambda_ai",
-    "crusoe",
     "hyperbolic",
     "vercel_ai_gateway",
     "aiml",
@@ -804,7 +801,6 @@ openai_text_completion_compatible_providers: List = (
         "chutes",
         "v0",
         "lambda_ai",
-        "crusoe",
         "hyperbolic",
         "wandb",
     ]

litellm/litellm_core_utils/get_llm_provider_logic.py

@@ -315,9 +315,6 @@ def get_llm_provider(  # noqa: PLR0915
                     elif endpoint == "https://api.lambda.ai/v1":
                         custom_llm_provider = "lambda_ai"
                         dynamic_api_key = get_secret_str("LAMBDA_API_KEY")
-                    elif endpoint == "https://managed-inference-api-proxy.crusoecloud.com/v1/":
-                        custom_llm_provider = "crusoe"
-                        dynamic_api_key = get_secret_str("CRUSOE_API_KEY")
                     elif endpoint == "https://api.hyperbolic.xyz/v1":
                         custom_llm_provider = "hyperbolic"
                         dynamic_api_key = get_secret_str("HYPERBOLIC_API_KEY")
@@ -883,13 +880,6 @@ def _get_openai_compatible_provider_info(  # noqa: PLR0915
         ) = litellm.LambdaAIChatConfig()._get_openai_compatible_provider_info(
             api_base, api_key
         )
-    elif custom_llm_provider == "crusoe":
-        (
-            api_base,
-            dynamic_api_key,
-        ) = litellm.CrusoeChatConfig()._get_openai_compatible_provider_info(
-            api_base, api_key
-        )
     elif custom_llm_provider == "hyperbolic":
         (
             api_base,

litellm/llms/crusoe/chat/transformation.py

@@ -1,42 +0,0 @@
-"""
-Translate from OpenAI's `/v1/chat/completions` to Crusoe's `/v1/chat/completions`
-"""
-
-from typing import Optional, Tuple
-
-from litellm.secret_managers.main import get_secret_str
-
-from ...openai_like.chat.transformation import OpenAILikeChatConfig
-
-
-class CrusoeChatConfig(OpenAILikeChatConfig):
-    """
-    Crusoe is OpenAI-compatible with standard endpoints.
-
-    Docs: https://docs.crusoecloud.com/managed-inference/overview/index.html
-    """
-
-    @property
-    def custom_llm_provider(self) -> Optional[str]:
-        return "crusoe"
-
-    def _get_openai_compatible_provider_info(
-        self, api_base: Optional[str], api_key: Optional[str]
-    ) -> Tuple[Optional[str], Optional[str]]:
-        api_base = (
-            api_base
-            or get_secret_str("CRUSOE_API_BASE")
-            or "https://managed-inference-api-proxy.crusoecloud.com/v1/"
-        )  # type: ignore
-        dynamic_api_key = api_key or get_secret_str("CRUSOE_API_KEY")
-        return api_base, dynamic_api_key
-
-    def get_supported_openai_params(self, model: str) -> list:
-        return [
-            "messages",
-            "model",
-            "temperature",
-            "top_p",
-            "frequency_penalty",
-            "presence_penalty",
-        ]

litellm/llms/openai_like/providers.json

@@ -101,5 +101,10 @@
     "param_mappings": {
       "max_completion_tokens": "max_tokens"
     }
+  },
+  "crusoe": {
+    "base_url": "https://managed-inference-api-proxy.crusoecloud.com/v1/",
+    "api_key_env": "CRUSOE_API_KEY",
+    "api_base_env": "CRUSOE_API_BASE"
   }
 }

tests/llm_translation/test_crusoe.py

@@ -4,24 +4,29 @@ Tests for Crusoe provider integration
 import os
 from unittest import mock
 
-import pytest
-
 import litellm
-from litellm import completion
-from litellm.llms.crusoe.chat.transformation import CrusoeChatConfig
 
 CRUSOE_API_BASE = "https://managed-inference-api-proxy.crusoecloud.com/v1/"
 
 
-def test_crusoe_config_initialization():
-    """Test CrusoeChatConfig initializes correctly"""
-    config = CrusoeChatConfig()
-    assert config.custom_llm_provider == "crusoe"
+def test_crusoe_json_registry():
+    """Test CrusoeChatConfig is loaded from JSON provider registry"""
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    assert JSONProviderRegistry.exists("crusoe")
+    config = JSONProviderRegistry.get("crusoe")
+    assert config is not None
+    assert config.base_url == CRUSOE_API_BASE
+    assert config.api_key_env == "CRUSOE_API_KEY"
+    assert config.api_base_env == "CRUSOE_API_BASE"
 
 
 def test_crusoe_get_openai_compatible_provider_info():
     """Test Crusoe provider info retrieval"""
-    config = CrusoeChatConfig()
+    from litellm.llms.openai_like.dynamic_config import create_config_class
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
 
     # Test with default values (no env vars set)
     with mock.patch.dict(os.environ, {}, clear=True):
@@ -67,22 +72,6 @@ def test_get_llm_provider_crusoe():
     assert model == "meta-llama/Llama-3.3-70B-Instruct"
     assert provider == "crusoe"
 
-    # Test with api_base containing Crusoe endpoint
-    model, provider, api_key, api_base = get_llm_provider(
-        "meta-llama/Llama-3.3-70B-Instruct",
-        api_base=CRUSOE_API_BASE,
-    )
-    assert model == "meta-llama/Llama-3.3-70B-Instruct"
-    assert provider == "crusoe"
-    assert api_base == CRUSOE_API_BASE
-
-
-def test_crusoe_in_provider_lists():
-    """Test that Crusoe is registered in all necessary provider lists"""
-    assert "crusoe" in litellm.openai_compatible_providers
-    assert "crusoe" in litellm.provider_list
-    assert CRUSOE_API_BASE in litellm.openai_compatible_endpoints
-
 
 def test_crusoe_models_configuration():
     """Test that Crusoe models are configured correctly"""
@@ -91,9 +80,6 @@ def test_crusoe_models_configuration():
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
     litellm.model_cost = litellm.get_model_cost_map(url="")
 
-    litellm.crusoe_models = set()
-    litellm.add_known_models()
-
     crusoe_models = [
         "crusoe/meta-llama/Llama-3.3-70B-Instruct",
         "crusoe/deepseek-ai/DeepSeek-R1-0528",
@@ -111,54 +97,3 @@ def test_crusoe_models_configuration():
             f"{model} should have crusoe as provider"
         )
         assert model_info.get("mode") == "chat", f"{model} should be in chat mode"
-
-
-def test_crusoe_model_list_populated():
-    """Test that crusoe_models list is populated correctly"""
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    litellm.crusoe_models = set()
-    litellm.add_known_models()
-
-    assert len(litellm.crusoe_models) > 0, "crusoe_models list should not be empty"
-
-    for model in litellm.crusoe_models:
-        assert model.startswith("crusoe/"), (
-            f"Model {model} should start with 'crusoe/'"
-        )
-
-    expected_models = [
-        "crusoe/meta-llama/Llama-3.3-70B-Instruct",
-        "crusoe/deepseek-ai/DeepSeek-R1-0528",
-        "crusoe/deepseek-ai/DeepSeek-V3-0324",
-        "crusoe/Qwen/Qwen3-235B-A22B-Instruct-2507",
-        "crusoe/moonshotai/Kimi-K2-Thinking",
-        "crusoe/openai/gpt-oss-120b",
-        "crusoe/google/gemma-3-12b-it",
-    ]
-
-    for model in expected_models:
-        assert model in litellm.crusoe_models, (
-            f"{model} should be in crusoe_models list"
-        )
-
-
-@pytest.mark.asyncio
-async def test_crusoe_completion_call():
-    """Test completion call with Crusoe provider (requires CRUSOE_API_KEY)"""
-    if not os.getenv("CRUSOE_API_KEY"):
-        pytest.skip("CRUSOE_API_KEY not set")
-
-    try:
-        response = await litellm.acompletion(
-            model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
-            messages=[{"role": "user", "content": "Hello, this is a test"}],
-            max_tokens=10,
-        )
-        assert response.choices[0].message.content
-        assert response.model
-        assert response.usage
-    except Exception as e:
-        if "crusoe" not in str(e) and "provider" not in str(e).lower():
-            raise

tests/test_litellm/llms/crusoe/test_crusoe.py

@@ -0,0 +1,111 @@
+import os
+import sys
+
+sys.path.insert(0, os.path.abspath("../../../../.."))
+from unittest.mock import patch
+
+CRUSOE_API_BASE = "https://managed-inference-api-proxy.crusoecloud.com/v1/"
+
+
+def test_crusoe_json_registry():
+    """Test Crusoe is registered in the JSON provider registry"""
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    assert JSONProviderRegistry.exists("crusoe")
+    config = JSONProviderRegistry.get("crusoe")
+    assert config is not None
+    assert config.base_url == CRUSOE_API_BASE
+    assert config.api_key_env == "CRUSOE_API_KEY"
+    assert config.api_base_env == "CRUSOE_API_BASE"
+
+
+def test_crusoe_dynamic_config_defaults():
+    """Test dynamic config returns correct default API base"""
+    from litellm.llms.openai_like.dynamic_config import create_config_class
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
+
+    with patch.dict(os.environ, {}, clear=True):
+        api_base, api_key = config._get_openai_compatible_provider_info(None, None)
+
+    assert api_base == CRUSOE_API_BASE
+    assert api_key is None
+
+
+def test_crusoe_dynamic_config_env_vars():
+    """Test dynamic config reads CRUSOE_API_KEY and CRUSOE_API_BASE from env"""
+    from litellm.llms.openai_like.dynamic_config import create_config_class
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
+
+    with patch.dict(
+        os.environ,
+        {"CRUSOE_API_KEY": "test-key", "CRUSOE_API_BASE": "https://custom.crusoe.com/v1/"},
+    ):
+        api_base, api_key = config._get_openai_compatible_provider_info(None, None)
+
+    assert api_base == "https://custom.crusoe.com/v1/"
+    assert api_key == "test-key"
+
+
+def test_crusoe_dynamic_config_explicit_params():
+    """Test explicit params override env vars"""
+    from litellm.llms.openai_like.dynamic_config import create_config_class
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
+
+    with patch.dict(os.environ, {"CRUSOE_API_KEY": "env-key"}):
+        api_base, api_key = config._get_openai_compatible_provider_info(
+            "https://override.crusoe.com/v1/", "override-key"
+        )
+
+    assert api_base == "https://override.crusoe.com/v1/"
+    assert api_key == "override-key"
+
+
+def test_crusoe_supported_params():
+    """Test dynamic config returns standard OpenAI params"""
+    from litellm.llms.openai_like.dynamic_config import create_config_class
+    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
+
+    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
+    params = config.get_supported_openai_params(model="meta-llama/Llama-3.3-70B-Instruct")
+
+    assert isinstance(params, list)
+    assert len(params) > 0
+    assert "temperature" in params
+    assert "max_tokens" in params
+    assert "stream" in params
+
+
+def test_crusoe_provider_detection_by_prefix():
+    """Test crusoe/model prefix is correctly routed"""
+    from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+
+    model, provider, _, _ = get_llm_provider("crusoe/meta-llama/Llama-3.3-70B-Instruct")
+    assert provider == "crusoe"
+    assert model == "meta-llama/Llama-3.3-70B-Instruct"
+
+
+def test_crusoe_model_list_populated():
+    """Test Crusoe models are present in model_prices_and_context_window.json"""
+    import litellm
+
+    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
+    litellm.model_cost = litellm.get_model_cost_map(url="")
+
+    expected = [
+        "crusoe/meta-llama/Llama-3.3-70B-Instruct",
+        "crusoe/deepseek-ai/DeepSeek-R1-0528",
+        "crusoe/deepseek-ai/DeepSeek-V3-0324",
+        "crusoe/Qwen/Qwen3-235B-A22B-Instruct-2507",
+        "crusoe/moonshotai/Kimi-K2-Thinking",
+        "crusoe/openai/gpt-oss-120b",
+        "crusoe/google/gemma-3-12b-it",
+    ]
+    for model in expected:
+        assert model in litellm.model_cost, f"{model} not found in model_cost"
+        assert litellm.model_cost[model].get("litellm_provider") == "crusoe"