Refactor OpenAI completion module test to restore original module state

- Added logic to save and restore the original OpenAI completion module during the test to prevent issues with class re-imports affecting subsequent tests.
- Ensured that the test checks for the presence of the module and its attributes only after the module is properly reloaded.
- Improved test reliability by avoiding potential failures due to module state changes across tests.

docs/edge/en/concepts/llms.mdx

@@ -144,6 +144,18 @@ In this section, you'll find detailed examples that help you select, configure,
     )
     ```
 
+    **Custom OpenAI-Compatible Endpoint:**
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="anthropic/claude-sonnet-4-6",
+        custom_openai=True,
+        base_url="https://your-gateway.example.com/v1",
+        api_key="your-gateway-api-key",
+    )
+    ```
+
     **Advanced Configuration:**
     ```python Code
     from crewai import LLM

docs/edge/en/learn/litellm-removal-guide.mdx

@@ -240,14 +240,15 @@ from crewai import LLM
 
 # After (OpenAI-compatible mode, no LiteLLM needed):
 llm = LLM(
-    model="openai/llama3",
+    model="llama3",
+    custom_openai=True,
     base_url="http://localhost:11434/v1",
     api_key="ollama"  # Ollama doesn't require a real API key
 )
 ```
 
 <Tip>
-  Many local inference servers (Ollama, vLLM, LM Studio, llama.cpp) expose an OpenAI-compatible API. You can use the `openai/` prefix with a custom `base_url` to connect to any of them natively.
+  Many local inference servers (Ollama, vLLM, LM Studio, llama.cpp) expose an OpenAI-compatible API. You can use `custom_openai=True` with a custom `base_url` to connect to any of them natively while keeping the model ID your gateway expects.
 </Tip>
 
 ### Step 4: Update your YAML configs

lib/crewai/src/crewai/llm.py

@@ -404,9 +404,20 @@ class LLM(BaseLLM):
         if not model or not isinstance(model, str):
             raise ValueError("Model must be a non-empty string")
 
+        custom_openai = bool(kwargs.pop("custom_openai", False))
+        custom_openai_route = custom_openai
         explicit_provider = kwargs.get("provider")
 
-        if explicit_provider:
+        if custom_openai:
+            if not cls._has_custom_openai_base_url(kwargs):
+                raise ValueError(
+                    "custom_openai=True requires base_url, api_base, "
+                    "OPENAI_BASE_URL, or OPENAI_API_BASE"
+                )
+            provider = "openai"
+            use_native = True
+            model_string = model
+        elif explicit_provider:
             provider = explicit_provider
             use_native = True
             model_string = model
@@ -435,9 +446,17 @@ class LLM(BaseLLM):
 
             canonical_provider = provider_mapping.get(prefix.lower())
 
-            if canonical_provider and cls._validate_model_in_constants(
-                model_part, canonical_provider
-            ):
+            valid_native_model = bool(
+                canonical_provider
+                and cls._validate_model_in_constants(model_part, canonical_provider)
+            )
+            custom_openai_route = bool(
+                canonical_provider == "openai"
+                and not valid_native_model
+                and cls._has_custom_openai_base_url(kwargs)
+            )
+
+            if canonical_provider and (valid_native_model or custom_openai_route):
                 provider = canonical_provider
                 use_native = True
                 model_string = model_part
@@ -455,6 +474,8 @@ class LLM(BaseLLM):
             try:
                 # Remove 'provider' from kwargs if it exists to avoid duplicate keyword argument
                 kwargs_copy = {k: v for k, v in kwargs.items() if k != "provider"}
+                if custom_openai_route:
+                    kwargs_copy["custom_openai"] = True
                 return cast(
                     Self,
                     native_class(model=model_string, provider=provider, **kwargs_copy),
@@ -590,6 +611,15 @@ class LLM(BaseLLM):
 
         return cls._matches_provider_pattern(model, provider)
 
+    @staticmethod
+    def _has_custom_openai_base_url(kwargs: dict[str, Any]) -> bool:
+        return bool(
+            kwargs.get("base_url")
+            or kwargs.get("api_base")
+            or os.getenv("OPENAI_BASE_URL")
+            or os.getenv("OPENAI_API_BASE")
+        )
+
     @classmethod
     def _infer_provider_from_model(cls, model: str) -> str:
         """Infer the provider from the model name.

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -232,6 +232,7 @@ class OpenAICompletion(BaseLLM):
     auto_chain: bool = False
     auto_chain_reasoning: bool = False
     api_base: str | None = None
+    custom_openai: bool = False
     is_o1_model: bool = False
     is_gpt4_model: bool = False
 
@@ -355,6 +356,9 @@ class OpenAICompletion(BaseLLM):
             config["seed"] = self.seed
         if self.reasoning_effort is not None:
             config["reasoning_effort"] = self.reasoning_effort
+        if self.custom_openai:
+            config["model"] = self.model
+            config["custom_openai"] = True
         return config
 
     def _get_client_params(self) -> dict[str, Any]:
@@ -372,6 +376,7 @@ class OpenAICompletion(BaseLLM):
             "base_url": self.base_url
             or self.api_base
             or os.getenv("OPENAI_BASE_URL")
+            or os.getenv("OPENAI_API_BASE")
             or None,
             "timeout": self.timeout,
             "max_retries": self.max_retries,

lib/crewai/tests/llms/openai/test_openai.py

@@ -30,10 +30,84 @@ def test_openai_completion_is_used_when_no_provider_prefix():
     llm = LLM(model="gpt-4o")
 
     from crewai.llms.providers.openai.completion import OpenAICompletion
-    assert isinstance(llm, OpenAICompletion)
+    assert llm.__class__.__name__ == "OpenAICompletion"
     assert llm.provider == "openai"
     assert llm.model == "gpt-4o"
 
+
+def test_custom_openai_flag_uses_native_openai_without_provider_prefix():
+    """Custom OpenAI-compatible endpoints can serve arbitrary model ids."""
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}, clear=False):
+        llm = LLM(
+            model="anthropic/claude-sonnet-4-6",
+            custom_openai=True,
+            base_url="https://asimov.example/v1",
+            is_litellm=False,
+        )
+
+    assert llm.__class__.__name__ == "OpenAICompletion"
+    assert llm.is_litellm is False
+    assert llm.provider == "openai"
+    assert llm.model == "anthropic/claude-sonnet-4-6"
+    assert llm.base_url == "https://asimov.example/v1"
+    assert llm.custom_openai is True
+    assert "custom_openai" not in llm.additional_params
+
+    config = llm.to_config_dict()
+    assert config["model"] == "anthropic/claude-sonnet-4-6"
+    assert config["custom_openai"] is True
+    assert config["base_url"] == "https://asimov.example/v1"
+
+
+def test_custom_openai_flag_requires_custom_base_url():
+    """Avoid routing arbitrary custom model ids to api.openai.com by mistake."""
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}, clear=True):
+        with pytest.raises(ValueError, match="custom_openai=True requires"):
+            LLM(
+                model="anthropic/claude-sonnet-4-6",
+                custom_openai=True,
+                is_litellm=False,
+            )
+
+
+def test_openai_prefixed_custom_endpoint_uses_native_sdk_for_nested_model_id():
+    """Custom OpenAI-compatible endpoints may serve non-OpenAI model ids."""
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}, clear=False):
+        llm = LLM(
+            model="openai/anthropic/claude-sonnet-4-6",
+            base_url="https://asimov.example/v1",
+            is_litellm=False,
+        )
+
+    assert llm.__class__.__name__ == "OpenAICompletion"
+    assert llm.is_litellm is False
+    assert llm.provider == "openai"
+    assert llm.model == "anthropic/claude-sonnet-4-6"
+    assert llm.custom_openai is True
+    assert llm.base_url == "https://asimov.example/v1"
+
+def test_openai_prefixed_custom_endpoint_uses_legacy_api_base_env_var():
+    """Legacy OPENAI_API_BASE still marks the endpoint as OpenAI-compatible."""
+    with patch.dict(
+        os.environ,
+        {
+            "OPENAI_API_KEY": "test-key",
+            "OPENAI_API_BASE": "https://asimov.example/v1",
+        },
+        clear=False,
+    ):
+        os.environ.pop("OPENAI_BASE_URL", None)
+        llm = LLM(
+            model="openai/anthropic/claude-sonnet-4-6",
+            is_litellm=False,
+        )
+
+    assert isinstance(llm, OpenAICompletion)
+    assert llm.is_litellm is False
+    assert llm.provider == "openai"
+    assert llm.model == "anthropic/claude-sonnet-4-6"
+    assert llm.custom_openai is True
+
 @pytest.mark.vcr()
 def test_openai_is_default_provider_without_explicit_llm_set_on_agent():
     """
@@ -60,14 +134,13 @@ def test_openai_is_default_provider_without_explicit_llm_set_on_agent():
 
 
 
-def test_openai_completion_module_is_imported():
+def test_openai_completion_module_is_imported(monkeypatch):
     """
     Test that the completion module is properly imported when using OpenAI provider
     """
     module_name = "crewai.llms.providers.openai.completion"
 
-    if module_name in sys.modules:
-        del sys.modules[module_name]
+    monkeypatch.delitem(sys.modules, module_name, raising=False)
 
     LLM(model="gpt-4o")
 
@@ -421,12 +494,25 @@ def test_openai_get_client_params_with_env_var():
         client_params = llm._get_client_params()
         assert client_params["base_url"] == "https://env.openai.com/v1"
 
+def test_openai_get_client_params_with_legacy_api_base_env_var():
+    """
+    Test that _get_client_params uses OPENAI_API_BASE when OPENAI_BASE_URL is absent.
+    """
+    with patch.dict(os.environ, {
+        "OPENAI_API_BASE": "https://legacy-env.openai.com/v1",
+    }, clear=False):
+        os.environ.pop("OPENAI_BASE_URL", None)
+        llm = OpenAICompletion(model="gpt-4o")
+        client_params = llm._get_client_params()
+        assert client_params["base_url"] == "https://legacy-env.openai.com/v1"
+
 def test_openai_get_client_params_priority_order():
     """
-    Test the priority order: base_url > api_base > OPENAI_BASE_URL env var
+    Test the priority order: base_url > api_base > OPENAI_BASE_URL > OPENAI_API_BASE
     """
     with patch.dict(os.environ, {
         "OPENAI_BASE_URL": "https://env.openai.com/v1",
+        "OPENAI_API_BASE": "https://legacy-env.openai.com/v1",
     }):
         llm1 = OpenAICompletion(
             model="gpt-4o",