improving custom OpenAI urls (#6490)

* Support legacy OpenAI base URL env var

* Add custom OpenAI-compatible endpoint support

* 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.

* addressing comments

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
@@ -295,6 +296,92 @@ crewai run
 uv run pytest
 ```
 
+## Custom OpenAI-Compatible Endpoints
+
+Many providers and local servers (Ollama, vLLM, LM Studio, llama.cpp, LiteLLM proxies, and hosted gateways) expose an **OpenAI-compatible** API. Instead of routing these through LiteLLM, you can talk to them directly with CrewAI's native OpenAI integration by setting `custom_openai=True`.
+
+This is the recommended replacement for any LiteLLM provider that offers an OpenAI-compatible endpoint.
+
+### How it works
+
+- `custom_openai=True` forces CrewAI to use the native OpenAI SDK, regardless of the model name.
+- The model ID is passed to the endpoint without validation against OpenAI's known-model list. This lets you use arbitrary model IDs your gateway expects (for example, `anthropic/claude-sonnet-4-6` served behind an OpenAI-compatible proxy). An optional leading `openai/` routing prefix is stripped.
+- A base URL is **required**. CrewAI resolves it, in order, from:
+  1. `base_url=...`
+  2. `api_base=...`
+  3. `OPENAI_BASE_URL` environment variable
+  4. `OPENAI_API_BASE` environment variable (legacy)
+
+  If none are set, CrewAI raises a `ValueError` so misconfiguration fails fast instead of silently hitting `api.openai.com`.
+
+```python
+from crewai import LLM
+
+llm = LLM(
+    model="anthropic/claude-sonnet-4-6",  # passed through as-is
+    custom_openai=True,
+    base_url="https://your-gateway.example/v1",
+    api_key="your-key",
+)
+```
+
+### Connect to common servers
+
+<Tabs>
+  <Tab title="Ollama">
+    ```python
+    from crewai import LLM
+
+    llm = LLM(
+        model="llama3.2:latest",
+        custom_openai=True,
+        base_url="http://localhost:11434/v1",
+        api_key="ollama",  # Ollama ignores it, but the client requires a value
+    )
+    ```
+  </Tab>
+  <Tab title="vLLM">
+    ```python
+    from crewai import LLM
+
+    llm = LLM(
+        model="meta-llama/Meta-Llama-3.1-8B-Instruct",
+        custom_openai=True,
+        base_url="http://localhost:8000/v1",
+        api_key="not-needed",
+    )
+    ```
+  </Tab>
+  <Tab title="LM Studio">
+    ```python
+    from crewai import LLM
+
+    llm = LLM(
+        model="your-loaded-model",
+        custom_openai=True,
+        base_url="http://localhost:1234/v1",
+        api_key="lm-studio",
+    )
+    ```
+  </Tab>
+  <Tab title="Env vars">
+    ```bash
+    export OPENAI_BASE_URL="https://your-gateway.example/v1"
+    export OPENAI_API_KEY="your-key"
+    ```
+    ```python
+    from crewai import LLM
+
+    # base_url is picked up from OPENAI_BASE_URL / OPENAI_API_BASE
+    llm = LLM(model="anthropic/claude-sonnet-4-6", custom_openai=True)
+    ```
+  </Tab>
+</Tabs>
+
+<Tip>
+  If you use the `openai/` prefix with a model that isn't a known OpenAI model and pass `base_url` or `api_base` directly, CrewAI automatically treats it as a custom OpenAI-compatible endpoint. Environment variables alone do not enable automatic routing for unknown models; set `custom_openai=True` when configuring the endpoint through `OPENAI_BASE_URL` or `OPENAI_API_BASE`.
+</Tip>
+
 ## Quick Reference: Model String Mapping
 
 Here are common migration paths from LiteLLM-dependent providers to native ones:
@@ -321,7 +408,8 @@ llm = LLM(model="anthropic/claude-sonnet-4-20250514")  # High quality
 # Ollama → OpenAI-compatible (keep using local models)
 # llm = LLM(model="ollama/llama3")
 llm = LLM(
-    model="openai/llama3",
+    model="llama3",
+    custom_openai=True,
     base_url="http://localhost:11434/v1",
     api_key="ollama"
 )
@@ -349,6 +437,9 @@ llm = LLM(
   <Accordion title="What about environment variables like OPENAI_API_KEY?">
     Native providers use the same environment variables you're already familiar with. No changes needed for `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, etc.
   </Accordion>
+  <Accordion title="How do I connect to Groq, Together AI, or other OpenAI-compatible providers without LiteLLM?">
+    Most of these providers expose an OpenAI-compatible API. Use `custom_openai=True` with their base URL and API key — see [Custom OpenAI-Compatible Endpoints](#custom-openai-compatible-endpoints). For example, Groq: `LLM(model="llama-3.1-70b-versatile", custom_openai=True, base_url="https://api.groq.com/openai/v1", api_key="...")`. The model ID is passed through untouched, so use whatever ID the provider expects.
+  </Accordion>
 </AccordionGroup>
 
 ## Related Resources