Updates on OpenAI apigee compatibility

docs/agents/models/apigee.md

@@ -18,13 +18,12 @@ Apigee proxy, you immediately gain enterprise-grade capabilities:
 
 - **Monitoring & Visibility:** Get granular monitoring, analysis, and auditing of all your AI requests.
 
-!!! note
+   The `ApigeeLLM` wrapper is designed for use with Agent Platform
+   and the Gemini API (generateContent). We are continually expanding support for
+   other models and interfaces. For OpenAI compatible models, including self-hosted or 
+   other providers, use the `CompletionsHTTPClient` to route traffic through your Apigee proxy.
 
-    The `ApigeeLLM` wrapper is currently designed for use with Agent Platform
-    and the Gemini API (generateContent). We are continually expanding support for
-    other models and interfaces.
-
-## Example implementation
+## Implementation example
 
 Integrate Apigee's governance into your agent's workflow by instantiating the
 `ApigeeLlm` wrapper object and pass it to an `LlmAgent` or other agent type.
@@ -84,3 +83,42 @@ Apigee first, where all necessary policies (security, rate limiting, logging)
 are executed before the request is securely forwarded to the underlying AI model
 endpoint. For a full code example using the Apigee proxy, see
 [Hello World Apigee LLM](https://github.com/google/adk-python/tree/main/contributing/samples/models/hello_world_apigeellm).
+
+## Compatibility with OpenAI
+
+The `CompletionsHTTPClient` is a generic HTTP client designed for compatibility with the OpenAI API format. It allows you to route requests through proxies (such as Apigee) that expect standard OpenAI-compatible `/chat/completions` endpoints, rather than native Gemini or Vertex AI protocols. This client handles:
+
+- **Payload construction**: Converts LlmRequest objects into the format required by OpenAI-compatible APIs.
+- **Response handling**: Manages streaming and non-streaming responses from the proxy.
+- **Reliability**: Uses `tenacity` for built-in retry logic.
+- **Normalization**: Parses responses and streaming chunks into the standard format expected by the rest of the ADK framework.
+
+### Implementation example
+
+```python
+
+import asyncio
+from google.adk.models.apigee_llm import CompletionsHTTPClient
+from google.adk.models.llm_request import LlmRequest
+from google.genai import types
+
+async def test_client():
+    # 1. Initialize the client
+    client = CompletionsHTTPClient(
+        base_url="https://your-apigee-proxy-url.com/v1",
+        headers={"Authorization": "Bearer YOUR_API_KEY"}
+    )
+
+    # 2. Construct a minimal request
+    request = LlmRequest(
+        model="gpt-4o",  # Replace with your target model ID
+        contents=[types.Content(role="user", parts=[types.Part.from_text(text="Hello!")])]
+    )
+
+    # 3. Execute a non-streaming generation
+    async for response in client.generate_content_async(request, stream=False):
+        print(f"Response: {response.text}")
+
+if __name__ == "__main__":
+    asyncio.run(test_client())
+```