Python: docs: add OpenAI-compatible control plane example#14054
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cerebrixos wants to merge 1 commit into
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Python: docs: add OpenAI-compatible control plane example#14054cerebrixos wants to merge 1 commit into
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Pull request overview
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Adds guidance to the Python “Configuring the Kernel” doc for using a custom OpenAI-compatible client (e.g., when routing through a gateway/control plane), and cleans up the Microsoft Entra authentication link formatting.
Changes:
- Document passing a custom OpenAI-compatible
AsyncOpenAIclient intoOpenAIChatCompletion. - Add an example using Tuning Engines’ OpenAI-compatible endpoint.
- Fix formatting of the Microsoft Entra authentication guide link.
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| You can also pass a custom OpenAI-compatible client to `OpenAIChatCompletion` when your organization routes model calls through a gateway or control plane for centralized model access, policy, audit trails, quota enforcement, or cost reporting. | ||
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| For example, [Tuning Engines](https://www.tuningengines.com/) exposes an OpenAI-compatible endpoint: |
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| from openai import AsyncOpenAI | ||
| from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion |
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This adds a small manual-configuration example showing how to pass a custom AsyncOpenAI client to OpenAIChatCompletion for an OpenAI-compatible gateway or control plane.\n\nWhy this may be useful:\n- Semantic Kernel already supports custom OpenAI clients through the async_client parameter.\n- Production teams often route model traffic through centralized controls for model access, policy, audit trails, quotas, routing, and cost reporting.\n- The example keeps Semantic Kernel responsible for orchestration, functions, plugins, memory, and agents while the external control plane handles organization-wide governance.\n\nThe change is docs-only and uses placeholder environment variables.