Summary
Microsoft publishes a dedicated TypeScript SDK for Azure AI model inference: @azure-rest/ai-inference (part of the Azure SDK for JavaScript). It provides execution APIs for chat completions, streaming, and embeddings for models hosted on Azure AI Foundry (Phi, Mistral, Meta Llama, and others). This package uses a path-based REST client pattern that is architecturally distinct from the openai npm package and is not covered by any existing instrumentation. Users who call @azure-rest/ai-inference directly get no Braintrust spans.
What instrumentation is missing
The @azure-rest/ai-inference package exposes these execution surfaces, none of which are instrumented:
| SDK Method |
Description |
client.path("/chat/completions").post({ body: { messages, ... } }) |
Chat completions for hosted models |
.post({ body: { ..., stream: true } }).asNodeStream() |
Streaming chat completions |
client.path("/embeddings").post({ body: { input, model } }) |
Text embeddings |
Users instantiate it as:
import ModelClient from "@azure-rest/ai-inference";
import { AzureKeyCredential } from "@azure/core-auth";
const client = ModelClient(endpoint, new AzureKeyCredential(apiKey));
const response = await client.path("/chat/completions").post({
body: {
messages: [{ role: "user", content: "Hello" }],
model: "Phi-4",
},
});
Auto-instrumentation gap:
The @azure-rest/ai-inference SDK uses a path-based REST client architecture (from @azure/core-rest-pipeline) that is fundamentally different from the openai package's class-method structure. None of the existing configs in js/src/auto-instrumentations/configs/ target any @azure-rest/* module paths. The existing openai instrumentation targets openai module file paths and does not fire for calls made through @azure-rest/ai-inference.
No coverage in any instrumentation layer:
- No auto-instrumentation config for
@azure-rest/ai-inference in js/src/auto-instrumentations/configs/
- No wrapper function (e.g.
wrapAzureAIInference())
- No channels or plugin for Azure AI Inference methods in
js/src/instrumentation/plugins/
- No e2e test scenarios
- Grep for
azure-rest, @azure, or ai-inference across js/src/ returns zero matches
Braintrust docs status
unclear — The Braintrust integrations page at https://www.braintrust.dev/docs/integrations lists "Azure AI Foundry" as a supported provider, but the JavaScript SDK documentation does not describe any direct instrumentation for the @azure-rest/ai-inference package.
Upstream references
Local files inspected
js/src/auto-instrumentations/configs/ — full config list: anthropic.ts, openai.ts, ai-sdk.ts, groq.ts, mistral.ts, cohere.ts, huggingface.ts, google-genai.ts, google-adk.ts, genkit.ts, openai-agents.ts, openrouter.ts, openrouter-agent.ts, claude-agent-sdk.ts, cursor-sdk.ts, github-copilot.ts, openai-codex.ts, flue.ts — no Azure AI Inference config present
js/src/auto-instrumentations/configs/all.ts — @azure-rest/ai-inference not listed among any instrumentation groups
- Full repo grep for
azure-rest, @azure, ai-inference in js/src/ — zero matches
e2e/scenarios/ — no Azure AI Inference test scenarios
Summary
Microsoft publishes a dedicated TypeScript SDK for Azure AI model inference:
@azure-rest/ai-inference(part of the Azure SDK for JavaScript). It provides execution APIs for chat completions, streaming, and embeddings for models hosted on Azure AI Foundry (Phi, Mistral, Meta Llama, and others). This package uses a path-based REST client pattern that is architecturally distinct from theopenainpm package and is not covered by any existing instrumentation. Users who call@azure-rest/ai-inferencedirectly get no Braintrust spans.What instrumentation is missing
The
@azure-rest/ai-inferencepackage exposes these execution surfaces, none of which are instrumented:client.path("/chat/completions").post({ body: { messages, ... } }).post({ body: { ..., stream: true } }).asNodeStream()client.path("/embeddings").post({ body: { input, model } })Users instantiate it as:
Auto-instrumentation gap:
The
@azure-rest/ai-inferenceSDK uses a path-based REST client architecture (from@azure/core-rest-pipeline) that is fundamentally different from theopenaipackage's class-method structure. None of the existing configs injs/src/auto-instrumentations/configs/target any@azure-rest/*module paths. The existingopenaiinstrumentation targetsopenaimodule file paths and does not fire for calls made through@azure-rest/ai-inference.No coverage in any instrumentation layer:
@azure-rest/ai-inferenceinjs/src/auto-instrumentations/configs/wrapAzureAIInference())js/src/instrumentation/plugins/azure-rest,@azure, orai-inferenceacrossjs/src/returns zero matchesBraintrust docs status
unclear— The Braintrust integrations page at https://www.braintrust.dev/docs/integrations lists "Azure AI Foundry" as a supported provider, but the JavaScript SDK documentation does not describe any direct instrumentation for the@azure-rest/ai-inferencepackage.Upstream references
@azure-rest/ai-inferencesource: https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-restnpm install @azure-rest/ai-inferenceLocal files inspected
js/src/auto-instrumentations/configs/— full config list:anthropic.ts,openai.ts,ai-sdk.ts,groq.ts,mistral.ts,cohere.ts,huggingface.ts,google-genai.ts,google-adk.ts,genkit.ts,openai-agents.ts,openrouter.ts,openrouter-agent.ts,claude-agent-sdk.ts,cursor-sdk.ts,github-copilot.ts,openai-codex.ts,flue.ts— no Azure AI Inference config presentjs/src/auto-instrumentations/configs/all.ts—@azure-rest/ai-inferencenot listed among any instrumentation groupsazure-rest,@azure,ai-inferenceinjs/src/— zero matchese2e/scenarios/— no Azure AI Inference test scenarios