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[bot] Instrument Azure AI Agents SDK (219,062 weekly downloads)

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#2,605 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
48/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
azure, javascript, typescript
Área
devtools, observability

Línea de trabajo

Start by reading js/src/auto-instrumentations/configs/all.ts and js/src/span-origin.ts, then compare existing SDK instrumentation with the Azure AI Agents create, thread, run, and streaming APIs described in the linked upstream docs. The issue identifies e2e/scenarios/* as the place to check coverage. Done means the agent execution surface is instrumented and represented in the registry and end-to-end scenarios.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

typescript

Summary

@azure/ai-agents is Microsoft's official TypeScript/JavaScript SDK for Azure AI Foundry's Agent Service — a stateful, server-run agent surface (analogous to OpenAI's Assistants/Responses agent model) where you create an agent, create a thread, and execute runs that the service drives end-to-end (including tool calls such as file search and code interpreter), optionally streamed. This execution surface is not instrumented anywhere in this repository. This is distinct from Azure OpenAI/Azure AI Foundry model-routing support, which Braintrust already documents as an AI provider (gateway/billing config), not a client-side agent-run tracing integration.

What's missing

  • AgentsClient.createAgent(...) — registers an agent (model + instructions + tools).
  • Thread + run execution (client.threads.create(), client.runs.create()/createAndRun, streaming runs) — the actual agent-execution surface, where the service plans, calls the model, and executes tool calls (file search, code interpreter, function tools) before returning.
  • The higher-level @azure/ai-projects client, which wraps @azure/ai-agents behind a .agents property for the same create/run/stream surface.

None of @azure/ai-agents, @azure/ai-projects, AgentsClient, or azure-ai-agents appear anywhere in js/src/, js/src/auto-instrumentations/configs/all.ts (the instrumentation registry), js/src/span-origin.ts (INSTRUMENTATION_NAMES), or any e2e/scenarios/* directory.

Weekly downloads

Weekly downloads: 219,062 (as of 2026-10-12; window 2026-10-04–2026-10-10; source https://api.npmjs.org/downloads/point/last-week/@azure/ai-agents)

Braintrust docs status

not_found — Checked https://www.braintrust.dev/docs/integrations/ai-providers/azure, which covers Azure OpenAI/Azure AI Foundry as a model provider (chat completions via AzureOpenAIClient, Entra Workload Identity auth for the Braintrust gateway) — no mention of the Agents/Agent Service SDK, threads, or runs. Also checked https://www.braintrust.dev/docs/guides/traces/integrations (full agent-framework integration list: Agno, OpenAI Agents SDK, Claude Agent SDK, Pi Coding Agent SDK, Deep Agents, LangGraph, CrewAI, AutoGen, AgentScope, Google ADK, LiveKit Agents, Mastra, Pipecat, Pydantic AI, Strands Agents SDK, Cloudflare Agents/AI Chat) — Azure AI Agents is absent.

Upstream sources

Local repo files inspected

  • js/src/auto-instrumentations/configs/all.ts (full instrumentation registry — no Azure Agents entry)
  • js/src/span-origin.ts (INSTRUMENTATION_NAMES — no Azure Agents entry)
  • Repo-wide case-insensitive search for @azure/ai-agents, @azure/ai-projects, AgentsClient, azure-ai-agents across the working tree (zero matches)
  • e2e/scenarios/ directory listing (no Azure-Agents-named scenario)
Lenguaje dominante
TypeScript
Estrellas
29
Forks
16
Merge medio
1 d 22 h
PR fusionados (30 d)
72

Preparar el entorno

  • Incluye un Dockerfile o un archivo de Docker Compose
  • Sin plantilla de pull request
  • Sin guía de contribución

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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