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[bot] Cerebras Cloud TypeScript SDK (`@cerebras/cerebras_cloud_sdk`) not instrumented — no tracing for fast-inference chat completions or embeddings (126,155 weekly downloads)

Aperta
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#2,101 2 commenti 0 reazioni 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
68/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
node.js, typescript
Ambito
observability

Direzione di ricerca

Inizia leggendo le configurazioni esistenti in js/src/auto-instrumentations/configs/, in particolare openai.ts, groq.ts e mistral.ts, quindi esamina js/src/wrappers/ e js/src/instrumentation/plugins/ per individuare i pattern corrispondenti. Aggiungi la copertura per Cerebras chat completions, streaming, completions ed embeddings, con una configurazione di auto-instrumentation e uno scenario e2e in e2e/scenarios/; il lavoro è completo quando le chiamate dirette a @cerebras/cerebras_cloud_sdk producono span Braintrust.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Summary

Cerebras publishes an official TypeScript SDK for their ultra-fast LLM inference API: @cerebras/cerebras_cloud_sdk on npm (v1.64.1, actively maintained). It provides execution APIs for chat completions, completions, embeddings, and streaming responses. The SDK has its own HTTP client based on node-fetch — it does not depend on the openai npm package. This repository has zero instrumentation for any Cerebras SDK surface — no wrapper, no channels, no plugin, no auto-instrumentation config. Users who call @cerebras/cerebras_cloud_sdk directly get no Braintrust spans.

What instrumentation is missing

The @cerebras/cerebras_cloud_sdk npm package exposes these execution surfaces, none of which are instrumented:

SDK Method Description
client.chat.completions.create({ model, messages }) Chat completions with tool use, structured outputs, and reasoning
client.chat.completions.create({ ..., stream: true }) Streaming chat completions
client.completions.create({ model, prompt }) Raw text completions
client.embeddings.create(...) Text embeddings

Cerebras is notable for extremely low-latency LLM inference (their wafer-scale hardware delivers tokens significantly faster than GPU-based providers), making observability especially valuable for latency-sensitive production workloads.

No coverage in any instrumentation layer:

  • No wrapper function (e.g. wrapCerebras())
  • No diagnostics channels for Cerebras methods
  • No plugin handler in js/src/instrumentation/plugins/
  • No auto-instrumentation config in js/src/auto-instrumentations/configs/
  • No e2e test scenarios
  • Grep for cerebras (case-insensitive) across js/src/ returns zero matches

Indirect coverage is insufficient:

Braintrust's Cerebras integration page documents a gateway/OpenAI SDK approach only — using the openai npm client pointed at the Braintrust gateway to route to Cerebras models. Users who call @cerebras/cerebras_cloud_sdk directly get no spans at all. The Cerebras SDK has its own separate HTTP layer (runtime deps: node-fetch, abort-controller, agentkeepalive, form-data-encoder, formdata-node) and is not patched by the existing openai auto-instrumentation.

Braintrust docs status

not_found for direct SDK instrumentation. The Braintrust Cerebras integration page documents a gateway/OpenAI SDK approach only and does not reference @cerebras/cerebras_cloud_sdk.

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 Cerebras config present
  • js/src/wrappers/ — no cerebras.ts wrapper file
  • js/src/instrumentation/plugins/ — no Cerebras channels or plugin
  • e2e/scenarios/ — no Cerebras test scenarios
  • Full repo grep for cerebras (case-insensitive) in js/src/ — zero matches
  • Cerebras SDK package.json (GitHub) — confirmed runtime deps are node-fetch/agentkeepalive/form-data-encoder; no openai dependency
Lingua principale
TypeScript
Stelle
28
Fork
15
Merge medio
1g 20h
PR unite (30g)
70

Preparare l'ambiente

  • Include un Dockerfile o un file Docker Compose
  • Nessun modello di pull request
  • Nessuna guida per i contributori

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  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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