[bot] Instrument Baseten Performance Client (87,159 weekly downloads)

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Bewertung

Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Anfängerfreundlichkeit
25/100
Issue-Typ
Feature
Klarheit
Größtenteils klar
Aktivitätsstatus
Aktiv
Tech-Stack
python
Bereich
observability

Rechercherichtung

Start with the existing integrations under py/src/braintrust/integrations/ and the matrix in py/pyproject.toml to see how a wrapper is registered, then check py/noxfile.py for the session pattern. The issue lists five sync/async PerformanceClient entrypoints that need spans, so decide which ones to cover first. Done means a traced test session that runs against the package, but the scope and approach need maintainer input first.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Beschreibung

python

Summary

baseten-performance-client (import name baseten_performance_client) is Baseten's dedicated high-throughput Python client for embeddings, reranking, and classification inference against Baseten-hosted models. It is a Rust-backed (pyo3/reqwest/tokio) client distinct from both the general-purpose baseten management SDK and from calling Baseten endpoints through an OpenAI-compatible interface. This repository has zero instrumentation for it — no integration directory, wrapper, nox session, or matrix entry, and not even an incidental mention anywhere under py/.

This is a distinct execution surface from Braintrust's existing Baseten support: Braintrust currently only documents Baseten as a gateway-routed model provider for chat completions (see docs status below) — it does not cover this package's embeddings/reranking/classification execution API at all. It is also distinct from already-instrumented embedding/rerank libraries (cohere rerank, voyageai — itself still an open gap in #482) since it talks to Baseten-hosted deployments specifically via its own PerformanceClient class.

What is missing

The PerformanceClient class exposes paired sync/async execution entrypoints, none of which produce a Braintrust span today:

  • PerformanceClient.embed() / async_embed() — embedding execution against Baseten Embedding Inference deployments
  • PerformanceClient.rerank() / async_rerank() — document reranking execution
  • PerformanceClient.classify() / async_classify() — classification execution
  • PerformanceClient.batch_system_one() / async_batch_system_one() — batched "System One" decision execution
  • PerformanceClient.batch_post() / async_batch_post() — generic batched JSON request execution (e.g. against Engine-Builder-LLM completion endpoints)

All of these are high-concurrency batch execution calls (default max_concurrent_requests=256, configurable retries/hedging/timeouts via RequestProcessingPreference) that are the primary way applications drive bulk embedding/rerank/classification workloads through Baseten — currently entirely invisible to Braintrust tracing.

Weekly downloads

Weekly downloads: 87,159 (fetched 2026-11-02; https://pypistats.org/api/packages/baseten_performance_client/recent)

Braintrust docs status

not_found — checked:

Upstream sources

Local repo files inspected

  • py/src/braintrust/integrations/ — no baseten/ directory, no file matching baseten* anywhere
  • py/src/braintrust/wrappers/ — no Baseten wrapper
  • py/pyproject.toml [tool.braintrust.matrix] — no baseten entry
  • py/noxfile.py — no test_baseten session
  • Repo-wide case-insensitive grep for baseten under py/ — zero matches of any kind (not even incidental)
Vorherrschende Sprache
Python
Sterne
22
Forks
30
Ø Merge
9 Std.
Gemergte PRs (30 T.)
128

Entwicklungsumgebung

Erste Schritte

  1. Lesen Sie das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreiben Sie ins Issue, dass Sie es übernehmen — das erspart doppelte Arbeit.
  3. Forken Sie das Repository und arbeiten Sie in einem Branch.
  4. Öffnen Sie einen Pull Request, der die Issue-Nummer nennt.

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