UpTrain · Rate Limits

Uptrain Rate Limits

UpTrain does not publish documented rate limits for its managed evaluation API. The open-source framework is self-hosted and effectively bounded only by the rate limits of whichever LLM provider you supply a key for (OpenAI, Anthropic, Azure OpenAI, Mistral, etc.) when grading. For the managed service (demo.uptrain.ai), any per-account throttling is set by UpTrain and is not reconciled in this artifact.

Uptrain Rate Limits is the machine-readable rate-limit profile for UpTrain on the APIs.io network, conforming to the API Commons Rate Limits specification.

It captures 2 rate-limit definitions, measuring requests.

The profile also includes 2 backoff/retry policies defined and response codes documented for throttled.

Tagged areas include AI, LLM, Evaluation, LLM Evaluation, and Open Source.

2 Limits Throttle: 429
AILLMEvaluationLLM EvaluationOpen SourceRate LimitingQuotasThrottling

Limits

Managed Evaluation Requests account
requests
see provider documentation
No documented per-account limit for the managed evaluate / log_and_evaluate endpoints.
Upstream LLM Grading Limits account
requests
depends on configured LLM provider
In the open-source framework, grading calls go to your own LLM provider key and inherit that provider's rate limits.

Policies

Provider-Bound Limits
Open-source evaluation throughput is bound by the upstream LLM provider's rate limits, not by UpTrain itself.
Backoff Strategy
Clients should implement exponential backoff with jitter and honor Retry-After on 429 responses.

Sources