Evaluation & testing
Open-source Python evaluation library for LLM and RAG applications. It runs LLM-based and deterministic metrics over datasets, generates synthetic test sets, and tracks results across experiments so changes can be compared. It is a local library with no hosted control plane, access control or audit trail.
open_source · generally available · Research snapshot 2026-09-06
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Show me a Ragas experiment comparing two retrieval configurations on a generated test set, with per-metric scores and reasons.
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
Ragas documents an experiments-first workflow combining LLM-driven metrics, custom metrics defined with decorators, built-in dataset management and result tracking for LLM applications.
Limit: Docs do not state that spans, tool calls or multi-agent handoffs are captured; scope is dataset-level scoring.
Documented by provider
The repository states Ragas automatically creates test datasets covering a range of scenarios and supports production-aligned test set generation, with objective LLM-based and traditional metrics.
Limit: No published validation of generated test-set representativeness.
Documented by provider
The canonical repository resolves to the vibrantlabsai organization and the library is installed from PyPI or source; no enterprise tier or hosted deployment is documented.
Limit: License text and any commercial offering were not established from the pages fetched.
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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