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PacificAI / langtest

Deliver safe & effective language models

Why this job: topics: mlops, benchmarks

What it does

  • Generate and execute more than 60 distinct types of tests only with 1 line of code
  • Test all aspects of model quality. robustness, bias, representation, fairness and accuracy.​
  • Automatically augment training data based on test results (for select models)​
  • Support for popular NLP frameworks for NER, Translation and Text-Classifcation: Spark NLP, Hugging Face & Transformers.
  • Support for testing LLMS ( OpenAI, Cohere, AI21, Hugging Face Inference API and Azure-OpenAI LLMs) for question answering, toxicity, clinical-tests, legal-support, factuality, sycophancy, summarization and other popular tests.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 2 months ago
Stars
561
On GitHub
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
2.8.0
Released 2 months ago
Built with
Python
100% of the code

Is it looked after?

Contributors
Not stated
Last 90 days
Issues
99% closed
6 still open
Pull requests
659 merged
1 waiting
Releases
29
1 in the last year

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More: languages, topics and project record

Languages

  • Python 100%
  • Makefile <1%
  • Batchfile <1%
  • Shell <1%

Topics

  • benchmarks
  • ethics-in-ai
  • large-language-models
  • ml-safety
  • ml-testing
  • mlops
  • model-assessment
  • nlp
  • responsible-ai
  • llm-test
  • ai-safety
  • ai-testing

Project record

  • JobEvals and observability
  • StatusListed
  • Commits5,973
  • Forks53
  • Watching8
  • Stars in 28 days0
  • CreatedNov 18, 2022
  • First seen by usNov 7, 2026
  • CheckedNov 8, 2026

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