langkit
An open-source toolkit for monitoring Large Language Models ensuring safety and security
GraphCanon updated 3w · GitHub synced 3w
Decision brief
LangKit is an open-source toolkit designed for monitoring large language models by extracting signals from prompts and responses to ensure their quality, relevance, and sentiment analysis.
Good fit when
- When you need a comprehensive observability tool specifically crafted with features targeting text quality, relevance metrics, and sentiment analysis of LLM outputs.
- If your application involves prompt engineering or requires safeguards against potential issues like prompt injection and ensuring the safety and security of model responses.
Avoid when
- When the focus is exclusively on training models rather than observing their behavior and performance post-training, as LangKit specializes in monitoring and not enhancing training processes.
- In scenarios where minimal dependencies are necessary. LangKit's comprehensive feature set comes packaged with a broader dependency list that may be excessive for simpler needs.
- Requirements:
- Installation instructions suggest using pip to install LangKit.; The 'langkit[all]' package installation implies a full version that includes all optional dependencies.
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (617d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/whylabs/langkitSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
LangKit extracts signals from prompts & responses of LLMs to ensure their quality, relevance, and sentiment analysis, focusing on observability.
Capability facts
- Languages
- jupyter notebook, python
Source: github.language+pyproject.toml · Aug 2, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 2, 2026)
To install LangKit, use the Python Package Index (PyPI) as follows:Source link
Tags
README
Installation 💻
To install LangKit, use the Python Package Index (PyPI) as follows:
pip install langkit[all]
For agents
This page has a .md twin and JSON over the API.