v0.0.25

LangKit release v0.0.25

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Optionally disable CUDA for Encoder metric modules #191 [@richard-rogers]
• Update release workflow to use whylabs automator #190 [@jamie256]
• Add conditional CUDA support with env variable #189 [@richard-rogers]
• Preliminary benchmarking #185 [@richard-rogers]
• Bump version: 0.0.23 → 0.0.24 #187 [@jamie256]

v0.0.24

LangKit release v0.0.24

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Add langkit metadata to schema for inclusion in whylogs profiles #186 [@jamie256]
• security features doc update to include hallucinations #182 [@FelipeAdachi]
• Link reference paper for Hallucinations metric module doc. #181 [@jamie256]
• Add hallucinations to README and update modules list to fix formatting #180 [@jamie256]
• add hallucination docs #179 [@FelipeAdachi]
• Bump version: 0.0.22 → 0.0.23 #183 [@jamie256]

v0.0.23

LangKit release v0.0.23

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Fix duplicate init ResolverSpec registration warning in has_patterns #178 [@jamie256]
• cleanup push-release workflow #176 [@jamie256]
• Allow regexes UDF metric name to be configured in LangKitConfig #173 [@jamie256]
• Fix typo in classname for langkit/response_hallucination.py #172 [@richard-rogers]
• Update injection examples and tests #170 [@jamie256]
• Align injections score name with column it is targeting #168 [@jamie256]
• Hallucination example - small fixes #167 [@FelipeAdachi]
• Bump version: 0.0.21 → 0.0.22 #169 [@jamie256]

v0.0.22

LangKit release v0.0.22

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Add nltk.download of punkt to the response_hallucination init #166 [@jamie256]
• response_hallucination v0 #163 [@FelipeAdachi]
• Remove xformers as it breaks injections module on mac #162 [@jamie256]
• Choosing an LLM example notebook #165 [@jamie256]
• Update guardrails_openai_example_llm_schema.py #164 [@murilommen]
• Bump version: 0.0.20 → 0.0.21 #160 [@w0-automator]

v0.0.21

LangKit release v0.0.21

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Dependency updates: allow python 3.7, update whylogs, examples cleanup #158 [@jamie256]
• Bump version: 0.0.19 → 0.0.20 #157 [@jamie256]
• update sentiment and toxicity example and update modules documentation #156 [@FelipeAdachi]

v0.0.20

LangKit release v0.0.20

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Injection refactor #154 [@FelipeAdachi]
• add FrequentItemsMetric on blocked column #152 [@richard-rogers]
• Add homepage link to pyproject.toml #151 [@jamie256]
• More config cleanup #145 [@richard-rogers]
• docs refactor #144 [@FelipeAdachi]
• bump to 0.0.19 #149 [@FelipeAdachi]

v0.0.19

LangKit release v0.0.19

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• rolling logger in safeguards example from 30 min to 5 min #148 [@FelipeAdachi]

v0.0.18

LangKit release v0.0.18

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• guardrails example with openai api #146 [@FelipeAdachi]
• Add configuration example notebook #139 [@richard-rogers]
• Add test for empty string on toxicity #142 [@jamie256]

v0.0.17

LangKit release v0.0.17

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Safeguard example refactor #140 [@FelipeAdachi]
• Quieter logs in LanKit test suite #135 [@richard-rogers]
• safeguard example fix #137 [@FelipeAdachi]

v0.0.16

LangKit release v0.0.16

🔍 LangKit: An open-source toolkit for monitoring Language Learning Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
This version includes:

• Allow has_patterns to be called on strings #136 [@richard-rogers]
• make clean #134 [@jamie256]
• Simplify create pull-request-action workflow #133 [@jamie256]