Testing Langkit

WhyLogs Telemetry for the ML stack: It is an open-source tool for profiling your data and creating Telemetry about production systems at scale at massive scale. So this is an open-source tool for doing that Telemetry collection and summarization.
LangKit Observability and security for LLMs: It is an open-source tool that is built on top of Whylogs, specifically with metrics for hallucinations data, Quality Security, sentiment, governments of language models.
WhyLabs aI Observatory Monitoring and actionable production workflows that use the two products on top for monitoring.

For some exercises, you might need to send LangKit profiles to WhyLabs. We will need three pieces of information:

You can sign in and grab a free account to obtain those. You can create the next when required:

Create a new project and note its ID (if it's a model project, it will look like model-xxxx)
Create an API token from the "Access Tokens" tab
Copy your org ID from the same "Access Tokens" tab

You can see the video for the first notebook at 46:00 min where the setup of your dashboard where you will send LangKit profiles.

As part of exploring LangKit capabilities, the next issue was raised.

Name		Name	Last commit message	Last commit date
.gitignore		.gitignore
00_Intro_to_LLM_Monitoring_LangKit_and_WhyLabs.ipynb		00_Intro_to_LLM_Monitoring_LangKit_and_WhyLabs.ipynb
01_Trying_LangKit_Sentiment_Toxicity.ipynb		01_Trying_LangKit_Sentiment_Toxicity.ipynb
02_Trying_LangKit_Intro.ipynb		02_Trying_LangKit_Intro.ipynb
03_Trying_LangKit_Logging_text.ipynb		03_Trying_LangKit_Logging_text.ipynb
04_Trying_LangKit_LLM_to_WhyLabs.ipynb		04_Trying_LangKit_LLM_to_WhyLabs.ipynb
05_Trying_LangKit_Detecting_Jailbreaks_and_Prompt_Injections.ipynb		05_Trying_LangKit_Detecting_Jailbreaks_and_Prompt_Injections.ipynb
06_Trying_LangKit_Detecting_Behavioural_Monitoring.ipynb		06_Trying_LangKit_Detecting_Behavioural_Monitoring.ipynb
README.md		README.md

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