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Documentation Index

Fetch the complete documentation index at: https://docs.lunary.ai/llms.txt

Use this file to discover all available pages before exploring further.

Tags allow you to label queries and completions. This is useful to further segment your data. For example, you can label all the queries that are related to a specific feature or a specific company. Later on, this can also be useful for creating fine-tune datasets.
1

Setup the SDK

Python

Learn how to install the Python SDK.

JavaScript

Learn how to install the JS SDK.
2

Simplest: Identify OpenAI calls

The easiest way to get started adding tags is to send them when doing your OpenAI API calls.
const res = await openai.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "Hello" }],
  tags: ["some-tag"]
})
If you’re using LangChain, you can similarly pass the tags on any LangChain object.
const chat = new ChatOpenAI({
  callbacks: [new LunaryHandler()],
});

const res = await chat.call([new HumanMessage("Hello!")], {
tags: ["some-tag"],
});
3

Advanced: Inject tag into context

You can also inject tags into the context of your code. This is useful if you want to tag all the queries that are related to a specific feature or a specific company.
Coming soon