# NLP

## **Tokenization and Embeddings**

Textopia Natural Language Processing module employs tokenization techniques to break down textual input into meaningful units. Word embeddings, such as Word2Vec or GloVe, are then used to represent these tokens numerically

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://textopia.gitbook.io/textopia.ai/technical-implementation/nlp.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.