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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
🎯🗯 Dataset generation for AI chatbots, NLP tasks, named entity recognition or text classification models using a simple DSL!
| Date | Stars |
|---|---|
| 2026-07-24 | 889 |
| 2026-07-25 | 889 |
| 2026-07-28 | 889 |
| 2026-07-30 | 889 |
| 2026-08-06 | 889 |
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# Chatito [](https://www.npmjs.com/package/chatito) [](https://circleci.com/gh/rodrigopivi/workflows/Chatito) [](https://www.npmjs.com/package/chatito) [](https://www.npmjs.com/package/chatito) [](https://rodrigopivi.github.io/Chatito/) [Try the online IDE!](https://rodrigopivi.github.io/Chatito/) ## Overview Chatito helps you generate datasets for training and validating chatbot models using a simple DSL. If you are building chatbots using commercial models, open source frameworks or writing your own natural language processing model, you need training and testing examples. Chatito is here to help you. This project contains the: - [Online chatito IDE](https://rodrigopivi.github.io/Chatito/) - [Chatito DSL specification](https://github.com/rodrigopivi/Chatito/blob/master/spec.md) - [DSL AST parser in pegjs format](https://github.com/rodrigopivi/Chatito/blob/master/parser/chatito.pegjs) - [Generator implemented in typescript + npm package](https://github.com/rodrigopivi/Chatito/tree/master/src) ### Chatito language For the full language specification and documentation, please refer to the [DSL spec document](https://github.com/rodrigopivi/Chatito/blob/master/spec.md). ## Tips ### Prevent overfit [Overfitting](https://en.wikipedia.org/wiki/Overfitting) is a problem that can be prevented if we use Chatito correctly. The idea behind this tool, is to have an intersection between data augmentation and a description of possible sentences combinations. It is not intended to generate deterministic datasets that may overfit a single sentence model, in those cases, you can have some control over the generation paths only pull samples as required. ### Tools and resources - [Visual Studio Code syntax highlighting plugin](https://marketplace.visualstudio.com/items?itemName=nimfin.chatito) Thanks to [Yuri Golobokov](https://github.com/nimf) for his [work on this](https://github.com/nimf/chatito-vscode). - [AI Blueprints: How to build and deploy AI business projects](https://books.google.com.pe/books?id=sR2CDwAAQBAJ) implements practical full chatbot examples using chatito at chapter 7. - [3 steps to convert chatbot training data between different NLP Providers](https://medium.com/@benoit.alvarez/3-steps-to-convert-chatbot-training-data-between-different-nlp-providers-fa235f67617c) details a simple way to convert the data format to non implemented adapters. You can use a generated dataset with providers like DialogFlow, Wit.ai and Watson. - [Aida-nlp](https://github.com/rodrigopivi/aida) is a tiny experimental NLP deep learning library for text classification and NER. Built with Tensorflow.js, Keras and Chatito. Implemented in JS and Python. ## Adapters The language is independent from the generated output format and because each model can receive different parameters and settings, this are the currently implemented data formats, if your provider is not listed, at the Tools and resources section there is more information on how to support more formats. NOTE: Samples are not shuffled between intents for easier review and because some adapters stream samples directly to the file and it's recommended to split intents in different files for easier review and maintenance. ### [Rasa](https://rasa.com/docs/rasa/) [Rasa](https://rasa.com/docs/rasa/) is an open source machine learning framework for automated text and voice-based conversations. Understand messages, hold conversations, and connect to messaging channels and APIs. Chatito can help you build a dataset for the [Rasa NLU](https://rasa.com/docs/rasa/nlu/about/) component. One particular behavior of the Rasa adapter is that when a slot
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:081db71946b78ac8, topic:nlp, topic:named-entity-recognition, topic:text-classification