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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.
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.
:tiger: Sara - the Rasa Demo Bot: An example of a contextual AI assistant built with the open source Rasa Stack
| Date | Stars |
|---|---|
| 2026-07-31 | 990 |
| 2026-08-04 | 990 |
| 2026-08-06 | 990 |
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# Sara - the Rasa Demo Bot ## :surfer: Introduction The purpose of this repo is to showcase a contextual AI assistant built with the open source Rasa framework. Sara is an alpha version and lives in our docs, helping developers getting started with our open source tools. It supports the following user goals: - Understanding the Rasa framework - Getting started with Rasa - Answering some FAQs around Rasa - Directing technical questions to specific documentation - Subscribing to the Rasa newsletter - Requesting a call with Rasa's sales team - Handling basic chitchat You can find planned enhancements for Sara in the [Project Board](https://github.com/RasaHQ/rasa-demo/projects/1) ## 👷 Installation To install Sara, please clone the repo and run: ```sh cd rasa-demo make install ``` This will install the bot and all of its requirements. Note that this bot should be used with python 3.6 or 3.7. ## 🤖 To run Sara: Use `rasa train` to train a model (this will take a significant amount of memory to train, if you want to train it faster, try the training command with `--augmentation 0`). Then, to run, first set up your action server in one terminal window: ```bash rasa run actions --actions actions.actions ``` There are some custom actions that require connections to external services, specifically `SubscribeNewsletterForm` and `SalesForm`. For these to run you would need to have your own MailChimp newsletter and a Google sheet to connect to. See the [development](#development) section for instructions on providing credentials for external services. In another window, run the bot: ```bash docker run -p 8000:8000 rasa/duckling rasa shell --debug ``` Note that `--debug` mode will produce a lot of output meant to help you understand how the bot is working under the hood. To simply talk to the bot, you can remove this flag. If you would like to run Sara on your website, follow the instructions [here](https://github.com/botfront/rasa-webchat) to place the chat widget on your website. ## To test Sara: After doing a `rasa train`, run the command: ```bash rasa test nlu -u test/test_data.json --model models rasa test core --stories test/test_stories.md ``` ## 👩💻 Overview of the files `data/core/` - contains stories `data/nlu` - contains NLU training data `actions` - contains custom action code `domain.yml` - the domain file, including bot response templates `config.yml` - training configurations for the NLU pipeline and policy ensemble ## Development To install requirements for development, run: ```sh make install-dev ``` To run custom actions locally, put a file called .env in the root of your local directory with values for the following environment variables. Most actions will work without them, but if you are working on actions connecting to external APIs you will need credentials. ``` GDRIVE_CREDENTIALS=#json access key for Google Drive API for action_submit_sales_form MAILCHIMP_LIST=#id of mailchimp list for action_submit_subscribe_newsletter_form MAILCHIMP_API_KEY=#api key for mailchimp ALGOLIA_APP_ID=#algolia app ID for action_docs_search ALGOLIA_SEARCH_KEY=#algolia search key ALGOLIA_DOCS_INDEX=#algolia search index RASA_X_HOST=#Rasa X domain e.g. localhost:5002 RASA_X_PASSWORD=#password for authenticating into Rasa X RASA_X_USERNAME=#username for authenticating into Rasa X RASA_X_HOST_SCHEMA=#Rasa X address schema (http/https) ``` To run unit tests for custom actions: ``` make test-actions ``` To ensure proper database cleanup during testing, you will need to include a connection URL for your tracker store database in your .env file e.g. ``` TRACKER_DB_URL=postgresql:///tracker ``` This is not necessary for running the actions. ## ⚫️ Code Style To ensure a standardized code style we use the formatter [black](https://github.com/ambv/black). If you want to automatically format your code on every commit, you can use [pre-commit](https://pre-commit.com/). Just install it via `pip install pre-com
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Would you bet a product on this? Bounded 0–100 and slow moving.
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