An open source project from Data to AI Lab at MIT.

Sintel (Signal Intelligence) provides Restful APIs to process massive signal data for anomaly analysis in an efficient and user-friendly way.

• License: MIT
• Development Status: Pre-Alpha
• Homepage: https://github.com/sintel-dev/sintel

Make sure you have installed all of the following prerequisites on your development machine:

• Python (>= 3.8) - Sintel has been developed and runs on Python 3.8. Although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where MTV is run. To this end, Anaconda python is suggested to maintain the virtual environments.
• Git - Download & Install Git. OSX and Linux machines typically have this already installed.
• MongoDB (>= 4.4) - Download & Install MongoDB, and make sure it's running on the default port (27017).

Once you've downloaded the Sintel repository and installed all the prerequisites, you're just a few steps away from running your application. To install the project, create a virtualenv and execute

$ make install

This command will install all the dependencies needed for the application to run. For development, use the following command instead, which will install some additional dependencies for code linting and testing

$ make install-develop

Download demo data and load it to the mongodb. The database name by default is sintel.

$ make load-db

Please activate your virtualenv, and then launch the API server:

$ sintel run -v

Go to the API playground (http:https://localhost:3000/apidocs) to have a try.

Run the following command for the purpose of development

$ sintel run -E development -v

Once the server runs up, you should be able to open the following API interfaces:

• http:https://localhost:3000/apidocs (Swagger UI style)
• http:https://localhost:3000/redoc (Redoc UI style)

Follow the tutorial .tutorials/Anomaly Detection.ipynb for detail.

• Install Docker and Compose

• Load data into the mongo container

  $ make docker-db-up

  $ make docker-up

Go to the API playground (http:https://localhost:3000/apidocs) to have a try. For further commands, please refer to Makefile, the session of Docker Installation.