> For the complete documentation index, see [llms.txt](https://ed.sunbird.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ed.sunbird.org/use/source-code/manage-learn/ml-project-service/data-model.md).

# Data Model

### DB Schema

The schema serves as a blueprint for creating and maintaining the database that supports the ML Projects Services data storage and retrieval operations.

![ML-Projects Service](https://ml-services-uploads.s3.ap-south-1.amazonaws.com/DBSchema/ML-Project.png)

#### Here are examples of sample data for each collection

#### [programs](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/programs.json)

Programs collection is tasked with housing high-level program information, encompassing program specifics, resource listings, and program categorizations.

#### [solutions](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/solutions.json)

The solutions collection will serve as a repository for various types of resources, encompassing observations, improvement projects, and surveys, among others.

#### [projects](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/projects.json)

The projects collection will house projects generated by users, along with their respective status updates.

#### [projectTemplates](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/projectTemplates.json)

The projectTemplates collection will store foundational project structures that will serve as templates for creating individual projects.

#### [certificateTemplates](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/certificateTemplates.json)

The certificateTemplates collection will be established for solutions and associated with certificate templates to facilitate the generation of certificates, incorporating predefined criteria.

#### [projectTemplateTasks](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/projectTemplateTasks.json)

The projectTemplateTasks collection will be used to store tasks associated with a specific project template.

#### [programUsers](https://github.com/shikshalokam/ml-projects-service/blob/master/DBSchema/programUsers.json)

The programUsers Collection holds user data of those who have become part of the program and have provided their consent status.

[Click here](https://ml-services-uploads.s3.ap-south-1.amazonaws.com/DBSchema/ML-Project.pdf) for DB schema and corresponding examples in a PDF format.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://ed.sunbird.org/use/source-code/manage-learn/ml-project-service/data-model.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.