> 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/older-versions/contribute/source-code/workflows/manage-learn/ml-anaylatics-service/setup-guide.md).

# Setup Guide

## Pre-requisites :

* Core Python
* Pyspark
* Druid
* Kafka
* MongoDB

## System Requirements :

* Java version 1.8. 0 or More
* Python 3.6
* Druid
* Kafka

## How to set up

First clone project

`git clone` [`https://github.com/shikshalokam/ml-analytics-service.git`](https://github.com/shikshalokam/ml-analytics-service.git)

Checkout latest version or repo

* install python and pip
* add alias python=python3.8 in \~/.bashrc file
* Refresh with source .bashrc command \[Try `python -V` && `pip -V` to confirm the installation]
* Install virtual environment using `pip install virtual env` command or `sudo apt install python3.8-venv` command
* Create a virtual environment using the `python -m venv spark_venv` command
* Activate virtual environment using source `spark_venv/bin/activate` command
* Install the required dependency using `sudo pip install -r requirements.txt`
* Use the `pip list` command to recheck if the dependencies are installed correctly
* Create a config.ini file and add config paths ( In the ml-analytics dir )


---

# 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 dynamically by asking a question.

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

```
GET https://ed.sunbird.org/older-versions/contribute/source-code/workflows/manage-learn/ml-anaylatics-service/setup-guide.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.