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Installation

This section outlines the installation process for both the Ayushma front-end and back-end components.

Front-end Installation​

Prerequisites​

  • Node.js and npm (or yarn): Ayushma is built using JavaScript and requires Node.js and a package manager (npm or yarn) to be installed. Download and install the latest LTS version of Node.js from the official website: https://nodejs.org/
  • Git: Ayushma's source code is hosted on GitHub, so you'll need Git to clone the repository. Download and install Git from the official website: https://git-scm.com/

Installation Steps​

  1. Clone the Repository: Open a terminal or command prompt and navigate to the directory where you want to install Ayushma. Then, clone the repository using the following command:
git clone https://github.com/ohcnetwork/ayushma_fe.git
  1. Navigate to the Project Directory:
cd ayushma_fe
  1. Install Dependencies: Install the required dependencies using either npm or yarn:
# Using npm
npm install
# Using yarn
yarn install

This command will download and install all the necessary packages for Ayushma's front-end to run.

Back-end Installation​

Prerequisites​

  • Python 3.8+: Ayushma's back-end is built using Python. Ensure you have Python 3.8 or a newer version installed. Download and install Python from the official website: https://www.python.org/
  • Postgres 15+: Ayushma utilizes PostgreSQL as its database system. Install PostgreSQL 15 or a newer version. Download and install PostgreSQL from the official website: https://www.postgresql.org/
  • OpenAI Account with API Key: Ayushma integrates with OpenAI for its AI capabilities. You'll need an OpenAI account with a valid API key. Create an account and obtain your API key from the OpenAI website: https://openai.com/
  • Pinecone Account with API Key: Ayushma uses Pinecone for vector storage. You'll need a Pinecone account with a valid API key and an active index. Sign up and set up your index on the Pinecone website: https://www.pinecone.io/

Optional Prerequisites:​

  • Docker: For simplified deployment and environment management, consider using Docker. Download and install Docker from the official website: https://www.docker.com/
  • AWS SES Account: If you want to enable email functionality, such as password resets, you'll need an AWS SES account.
  • AWS S3 Account: For document storage, you can optionally use AWS S3.
  • Google Cloud Account with Speech-to-Text API Access: To enable speech-to-text functionality, you'll need a Google Cloud account with access to the Speech-to-Text API.

Installation Steps​

  1. Create a Virtual Environment: It is recommended to create a virtual environment to isolate Ayushma's dependencies from other Python projects. Use the following command:

python3 -m venv .venv

  1. Activate the Virtual Environment:
# On Linux/macOS
source .venv/bin/activate
# On Windows
.venv\Scripts\activate
  1. Install Requirements: Install the required Python packages using pip:

pip install -r requirements/local.txt

  1. Set Environment Variables: Ayushma's back-end relies on several environment variables for configuration. You can set these variables in your virtual environment's activation script or using a tool like python-dotenv. Refer to the README file in the back-end code for a complete list of environment variables and their descriptions.
  2. Create Database: Use the psql command-line tool or a PostgreSQL client to create a new database for Ayushma.

CREATE DATABASE ayushma;

  1. Apply Migrations: Run the following command to apply the database migrations:

python manage.py migrate

This command will create the necessary tables and schema in the database.

  1. Create Superuser: Create a superuser account for managing Ayushma through the admin interface.

python manage.py createsuperuser

Follow the prompts to set the username, email, and password for the superuser account.

Additional Configuration​

  • Email Configuration (Optional): If you have set up an AWS SES account and want to enable email sending, configure the email settings in core/settings/local.py or core/settings/production.py according to your SES credentials.
  • Document Storage (Optional): If you prefer to use AWS S3 for document storage, configure the S3 settings in your environment variables and settings file.
  • Google Cloud Speech-to-Text (Optional): To enable speech-to-text functionality, set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your Google Cloud credentials JSON file.

Verification​

  1. Start the Development Server:

python manage.py runserver

This will start the Django development server, making the back-end API accessible at http://127.0.0.1:8000/.