https://github.com/ai4bharat/anudesh

An open source platform to annotate data for Large language models - at scale

https://github.com/ai4bharat/anudesh

Science Score: 13.0%

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    Low similarity (15.5%) to scientific vocabulary

Keywords

data-annotation llm llm-evaluation
Last synced: 9 months ago · JSON representation

Repository

An open source platform to annotate data for Large language models - at scale

Basic Info
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  • Stars: 4
  • Watchers: 5
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
data-annotation llm llm-evaluation
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Anudesh

An open source platform to annotate and label LLM data at scale

License: MIT


Anudesh is an open source platform to annotate Lare language models' data at scale, built with a vision to enhance digital presence of under-represented languages in India.

Cloning this Master Repo

git clone --recurse-submodules https://github.com/AI4Bharat/Anudesh

Backend Setup

Clone the Anudesh-Backend repository from GitHub to your local machine.

git clone https://github.com/AI4Bharat/Anudesh-Backend.git

Create a virtual environment for the project. Replace with your preferred environment name.

python3 -m venv 

Activate the virtual environment. This ensures that the packages you install are isolated from the global Python environment.

source /bin/activate

Install all required Python packages listed in the requirements-dev.txt file.

pip install -r deploy/requirements-dev.txt

Set up the environment variables needed for the project by copying the example environment file.

cp .env.example ./backend/.env

Generate a new secret key for Django (within the virtual environment):

Open a Python shell.

python backend/manage.py shell

# Import the utility function to generate a secret key.
>> from django.core.management.utils import get_random_secret_key

# Generate and print a new secret key.
>> get_random_secret_key()

Copy the generated secret key and paste it into the .env file as the value for SECRET_KEY.

Docker Installation

Build the Docker containers as defined in the docker-compose-local.yml file.

docker-compose -f docker-compose-local.yml build

Run the containers in detached mode (-d flag). This will start up all the services defined in the Docker Compose file.

docker-compose -f docker-compose-local.yml up -d

Run Migrations

The following steps are required only when you run the project for the first time or after making changes to the models.

# Check if there are any pending migrations.
docker-compose exec web python backend/manage.py makemigrations 

# Apply all pending migrations to the database.
docker-compose exec web python backend/manage.py migrate

Create a superuser for accessing the Django admin interface (required only once).

docker-compose exec web python backend/manage.py createsuperuser

Run the Django development server within the Docker container.

docker-compose exec web python backend/manage.py runserver

Frontend Setup

Clone the Anudesh-Frontend repository from GitHub to your local machine.

git clone https://github.com/AI4Bharat/Anudesh-Frontend.git

Change directory to the newly cloned Anudesh-Frontend folder.

cd Anudesh-Frontend

Install the necessary dependencies for the project.

The --force flag is used to bypass conflicts with the existing dependencies.

npm i --force

Start the development server. This will run the frontend application on a local server.

npm run dev

Owner

  • Name: AI4Bhārat
  • Login: AI4Bharat
  • Kind: organization
  • Email: opensource@ai4bharat.org
  • Location: India

Artificial-Intelligence-For-Bhārat : Building open-source AI solutions for India!

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Last synced: 9 months ago

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  • kartikvirendrar (1)
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