Important
At its early developmental stage, this project is still experimental and lacks many implemented features. Contributions are encouraged to advance its progress.
- About
- Key Features
- Roadmap for Development
- Getting Started
- Best Practices for Engaging with Darwin
- Help and Support
- License
Darwin is the first in the series of multiple AI Engineers with the capability to comprehend complex human commands, dissect them into actionable steps, conduct research, and generate code to accomplish the specified task all powered by LLMs.
The idea behind Darwin is to create an AI SWE Intern to assist in basic tasks. Whether you require assistance in creating a new feature, resolving a bug, or building an entire project from the ground up, Darwin is ready to support you every step of the way.
Note
Darwin is built by taking inspiration from Devin and Devika. Starting as an alternative to a Software Engineering Intern, we aim to eventually reach the competency of an SDE/ML/AI Engineer.
- 🧠 Capable of comprehending complex codebases and architectures
- 🔧 Skillful in managing changes, updates, and bug fixes within software projects
- 📚 Conducts thorough research to gather pertinent information
- 💡 Engages in brainstorming sessions to generate innovative ideas
- 💻 Writes code in multiple programming languages proficiently
- ⚙️ Executing code and debugging using internet to assess discussions and forums, just like software engineers do 😉!
-
Solving GitHub Issues: Enhance the ability to track, manage, and resolve GitHub issues efficiently within the software.
-
Building Model Pipelines: Develop a feature to create and optimize model pipelines for improved performance and productivity.
-
Training Models: Implement functionality for training models with diverse datasets to enhance accuracy and performance.
Darwin comes wrapped in a docker container with an image you can pull from the dockerhub using
sudo docker pull shankerabhigyan/darwin:latest
sudo docker pull shankerabhigyan/ui:latest
Or build and run the container yourself using
sudo docker build --no-cache -f Dockerfile.darwin -t darwin .
sudo docker build -f Dockerfile.ui -t ui .
After you have configured your .env file, referring to the steps below, you can spin up these containers using
sudo docker run --env-file .env -v ./data:/app/data -p 8080:80 darwin
sudo docker run -p 3000:3000 ui
Your app should now be live on localhost:3000
Version's requirements
- Python >= 3.9 and < 3.12
- NodeJs >= 18
To install npm
# installs NVM (Node Version Manager)
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
# download and install Node.js
nvm install 20
# verifies the right Node.js version is in the environment
node -v # should print `v20.12.2`
# verifies the right NPM version is in the environment
npm -v # should print `10.5.0`
# download and install Node.js
choco install nodejs-lts --version="20.12.2"
# verifies the right Node.js version is in the environment
node -v # should print `v20.12.2`
# verifies the right NPM version is in the environment
npm -v # should print `10.5.0`
To install Darwin, follow these steps:
- Clone the Darwin repository:
git clone https://github.com/Cognation/darwin.git
- Navigate to the project directory:
cd darwin
- Create a virtual environment/conda environment and install the required dependencies (you can use any virtual environment manager):
conda create -n darwin python=3.11
conda activate darwin
- Install the dependencies Installing python packages:
pip install -r requirements.txt
- Setup the frontend
cd ui
npm install
Now you just need to add your OpenAI key to a .env file, you can use this command:
echo "OPENAI_API_KEY='<your_OpenAI_key>' " > .env
export OPENAI_API_KEY=<your_OpenAI_key>
All your data is stored on your machine, initialise your database using:
mkdir ./data && touch ./data/data.db && echo '{}' > ./data/data.db
This version comes with changes that would require you to delete any previous data.db file you created.
You can start using Darwin with these two lines of command
python3 server.py
cd ui
npm start
Darwin is an early-stage AI Assistant chatbot designed to support your advanced development inquiries. To enhance your experience, please consider the following guidelines:
- Ensure that your queries are comprehensive and detailed, covering all aspects of your request.
- Include links to any relevant issues or references to enable Darwin to provide more accurate and tailored responses.
- If you encounter any difficulties, please raise issues or contact us. Your feedback is invaluable in helping us refine and improve your experience.
Should you have any queries, feedback, or ideas, do not hesitate to contact us. You can submit an issue through the issue tracker or participate in our discussions for overall conversations.
Furthermore, we also host a Discord server for the Darwin community, providing a platform for users to interact, exchange experiences, seek assistance, and engage in project collaboration. To join the Darwin community Discord server, simply click here.
Darwin is released under the MIT License. See the LICENSE file for more information.
We hope you find Darwin to be a valuable tool in your software development journey. If you have any questions, feedback, or suggestions, please don't hesitate to reach out. Happy coding with Darwin!