An Easier Way: Chat to Deploy Llama2 with Walrus
In this blog we will introduce an AI tool, Appilot, to make the deployment simpler
Appilot ['æpaɪlət] stands for application-pilot. It is an experimental project that helps you operate applications using GPT-like LLMs. Appilot empowers users to execute tasks such as application management, environment management, diagnosis, and hybrid infrastructure orchestration seamlessly through natural language commands.
Get OpenAI API key with access to the gpt-4 model.
Install python3 and make.
Have a running Kubernetes cluster.
- Clone the repository.
git clone https://github.com/seal-io/appilot && cd appilot
- Run the following command to get the envfile.
cp .env.example .env
.envfile and fill in
Run the following command to install. It will create a venv and install required dependencies.
Using Walrus Backend
Walrus serves as the application management engine. It provides features like hybrid infrastructure support, environment management, etc. To enable Walrus backend, you need to install Walrus first and edit the envfile:
Below is more information about configuration, Appilot is configurable via environment variable or the envfile:
Then you can run Appilot to get started:
Chat to Deploy Llama2 on AWS
In this blog, we've embarked on a journey to explore the deployment of Llama2, using Appilot and Walrus. We've witnessed how these powerful tools can simplify the complex process of deployment.
In conclusion, as demonstrated in this blog, both Appilot and Walrus stand as indispensable allies in the face of the intricate challenges of application deployment. What's even more enticing is that both these tools are open-source, inviting you to download and give them a try!