This project serves as a template for individuals interested in building agents with Eidolon.
For a detailed guide, check out the quickstart walkthrough on our website.
resources
: This directory contains additional resources for the project. An example agent is provided for reference.components
: This directory is where any custom code should be placed.
First you need to clone the project and navigate to the project directory:
git clone https://github.com/eidolon-ai/eidolon-quickstart.git
cd eidolon-quickstart
Then run the server using docker, use the following command:
make docker-serve
The first time you run this command, you may be prompted to enter credentials that the machine needs to run (ie, OpenAI API Key).
This command will download the dependencies required to run your agent machine and start the Eidolon http server in "dev-mode".
If the server starts successfully, you should see the following output:
Starting Server...
INFO: Started server process [34623]
INFO: Waiting for application startup.
INFO - Building machine 'local_dev'
...
INFO - Server Started in 1.50s
First download the Ediolon CLI
pip install 'eidolon-ai-client[cli]' -U
The create an AgentProcess
export PID=$(eidolon-cli processes create --agent hello-world)
Now that we have started a conversation, we can converse with our agent
eidolon-cli actions converse --process-id $PID --body "Hi! I made you"
You should see a response from your agent
Hello! 🎉 I'm super excited to be here and help you out!
WARNING: This will work for local k8s environments only. See Readme.md in the k8s directory if you are using this against a cloud based k8s environment.
To use kubernetes for local development, you will need to have the following installed:
If you are using Minikube, run the following commands before any make commands:
alias kubectl="minikube kubectl --"
eval $(minikube docker-env)
Make sure your kubernetes environment is set up properly and install the Eidolon k8s operator.
make k8s-operator
This will install the Eidolon operator in your k8s cluster. This only needs to be done once.
Next install the Eidolon resources. This will create an Eidolon machine and an Eidolon agent in your cluster, start them, and tail the logs:
make k8s-serve
If the server starts successfully, you should see the following output:
Deployment is ready. Tailing logs from new pods...
INFO: Started server process [1]
INFO: Waiting for application startup.
INFO - Building machine 'local-dev'
INFO - Starting agent 'hello-world'
INFO - Server Started in 0.86s