Eidolon Git Search Recipe

In this recipe we have created a github copilot who can answer questions about the Eidolon monorepo. It dynamically pulls in information via similarity search to answer user queries. This is important if you have a body of information that is constantly changing, but you need real time information about (ie, a git repository).

Core Concepts

• Multi-agent communication
• Sub-component customization
• Dynamic embedding management

Agents

Repo Expert

The user facing copilot. Ask this agent questions about a repository, and it will go and find the answer with the assistance of the repo search agent.

Repo Search

Handles loading, embedding, and re-embedding documents ensuring they are up-to-date.

Translates queries into a vector search query and returns the top results.

Directory Structure

• 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.

Running the Server in Docker

First you need to clone the project and navigate to the project directory:

git clone https://github.com/eidolon-ai/eidolon-git-search.git
cd eidolon-git-search

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

Running the server in K8s

Prerequisites

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:

• Docker
• Kubernetes
• Helm

Clone the project and navigate to the project directory:

git clone https://github.com/eidolon-ai/eidolon-git-search.git
cd eidolon-git-search

Installation

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