Configuring Quarkus Langchain4j with Gemini

To run Langchain4j with the Gemini model in your Quarkus application, you need to configure your API key and model properties.

1. Set Your Gemini API Key (in `.env`)

Your API key must be set as an environment variable in a .env file located at the root of your project. Quarkus will automatically load this file.

.env

1	`QUARKUS_LANGCHAIN4J_AI_GEMINI_API_KEY=your_actual_api_key_goes_here`

2. Configure `application.properties`

Your application.properties file should then reference this environment variable to inject the API key. Here, you also specify which Gemini model you intend to use.

src/main/resources/application.properties

# Gemini AI Model Configuration
# -----------------------------

# Reference the API key from the .env file.
# The ':${}' syntax provides an empty default, but .env will supply the value.
quarkus.langchain4j.ai.gemini.api-key=${QUARKUS_LANGCHAIN4J_AI_GEMINI_API_KEY:}

# Set the desired chat model.
# This value can be changed to any other supported Gemini model.
quarkus.langchain4j.ai.gemini.chat-model.model-id=gemini-1.5-flash

Here is the new section for your README, formatted to match your existing file:

Configuring the Google Web Search Tool

This setup is required to enable the WebSearchTool, which allows the AI to perform live web searches using the Google Custom Search Engine (CSE) API.

1. Get Google API Key and Search Engine ID

You will need two pieces of information from Google:

API Key: This is a standard API key from your Google Cloud Console. You must ensure the "Custom Search API" is enabled for your project.
Search Engine ID (cse.id): This ID connects your API key to a specific search configuration.
1. Go to the Google Programmable Search Engine control panel.
2. Click Add to create a new search engine.
3. In the "What to search?" section, select the option to "Search the entire web".
4. After creation, go to the "Setup" tab and copy your "Search engine ID".

2. Set Environment Variables (in `.env`)

Add your two new credentials to the .env file at the project root. This file is loaded by Quarkus and keeps your secrets out of the code.

.env

# Google Custom Search Credentials
GOOGLE_API_KEY=your-actual-api-key-goes-here
GOOGLE_CSE_ID=your-actual-search-engine-id-goes-here
````

### 3\. Configure `application.properties`

Finally, add the following to your `application.properties` file. This tells the Quarkus REST Client the API's URL and tells your `WebSearchTool` to read its credentials from the environment. By default this is already set up.

**`src/main/resources/application.properties`**

```properties
quarkus.rest-client.google-search-api.url=https://www.googleapis.com

google.api.key=${GOOGLE_API_KEY}
google.cse.id=${GOOGLE_CSE_ID}

How to Export GitHub Issues

This guide covers the basic steps to export all issues from a repository to a JSON file using the official GitHub CLI.

Regarding Ticket: github.com/Jenga-PMS/Jenga/issues/56

Introduction

With the official GitHub CLI, you can easily export all issues. The following command will save the data to a JSON file (not CSV).

Step 1: Install the GitHub CLI

If you are on a Mac, you can use Homebrew.

1	`brew install gh`

Step 2: Log In

You will need to authenticate with your GitHub account. This command requests the read:project scope, which is necessary to access project information.

gh auth login -h github.com -s read:project

Step 3: Export All Issues

Run this command to fetch all issues (both open and closed) and save them to a file named issues.json.

gh issue list --repo Jenga-PMS/Jenga --state all --json number,title,body,state,assignees,labels,milestone,comments,createdAt,updatedAt,projectItems > all-issues.json

Size, Estimate and Priority could not be extracted