AI with IssueOps

[jianghao0718]

Get implementation steps for Issue Ops command like /ai to read comments of an issue or PR and reply with similar functionality of ActionAgents to answer with LLM.

[github-actions[bot]]

Sure! Implementing an IssueOps command to read comments from an issue or PR and reply using an LLM (Large Language Model) like ActionAgents involves a series of steps. Below is a guide to help you get started:

Steps to Implement IssueOps Command

Step 1: Setup Your Environment 🔧

1. Install necessary tools and libraries:
   • Ensure you have Node.js installed.
   • Install GitHub CLI: gh for CLI operations.
   • Set up your preferred LLM (e.g., OpenAI's GPT).

npm install @octokit/rest openai

2. Authenticate GitHub CLI:
   • Run gh auth login and follow the prompts to authenticate.

Step 2: Create a GitHub App or Token 🔒

1. GitHub Token:

   • Generate a personal access token from GitHub with appropriate permissions.

2. Register a GitHub App:

   • Create a new GitHub App with necessary permissions (issues, pull_requests, etc.).
   • Once created, download the private key and note the App ID.

Step 3: Read Comments from an Issue or PR 🗨️

1. Fetch Comments Using Octokit:

const { Octokit } = require("@octokit/rest");

const octokit = new Octokit({
  auth: process.env.GITHUB_TOKEN
});

async function getComments(owner, repo, number) {
  const { data } = await octokit.issues.listComments({
    owner,
    repo,
    issue_number: number
  });
  return data;
}

Step 4: Setup Your LLM Integration🧠

1. Integrate with OpenAI GPT:

const { Configuration, OpenAIApi } = require("openai");

const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY
});

const openai = new OpenAIApi(configuration);

async function generateReply(prompt) {
  const completion = await openai.createCompletion({
    model: "text-davinci-003",
    prompt: prompt,
    max_tokens: 150
  });
  return completion.data.choices[0].text.trim();
}

Step 5: Combine the Functionality 🪄

1. Read Comments and Generate Reply:

async function handleIssueComment(owner, repo, issueNumber) {
  try {
    const comments = await getComments(owner, repo, issueNumber);
    const latestComment = comments[comments.length - 1].body;

    const reply = await generateReply(latestComment);

    await octokit.issues.createComment({
      owner,
      repo,
      issue_number: issueNumber,
      body: reply
    });

    console.log("Reply posted successfully!");
  } catch (error) {
    console.error("Error handling issue comment:", error);
  }
}

handleIssueComment("your-username", "your-repo", 1);

Step 6: Automate the Process ⚙️

1. Run as GitHub Action:
   • Create a new file in your repository: .github/workflows/issue-ops.yml.

name: IssueOps with LLM

on:
  issue_comment:
    types: [created]

jobs:
  reply_with_llm:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout Repo
        uses: actions/checkout@v2
      - name: Setup Node.js
        uses: actions/setup-node@v2
        with:
          node-version: '16'
      - name: Install Dependencies
        run: npm install
      - name: Run IssueOps Command
        run: node your-script-file.js
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}

Final Thoughts 💭

• Ensure you handle exceptions and edge cases.
• Test thoroughly in a development repository before deploying to production.
• Regularly update dependencies to maintain security.

Good luck with your implementation! If you have any more questions or need further assistance, feel free to ask! 😊