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roanbrasil
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devops-gitops-corpus

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const supervisorAgent = new Agent({
name: "Supervisor",
instructions: `You are a GitHub repository analyzer. When given a GitHub repository URL or owner/repo format, you will:
1. Extract the owner/repo name.
2. Use the StarsFetcher agent to get the repository's star count.
3. Use the ContributorsFetcher agent to get the repository's contributors.
4. Pass the collected data (stars, contributors) to the RepoAnalyzer agent.
5. Return the analysis provided by the RepoAnalyzer.
Example input: https://github.com/vercel/ai-sdk or vercel/ai-sdk
`,
llm: new VercelAIProvider(),
model: openai("gpt-4o-mini"),
subAgents: [starsFetcherAgent, contributorsFetcherAgent, analyzerAgent], // Assign sub-agents
});
// 5. Initialize the VoltAgent with the agent hierarchy
new VoltAgent({
agents: {
// We only expose the supervisor externally.
// The supervisor will internally call the other agents.
supervisor: supervisorAgent,
},
});
console.log("GitHub Repo Analyzer Agent system started.");
```
**Explanation:**
1. **Imports:** We import necessary components from VoltAgent and AI SDK libraries.
2. **Mock Tools:** For simplicity, we've added mock versions of the tools directly in this file. In a real app, you'd import actual tool implementations.
3. **`starsFetcherAgent`:** Defined with a name, description, LLM configuration, and the `mockFetchRepoStarsTool`. Its job is solely to use this tool when asked.
4. **`contributorsFetcherAgent`:** Similar to the stars fetcher, but configured with the `mockFetchRepoContributorsTool`.
5. **`analyzerAgent`:** This agent doesn't need tools. Its purpose is to receive data (stars and contributors) and use its LLM capabilities to generate an analysis based on its description.
6. **`supervisorAgent`:** This is the main coordinator.
- Its `description` clearly outlines the steps it needs to take.
- Crucially, it includes the other three agents in its `subAgents` array. This tells the supervisor it can delegate tasks to these specific agents.
7. **`new VoltAgent(...)`:** This initializes the VoltAgent system. We register the `supervisorAgent` under the key `supervisor`. This means when we interact with our application, we'll be talking directly to the supervisor.
## Step 5: Run Your Agent System
Now, let's run the agent. Go back to your terminal (make sure you're in the `github-repo-analyzer` directory) and run the development command:
<Tabs>
<TabItem value="npm" label="npm" default>
```bash
npm run dev
```
</TabItem>
<TabItem value="yarn" label="yarn">
```bash
yarn dev
```
</TabItem>
<TabItem value="pnpm" label="pnpm">
```bash
pnpm dev
```
</TabItem>
</Tabs>
You should see the VoltAgent server startup message:
```bash
══════════════════════════════════════════════════
VOLTAGENT SERVER STARTED SUCCESSFULLY
══════════════════════════════════════════════════
✓ HTTP Server: http://localhost:3141
Test your agents with VoltOps Console: https://console.voltagent.dev
══════════════════════════════════════════════════
```
## Step 6: Interact with Your Agent
1. **Open the Console:** Go to [`https://console.voltagent.dev`](https://console.voltagent.dev).
2. **Find Your Agent:** Look for the agent named `supervisor` (or whatever name you gave it in the `new VoltAgent` call).
3. **Open Agent Details:** Click on the `supervisor` agent.
4. **Start Chatting:** Click the chat icon.
5. **Send a Message:** Try sending a message like:
`Analyze the repo voltagent/voltagent`
or
`Tell me about https://github.com/voltagent/voltagent`
![VoltAgent GitHub Repo Analyzer](https://cdn.voltagent.dev/2025-04-21-first-ai-agent-github-repo-analyzer/demo.gif)
The supervisor agent will now follow its instructions:
- It will likely first call the `StarsFetcher` to get the (mock) star count.
- Then, it will call the `ContributorsFetcher` for the (mock) contributor list.
- Finally, it will pass this information to the `RepoAnalyzer` and return the analysis to you in the chat.
You can observe this multi-step process happening in the VoltAgent VoltOps Platform!