Tool Use & Function Calling

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.SKYTELLS_API_KEY,
  baseURL: "https://api.skytells.ai/v1",
});

// Step 1: Send request with tool definitions
const response = await client.chat.completions.create({
  model: "deepbrain-router",
  messages: [
    { role: "user", content: "What's the weather in San Francisco right now?" },
  ],
  tools: [
    {
      type: "function",
      function: {
        name: "get_weather",
        description: "Get current weather for a city",
        parameters: {
          type: "object",
          properties: {
            city: { type: "string", description: "City name" },
            units: {
              type: "string",
              enum: ["celsius", "fahrenheit"],
              description: "Temperature units",
            },
          },
          required: ["city"],
        },
      },
    },
  ],
});

// Step 2: If the model decided to use a tool
const message = response.choices[0].message;
if (message.tool_calls) {
  const call = message.tool_calls[0];
  const args = JSON.parse(call.function.arguments);

  // Execute the actual function
  const weather = await getWeather(args.city, args.units);

  // Step 3: Send the result back
  const finalResponse = await client.chat.completions.create({
    model: "deepbrain-router",
    messages: [
      { role: "user", content: "What's the weather in San Francisco right now?" },
      message, // the assistant's tool_call message
      {
        role: "tool",
        tool_call_id: call.id,
        content: JSON.stringify(weather),
      },
    ],
  });

  console.log(finalResponse.choices[0].message.content);
}

curl https://api.skytells.ai/v1/chat/completions \
  -H "x-api-key: YOUR_SKYTELLS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepbrain-router",
    "messages": [
      {"role": "user", "content": "What is the weather in San Francisco?"}
    ],
    "tools": [{
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get current weather for a city",
        "parameters": {
          "type": "object",
          "properties": {
            "city": {"type": "string"},
            "units": {"type": "string", "enum": ["celsius", "fahrenheit"]}
          },
          "required": ["city"]
        }
      }
    }]
  }'

// BAD: Exposing raw GitHub API to the LLM
const rawTool = {
  name: "github_api",
  description: "Make any GitHub API call",
  parameters: {
    method: { type: "string" },
    path: { type: "string" },
    headers: { type: "object" },
    body: { type: "object" },
  },
};

// GOOD: Purpose-built adapter
const adapterTool = {
  name: "list_open_issues",
  description: "List open issues for a GitHub repo. Returns title, number, labels, and author.",
  parameters: {
    repo: {
      type: "string",
      description: "Repository in 'owner/repo' format",
    },
    label: {
      type: "string",
      description: "Filter by label name. Optional.",
    },
  },
};

async function listOpenIssues(repo: string, label?: string) {
  const [owner, name] = repo.split("/");
  const response = await octokit.issues.listForRepo({
    owner,
    repo: name,
    state: "open",
    labels: label,
    per_page: 20,
  });

  // Simplify response for LLM consumption
  return response.data.map((issue) => ({
    number: issue.number,
    title: issue.title,
    labels: issue.labels.map((l) => l.name),
    author: issue.user.login,
    created: issue.created_at,
  }));
}