APIs

Function calling

Define your own tools and let the model decide when to call them. The proxy forwards the OpenAI tool schema verbatim — nothing Caronte-specific here.

Declare a tool

example.ts

import { client } from "./client";

const response = await client.chat.completions.create({
  model: "gpt-4o-mini",
  messages: [{ role: "user", content: "What's the weather in Milan?" }],
  tools: [
    {
      type: "function",
      function: {
        name: "get_weather",
        description: "Get the current weather for a city.",
        parameters: {
          type: "object",
          properties: { city: { type: "string" } },
          required: ["city"],
        },
      },
    },
  ],
});

const toolCall = response.choices[0].message.tool_calls?.[0];
console.log(toolCall?.function.name, toolCall?.function.arguments);

Return the tool result

Append the assistant message that emitted the tool_call plus a tool message carrying the result, then re-issue the request.

example.ts

import { client } from "./client";

const result = JSON.stringify({ city: "Milan", temp_c: 21 });

const followup = await client.chat.completions.create({
  model: "gpt-4o-mini",
  messages: [
    { role: "user", content: "What's the weather in Milan?" },
    /* assistant tool_call message from previous response */
    {
      role: "tool",
      tool_call_id: "<call_id from previous response>",
      content: result,
    },
  ],
});

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