Tool calling

Tools work exactly as in the OpenAI SDK — Orbitrage just routes and traces the calls. Here’s a full ReAct loop you can run as-is.

import os, json, orbitrage
orbitrage.init(os.environ["ORBITRAGE_API_KEY"], user_id="customer_42")

from openai import OpenAI
client = OpenAI()

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Current weather for a city.",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string"}},
            "required": ["city"],
        },
    },
}]

def get_weather(city):           # your real implementation
    return f"22°C and sunny in {city}"

messages = [{"role": "user", "content": "What's the weather in Tokyo?"}]

while True:
    resp = client.chat.completions.create(model="minimax-m3", messages=messages, tools=tools)
    msg = resp.choices[0].message
    messages.append(msg)
    if not msg.tool_calls:
        print(msg.content)
        break
    for tc in msg.tool_calls:
        args = json.loads(tc.function.arguments)
        result = get_weather(**args)
        messages.append({"role": "tool", "tool_call_id": tc.id, "content": result})

import { orbitrage } from "orbitrage";
await orbitrage.init({ apiKey: process.env.ORBITRAGE_API_KEY, userId: "customer_42" });

import OpenAI from "openai";
const client = new OpenAI();

const tools = [{
  type: "function",
  function: {
    name: "get_weather",
    description: "Current weather for a city.",
    parameters: {
      type: "object",
      properties: { city: { type: "string" } },
      required: ["city"],
    },
  },
}];

const getWeather = (city) => `22°C and sunny in ${city}`;   // your real impl

const messages = [{ role: "user", content: "What's the weather in Tokyo?" }];

while (true) {
  const resp = await client.chat.completions.create({ model: "minimax-m3", messages, tools });
  const msg = resp.choices[0].message;
  messages.push(msg);
  if (!msg.tool_calls?.length) { console.log(msg.content); break; }
  for (const tc of msg.tool_calls) {
    const args = JSON.parse(tc.function.arguments);
    messages.push({ role: "tool", tool_call_id: tc.id, content: getWeather(args.city) });
  }
}

Managed tools — let Orbitrage run them

Don’t want to wire up a web-search or scrape API at all? Reference a managed tool by name and Orbitrage runs it server-side with our key, loops the result back to the model, and returns the final answer — no key, no tool loop on your side. Your own tools (like get_weather above) keep running on your side, in the same call.

resp = client.chat.completions.create(
    model="minimax-m3",
    messages=[{"role": "user", "content": "Search the web: what's new with MCP? Cite a source."}],
    tools=["tavily_orbitrage"],     # managed — we run it. Just name it.
)
print(resp.choices[0].message.content)   # final answer, already includes the search

const resp = await client.chat.completions.create({
  model: "minimax-m3",
  messages: [{ role: "user", content: "Search the web: what's new with MCP? Cite a source." }],
  tools: ["tavily_orbitrage"] as never,   // managed — we run it
});
console.log(resp.choices[0].message.content);

Mix managed + your own tools

Put both in one tools array. Orbitrage runs the managed ones server-side and hands your own tool calls back to you — in the same request.

tools = [
    "calculator_orbitrage",                          # managed — we run it
    "tavily_orbitrage",                              # managed — we run it
    {"type": "function", "function": {               # yours — you run it
        "name": "get_order_status",
        "description": "Look up an order by id.",
        "parameters": {"type": "object",
                       "properties": {"id": {"type": "string"}}, "required": ["id"]}}},
]

messages = [{"role": "user", "content": "Compute 1234*5678, then check order A-1009."}]
while True:
    resp = client.chat.completions.create(model="minimax-m3", messages=messages, tools=tools)
    msg = resp.choices[0].message
    messages.append(msg)
    if not msg.tool_calls:               # managed calls already resolved server-side
        print(msg.content); break
    for tc in msg.tool_calls:            # only YOUR tools land here
        if tc.function.name == "get_order_status":
            messages.append({"role": "tool", "tool_call_id": tc.id, "content": "shipped"})

See Tools Gateway for the full catalog (web search, scrape, calculator, datetime, weather, …) and billing. Managed tools also work with pinned models including glm-5.2. In the dashboard, the run shows each LLM hop, the tool definitions you sent, and which tools the model called (managed tools are badged via Orbitrage with their cost) — useful for spotting tool-selection drift.

Routing scores prompts with tools too: a request that offers many tools tends to route to a tool-strong model. Pin a model if you need a specific one.

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Managed tools — let Orbitrage run them

Mix managed + your own tools

​Managed tools — let Orbitrage run them

​Mix managed + your own tools

Managed tools — let Orbitrage run them

Mix managed + your own tools