Models for Agent API

Retrieve all available models for use with the Agent API.

GET /agent/v1/models

Lists the available models

cURL

curl --request GET \
  --url https://api.langdock.com/agent/v1/models \
  --header 'Authorization: Bearer <token>'

200

{
  "object": "list",
  "data": [
    {
      "id": "<string>",
      "object": "<string>",
      "created": 123,
      "owned_by": "<string>"
    }
  ]
}

Retrieve the list of models and their ids, available for use with the Agent API. This endpoint is useful when you want to see which models you can use when creating a temporary agent.

Before You Start

• Legacy Assistants API: This is the new Agents API with native Vercel AI SDK compatibility. If you’re using the legacy Assistants API, see the migration guide.

Base URL

https://api.langdock.com/agent/v1/models

Dedicated deployments

Replace api.langdock.com with <your-deployment-url>/api/public in all requests.

Example Request

const axios = require("axios");

async function getAvailableModels() {
  try {
    const response = await axios.get("https://api.langdock.com/agent/v1/models", {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    });

    console.log("Available models:", response.data.data);
  } catch (error) {
    console.error("Error fetching models:", error);
  }
}

Response Format

The API returns a list of available models in the following format:

Response Fields

object · string

Always ‘list’, indicating the top-level JSON object type.

data · array<Model>

Array containing available model objects.

Model object fields

id · string

Model ID to use when creating or updating agents (e.g., “gpt-5”).

object · string

Always ‘model’, indicating the object type.

created · integer

Unix timestamp (ms) when the model was created.

region · string

Region where the model is available (e.g., “eu”, “us”, “global”).

supportsExtendedThinking · boolean

Whether this model supports extended thinking mode.

Example response

{
  "object": "list",
  "data": [
    {
      "id": "gpt-5",
      "object": "model",
      "created": 1686935735000,
      "region": "eu",
      "supportsExtendedThinking": false
    }
    // …other models
  ]
}

Error Handling

try {
  const response = await axios.get("https://api.langdock.com/agent/v1/models", {
    headers: {
      Authorization: "Bearer YOUR_API_KEY",
    },
  });
} catch (error) {
  if (error.response) {
    switch (error.response.status) {
      case 400:
        console.error("Invalid request parameters");
        break;
      case 401:
        console.error("Invalid API key");
        break;
      case 500:
        console.error("Internal server error");
        break;
    }
  }
}

You can use any of these model IDs when creating a temporary agent through the Agent API. Simply specify the model ID in the model field of your agent configuration:

agent.js

const response = await axios.post("https://api.langdock.com/agent/v1/chat/completions", {
  agent: {
    name: "Custom Agent",
    instructions: "You are a helpful agent",
    model: "gpt-5", // Specify the model ID here
  },
  messages: [
    { id: "msg_1", role: "user", parts: [{ type: "text", text: "Hello!" }] },
  ],
});

Langdock intentionally blocks browser-origin requests to protect your API key and ensure your applications remain secure. For more information, please see our guide on API Key Best Practices.

Authorizations

Authorization · string · header · required

API key as Bearer token. Format "Bearer YOUR_API_KEY"

Response

200 - application/json

List of available models

object · enum<string> · required

Available options: list

data · object[] · required

Show child attributes