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This is the Agents API with native Vercel AI SDK compatibility.
This guide explains how to migrate agents from one Langdock workspace to another using the Agents API. This is useful when you want to replicate agent configurations across different workspaces, move agents during organizational restructuring, or create backup copies of your agents.

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Overview

The migration process involves two main steps:
  1. Export: Retrieve the agent configuration from the source workspace using the Agent Get API
  2. Import: Create a new agent in the target workspace using the Agent Create API

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Prerequisites

Before you begin, ensure you have:
  1. Two API keys with AGENT_API scope:
    • One API key for the source workspace (where the agent currently exists)
    • One API key for the target workspace (where you want to migrate the agent)
  2. Access to the agent: Your source workspace API key must have access to the agent you want to migrate
  3. Matching resources in target workspace (if applicable):
    • If both workspaces have access to the same model, it will be transferred automatically. Otherwise, the model may need to be adjusted manually in the Langdock UI after migration
    • If the agent uses custom actions, those integrations must be enabled in the target workspace
    • Attachments need to be re-uploaded separately (they are not transferred automatically)

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Step 1: Export the Agent from Source Workspace

Use the Agent Get API to retrieve the complete configuration of your agent: 
const axios = require("axios");

async function getAgentFromSource(agentId, sourceApiKey) {
  const response = await axios.get(
    "https://api.langdock.com/agent/v1/get",
    {
      params: {
        agentId: agentId
      },
      headers: {
        Authorization: `Bearer ${sourceApiKey}`
      }
    }
  );

  return response.data.agent;
}

​
Understanding the Response

The Get API returns the complete agent configuration including:
  • name, description, instruction - The agent’s identity and system prompt
  • emojiIcon - The emoji icon displayed for the agent
  • model - Identifier of the model being used (e.g., gpt-5-mini-eu)
  • temperature - Creativity setting (0-1)
  • conversationStarters - Suggested prompts for users
  • inputType - Either “PROMPT” or “STRUCTURED”
  • inputFields - Form field definitions (for STRUCTURED input type)
  • webSearchEnabled, imageGenerationEnabled, codeInterpreterEnabled, canvasEnabled - Capability flags
  • actions - Custom integration actions
  • attachments - UUIDs of attached files

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Step 2: Transform the Configuration

The Get API response uses slightly different field names than the Create API expects. You need to map the fields: 
function transformForCreate(sourceAgent) {
  return {
    // Basic information
    name: sourceAgent.name,
    description: sourceAgent.description || undefined,
    emoji: sourceAgent.emojiIcon || undefined,
    instruction: sourceAgent.instruction || undefined,

    // Settings
    model: sourceAgent.model,
    creativity: sourceAgent.temperature,
    inputType: sourceAgent.inputType,
    conversationStarters: sourceAgent.conversationStarters || [],

    // Capabilities
    webSearch: sourceAgent.webSearchEnabled,
    imageGeneration: sourceAgent.imageGenerationEnabled,
    dataAnalyst: sourceAgent.codeInterpreterEnabled,
    canvas: sourceAgent.canvasEnabled,

    // Input fields (for STRUCTURED input type)
    inputFields: sourceAgent.inputFields || [],

    // Note: actions and attachments require special handling (see below)
  };
}

​
Field Mapping Reference

Get API Response FieldCreate API Request Field
namename
descriptiondescription
emojiIconemoji
instructioninstruction
modelmodel
temperaturecreativity
inputTypeinputType
conversationStartersconversationStarters
webSearchEnabledwebSearch
imageGenerationEnabledimageGeneration
codeInterpreterEnableddataAnalyst
canvasEnabledcanvas
inputFieldsinputFields
actionsactions
attachmentsattachments

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Step 3: Create the Agent in Target Workspace

Use the Agent Create API to create the agent in the target workspace: 
async function createAgentInTarget(agentConfig, targetApiKey) {
  const response = await axios.post(
    "https://api.langdock.com/agent/v1/create",
    agentConfig,
    {
      headers: {
        Authorization: `Bearer ${targetApiKey}`,
        "Content-Type": "application/json"
      }
    }
  );

  return response.data.agent;
}

​
Complete Migration Script

Here’s a complete script that combines all steps: 
const axios = require("axios");

// Configuration
const SOURCE_API_KEY = "your-source-workspace-api-key";
const TARGET_API_KEY = "your-target-workspace-api-key";
const AGENT_ID_TO_MIGRATE = "550e8400-e29b-41d4-a716-446655440000";

async function migrateAgent() {
  try {
    // Step 1: Get agent from source workspace
    console.log("Fetching agent from source workspace...");
    const getResponse = await axios.get(
      "https://api.langdock.com/agent/v1/get",
      {
        params: { agentId: AGENT_ID_TO_MIGRATE },
        headers: { Authorization: `Bearer ${SOURCE_API_KEY}` }
      }
    );
    
    const sourceAgent = getResponse.data.agent;
    console.log(`Found agent: "${sourceAgent.name}"`);

    // Step 2: Transform configuration for Create API
    const createConfig = {
      name: sourceAgent.name,
      description: sourceAgent.description || undefined,
      emoji: sourceAgent.emojiIcon || undefined,
      instruction: sourceAgent.instruction || undefined,
      model: sourceAgent.model,
      creativity: sourceAgent.temperature,
      inputType: sourceAgent.inputType,
      conversationStarters: sourceAgent.conversationStarters || [],
      webSearch: sourceAgent.webSearchEnabled,
      imageGeneration: sourceAgent.imageGenerationEnabled,
      dataAnalyst: sourceAgent.codeInterpreterEnabled,
      canvas: sourceAgent.canvasEnabled,
      inputFields: sourceAgent.inputFields || [],
      // Note: actions and attachments excluded - see "Handling Special Cases"
    };

    // Remove undefined values
    Object.keys(createConfig).forEach(key => {
      if (createConfig[key] === undefined) {
        delete createConfig[key];
      }
    });

    // Step 3: Create agent in target workspace
    console.log("Creating agent in target workspace...");
    const createResponse = await axios.post(
      "https://api.langdock.com/agent/v1/create",
      createConfig,
      {
        headers: {
          Authorization: `Bearer ${TARGET_API_KEY}`,
          "Content-Type": "application/json"
        }
      }
    );

    const newAgent = createResponse.data.agent;
    console.log(`Migration successful!`);
    console.log(`New agent ID: ${newAgent.id}`);
    console.log(`Agent name: ${newAgent.name}`);
    
    return newAgent;

  } catch (error) {
    if (error.response) {
      console.error(`Error ${error.response.status}: ${JSON.stringify(error.response.data)}`);
    } else {
      console.error("Error:", error.message);
    }
    throw error;
  }
}

migrateAgent();

​
Handling Special Cases

​
Actions (Custom Integrations)

Actions reference integrations that must be enabled in the target workspace. Action UUIDs are specific to each workspace’s integration setup.
Exclude actions from the initial migration and manually configure them in the target workspace after the agent is created.

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Attachments

Attachment UUIDs reference files stored in the source workspace. These files are not automatically transferred. To migrate attachments:
  1. Download the files from the source workspace
  2. Re-upload them to the target workspace using the Upload Attachment API
  3. Update the agent with the new attachment UUIDs

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OAuth Connections

Pre-selected OAuth connections are not supported via the API. Users must configure OAuth connections through the Langdock UI after migration.

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Migrating Multiple Agents

To migrate multiple agents, simply loop through a list of agent IDs: 
const AGENT_IDS = [
  "agent-uuid-1",
  "agent-uuid-2",
  "agent-uuid-3"
];

async function migrateMultipleAgents() {
  const results = [];
  
  for (const agentId of AGENT_IDS) {
    try {
      console.log(`\nMigrating agent: ${agentId}`);
      const newAgent = await migrateAgent(agentId);
      results.push({ 
        sourceId: agentId, 
        targetId: newAgent.id, 
        status: "success" 
      });
    } catch (error) {
      results.push({ 
        sourceId: agentId, 
        status: "failed", 
        error: error.message 
      });
    }
  }
  
  console.log("\n=== Migration Summary ===");
  console.table(results);
}

​
Post-Migration Checklist

After migrating an agent, verify the following in the target workspace:
  • Agent appears in the Agents list with correct name and emoji
  • Description and instructions are correctly transferred
  • Model is correctly set (or adjust if the target workspace does not support the same model)
  • Conversation starters are present
  • Capabilities (web search, image generation, etc.) are correctly enabled
  • Input fields are properly configured (for STRUCTURED input type)
  • Manually configure any OAuth connections through the UI
  • Re-upload and attach any necessary files
  • Configure custom actions/integrations if needed
  • Test the agent by sending a message

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Limitations

Keep these limitations in mind when planning your migration:
  1. Attachments are not transferred - Files must be re-uploaded to the target workspace
  2. Actions may need reconfiguration - Integration action UUIDs are workspace-specific
  3. OAuth connections require manual setup - Cannot be configured via API
  4. Models may require adjustment - The model identifier is transferred, but if the target workspace does not have access to the same model, you may need to adjust it manually in the UI after migration
  5. Conversation history is not migrated - Only the agent configuration is transferred
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