langflow/docs/versioned_docs/version-1.9.0/Deployment/deployment-wxo.mdx

---
title: Deploy Langflow on watsonx Orchestrate
slug: /deployment-wxo
---

import Icon from "@site/src/components/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
import PartialGlobalModelProviders from '@site/docs/_partial-global-model-providers.mdx';

:::tip
As of Langflow 1.9.2, the IBM watsonx Orchestrate deployments feature is behind a feature flag. To enable it, set the following environment variable before starting Langflow:

```bash
LANGFLOW_FEATURE_WXO_DEPLOYMENTS=true
```
:::

Create a flow and deploy it to [IBM watsonx Orchestrate](https://www.ibm.com/docs/en/watsonx/watson-orchestrate/base?topic=getting-started-watsonx-orchestrate).

Deploying a flow on IBM watsonx Orchestrate is different from the other Langflow deployment options.
This workflow **does not** deploy a full-featured Langflow server and flow builder UI.
Instead, Langflow packages your selected flow and flow version, and then publishes it to IBM watsonx Orchestrate as a tool that an IBM watsonx Orchestrate agent can call.
Langflow is used to build and configure the flow, while IBM watsonx Orchestrate hosts the agent experience and invokes the deployed flow as part of that agent's toolset.

## Prerequisites

- [Install and start Langflow](/get-started-installation)
- Create an [OpenAI API key](https://platform.openai.com/api-keys)
- Create an [IBM watsonx Orchestrate instance](https://www.ibm.com/docs/en/watsonx/watson-orchestrate/base?topic=getting-started-watsonx-orchestrate)

## Create and deploy a flow

1. Create a flow in the Langflow UI, such as the Simple Agent starter flow in the [Quickstart](/get-started-quickstart).

2. Click <Icon name="Rocket" aria-hidden="true"/> **Deploy**.
The **Provider** pane opens.

3. Enter the **Name**, **Service Instance URL**, and **API Key** from your IBM watsonx Orchestrate instance.
These values are found in the **Settings** page of your IBM watsonx Orchestrate instance.

   - **Name**: `YOUR_DEPLOYMENT_NAME`
   - **Service Instance URL**: `https://api.dl.watson-orchestrate.ibm.com/instances/80194572-4421-6735-91ab-55c0d8e4f962`
   - **API Key**: `YOUR_WATSONX_ORCHESTRATE_API_KEY`

   The last segment of the Service Instance URL is the IBM watsonx Orchestrate tenant ID, which can be found in your watsonx Orchestrate deployment.
   In this example, the tenant ID is `80194572-4421-6735-91ab-55c0d8e4f962`.

4. Click **Next**.
   The **Deployment Type** pane opens.
5. Enter a **Type**, **Agent Name**, **Model**, and **Description**.

    The **Type** is always **Agent**. The deployed flow is an IBM watsonx Orchestrate agent with your flow available as a tool the agent can call.

    The **Model** list is populated from the connected watsonx Orchestrate instance, not Langflow.

6. To open the **Attach Flows** pane, click the **Attach Flows** tab. Select a flow and flow version to deploy.
7. To open the **Create Connections** pane, click the **Create Connections** tab. Create a new connection, or select an existing connection to bind to the flow.

   To create a new connection, do the following:

      1. Enter a **Connection Name** and any environment variables the flow requires, such as the `OPENAI_API_KEY`. Langflow auto-detects global variables from the flow JSON file, and you can add additional variables.

      2. To add the new connection to the list of available connections, click **Create Connection**.

      3. In the list of available connections, select the new connection, and then click **Attach Connection to Flow**.

   :::tip
   To bind the connection to the flow **without** environment variable binding, click **Skip**, and then click **Next**.
   :::

   For more information, see [Build flows](../Flows/concepts-flows.mdx#save-and-restore-flow-versions).
8. Click **Next**. The **Review & Confirm** pane opens.
9. Confirm the deployment values are correct, and then click <Icon name="Rocket" aria-hidden="true"/> **Deploy**.

    Langflow installs any required extra dependencies on your watsonx Orchestrate tenant automatically.

    In the Langflow UI, `Deployment successful` indicates your deployment succeeded.

    :::tip
    If you get an error that the tool name already exists on your deployment, click <Icon name="Pencil" aria-hidden="true"/> **Edit** to change the tool name.
    :::

10. Click **Test** to open a chat window with your agent on watsonx Orchestrate.
    Enter a question, and the agent responds using the connected flow as a tool.
11. Navigate to your IBM watsonx Orchestrate deployment, and then confirm that your Langflow flow is listed as an agent.

## Manage deployments in Langflow

From the **Projects** page, click **Deployments** to open the deployment management screen.

* **Deployments**:

   A **Deployment** is a published watsonx Orchestrate agent created from a specific Langflow flow version. Deployment details include the agent name, type, attached flows, model, and the IBM watsonx Orchestrate environment it belongs to.

   Use the **Deployments** tab to create, update, view, and delete flow deployments in Langflow.

* **Deployment Environments**:

   A **Deployment Environment** is a saved watsonx Orchestrate target that Langflow can deploy to. An environment stores the connection details for a watsonx Orchestrate tenant.

   Use the **Deployment Environments** tab to connect, view, and disconnect IBM watsonx Orchestrate environments in Langflow.

   To manage the tenant itself, use the IBM watsonx Orchestrate dashboard.

## Send requests to your flow

After you deploy your flow to IBM watsonx Orchestrate, you can connect to it through the Langflow deployment run endpoints.

Don't use the `/run` endpoint for flows deployed to IBM watsonx Orchestrate.
Instead use `POST /api/v1/deployments/{deployment_id}/runs` to start a run, and `GET /api/v1/deployments/{deployment_id}/runs/{run_id}` to check its status.

Endpoint paths must be prefixed with your Langflow server URL, such as `http://localhost:7860`.

### Create deployment run endpoint

**Endpoint:** `POST /api/v1/deployments/{deployment_id}/runs`

**Description:** Start a run for a deployed flow and return a provider-owned run ID that you can poll for status.

#### Example request

<Tabs>
<TabItem value="Python" label="Python" default>

```python
import requests

url = "http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs"

payload = {
    "provider_data": {
        "input": "Summarize today's tickets",
        "thread_id": "thread-123"
    }
}

headers = {
    "Content-Type": "application/json",
    "x-api-key": "LANGFLOW_API_KEY"
}

response = requests.post(url, json=payload, headers=headers)
response.raise_for_status()

print(response.json())
```

</TabItem>
<TabItem value="JavaScript" label="JavaScript">

```js
const payload = {
  provider_data: {
    input: "Summarize today's tickets",
    thread_id: "thread-123"
  }
};

const options = {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-api-key": "LANGFLOW_API_KEY"
  },
  body: JSON.stringify(payload)
};

fetch("http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs", options)
  .then((response) => response.json())
  .then((response) => console.log(response))
  .catch((err) => console.error(err));
```

</TabItem>
<TabItem value="curl" label="curl">

```bash
curl --request POST \
     --url "http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs" \
     --header "Content-Type: application/json" \
     --header "x-api-key: LANGFLOW_API_KEY" \
     --data '{
       "provider_data": {
         "input": "Summarize today's tickets",
         "thread_id": "thread-123"
       }
     }'
```

</TabItem>
</Tabs>

#### Request body

| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `provider_data.input` | `string` | Yes | The prompt or message content to send to the deployed agent. |
| `provider_data.thread_id` | `string` | No | Optional thread identifier to continue an existing conversation. |

#### Example response

```json
{
  "deployment_id": "3ea34379-1f72-4a33-9f6e-9e3ca88365b5",
  "provider_data": {
    "id": "run-42",
    "agent_id": "agent-123",
    "thread_id": "thread-123",
    "status": "accepted",
    "result": null,
    "started_at": null,
    "completed_at": null,
    "failed_at": null,
    "cancelled_at": null,
    "last_error": null
  }
}
```

#### Response body

The response returns the Langflow `deployment_id` and a `provider_data` object containing the provider-owned run metadata.
Use `provider_data.id` as the `run_id` when checking the run status.

### Get deployment run status endpoint

**Endpoint:** `GET /api/v1/deployments/{deployment_id}/runs/{run_id}`

**Description:** Retrieve the current status and result of a deployment run.

#### Example request

<Tabs>
<TabItem value="Python" label="Python" default>

```python
import requests

url = "http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs/RUN_ID"

headers = {
    "Content-Type": "application/json",
    "x-api-key": "LANGFLOW_API_KEY"
}

response = requests.get(url, headers=headers)
response.raise_for_status()

print(response.json())
```

</TabItem>
<TabItem value="JavaScript" label="JavaScript">

```js
const options = {
  method: "GET",
  headers: {
    "Content-Type": "application/json",
    "x-api-key": "LANGFLOW_API_KEY"
  }
};

fetch("http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs/RUN_ID", options)
  .then((response) => response.json())
  .then((response) => console.log(response))
  .catch((err) => console.error(err));
```

</TabItem>
<TabItem value="curl" label="curl">

```bash
curl --request GET \
     --url "http://LANGFLOW_SERVER_ADDRESS/api/v1/deployments/DEPLOYMENT_ID/runs/RUN_ID" \
     --header "Content-Type: application/json" \
     --header "x-api-key: LANGFLOW_API_KEY"
```

</TabItem>
</Tabs>

#### Path parameters

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `deployment_id` | `uuid` | Yes | The Langflow deployment ID for the deployed flow. |
| `run_id` | `string` | Yes | The provider-owned run ID returned in `provider_data.id`. |

#### Example response

```json
{
  "deployment_id": "3ea34379-1f72-4a33-9f6e-9e3ca88365b5",
  "provider_data": {
    "id": "run-42",
    "agent_id": "agent-123",
    "thread_id": "thread-123",
    "status": "completed",
    "result": {
      "output": "Here is your summary..."
    },
    "started_at": "2026-04-03T12:40:00Z",
    "completed_at": "2026-04-03T12:40:05Z",
    "failed_at": null,
    "cancelled_at": null,
    "last_error": null
  }
}
```

#### Response body

Check `provider_data.status` to determine whether the run is still processing or has finished.
When the status is `completed`, read the output from `provider_data.result`.