langflow/docs/docs/API-Reference/api-flows-run.md

title	slug
Flow trigger endpoints	/api-flows-run

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Use the /run amd /webhook endpoints to run flows.

To create, read, update, and delete flows, see Flow management endpoints.

Run flow

Execute a specified flow by ID or name. The flow is executed as a batch, but LLM responses can be streamed.

This example runs a Basic Prompting flow with a given flow ID and passes a JSON object as the input value. Flow IDs can be found on the Publish pane or in a flow's URL.

The parameters are passed in the request body. In this example, the values are the default values.

curl -X POST \
  "$LANGFLOW_URL/api/v1/run/$FLOW_ID" \
  -H "Content-Type: application/json" \
  -d '{
    "input_value": "Tell me about something interesting!",
    "session_id": "chat-123",
    "input_type": "chat",
    "output_type": "chat",
    "output_component": "",
    "tweaks": null
  }'

{
  "session_id": "chat-123",
  "outputs": [{
    "inputs": {
      "input_value": "Tell me about something interesting!"
    },
    "outputs": [{
      "results": {
        "message": {
          "text": "Sure! Have you ever heard of the phenomenon known as \"bioluminescence\"? It's a fascinating natural occurrence where living organisms produce and emit light. This ability is found in various species, including certain types of jellyfish, fireflies, and deep-sea creatures like anglerfish.\n\nBioluminescence occurs through a chemical reaction in which a light-emitting molecule called luciferin reacts with oxygen, catalyzed by an enzyme called luciferase. The result is a beautiful glow that can serve various purposes, such as attracting mates, deterring predators, or luring prey.\n\nOne of the most stunning displays of bioluminescence can be seen in the ocean, where certain plankton emit light when disturbed, creating a mesmerizing blue glow in the water. This phenomenon is often referred to as \"sea sparkle\" and can be seen in coastal areas around the world.\n\nBioluminescence not only captivates our imagination but also has practical applications in science and medicine, including the development of biosensors and imaging techniques. It's a remarkable example of nature's creativity and complexity!",
          "sender": "Machine",
          "sender_name": "AI",
          "session_id": "chat-123",
          "timestamp": "2025-03-03T17:17:37+00:00",
          "flow_id": "d2bbd92b-187e-4c84-b2d4-5df365704201",
          "properties": {
            "source": {
              "id": "OpenAIModel-d1wOZ",
              "display_name": "OpenAI",
              "source": "gpt-4o-mini"
            },
            "icon": "OpenAI"
          },
          "component_id": "ChatOutput-ylMzN"
        }
      }
    }]
  }]
}

Stream LLM token responses

To stream LLM token responses, append the ?stream=true query parameter to the request. LLM chat responses are streamed back as token events until the end event closes the connection.

curl -X POST \
  "$LANGFLOW_URL/api/v1/run/$FLOW_ID?stream=true" \
  -H "accept: application/json" \
  -H "Content-Type: application/json" \
  -d '{
    "message": "Tell me something interesting!",
    "session_id": "chat-123"
  }'

{"event": "add_message", "data": {"timestamp": "2025-03-03T17:20:18", "sender": "User", "sender_name": "User", "session_id": "chat-123", "text": "Tell me about something interesting!", "files": [], "error": false, "edit": false, "properties": {"text_color": "", "background_color": "", "edited": false, "source": {"id": null, "display_name": null, "source": null}, "icon": "", "allow_markdown": false, "positive_feedback": null, "state": "complete", "targets": []}, "category": "message", "content_blocks": [], "id": "0103a21b-ebf7-4c02-9d72-017fb297f812", "flow_id": "d2bbd92b-187e-4c84-b2d4-5df365704201"}}

{"event": "add_message", "data": {"timestamp": "2025-03-03T17:20:18", "sender": "Machine", "sender_name": "AI", "session_id": "chat-123", "text": "", "files": [], "error": false, "edit": false, "properties": {"text_color": "", "background_color": "", "edited": false, "source": {"id": "OpenAIModel-d1wOZ", "display_name": "OpenAI", "source": "gpt-4o-mini"}, "icon": "OpenAI", "allow_markdown": false, "positive_feedback": null, "state": "complete", "targets": []}, "category": "message", "content_blocks": [], "id": "27b66789-e673-4c65-9e81-021752925161", "flow_id": "d2bbd92b-187e-4c84-b2d4-5df365704201"}}

{"event": "token", "data": {"chunk": " Have", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " you", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " ever", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " heard", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " of", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " the", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "token", "data": {"chunk": " phenomenon", "id": "27b66789-e673-4c65-9e81-021752925161", "timestamp": "2025-03-03 17:20:18 UTC"}}

{"event": "end", "data": {"result": {"session_id": "chat-123", "message": "Sure! Have you ever heard of the phenomenon known as \"bioluminescence\"?..."}}}

This result is abbreviated, but illustrates where the end event completes the LLM's token streaming response.

Run endpoint headers

Header	Info	Example
Content-Type	Required. Specifies the JSON format.	"application/json"
accept	Required. Specifies the response format.	"application/json"
x-api-key	Optional. Required only if authentication is enabled.	"sk-..."

Run endpoint parameters

Parameter	Type	Info
flow_id	UUID/string	Required. Part of URL: /run/$FLOW_ID
stream	boolean	Optional. Query parameter: /run/$FLOW_ID?stream=true
input_value	string	Optional. JSON body field. Main input text/prompt. Default: null
input_type	string	Optional. JSON body field. Input type ("chat" or "text"). Default: "chat"
output_type	string	Optional. JSON body field. Output type ("chat", "any", "debug"). Default: "chat"
output_component	string	Optional. JSON body field. Target component for output. Default: ""
tweaks	object	Optional. JSON body field. Component adjustments. Default: null
session_id	string	Optional. JSON body field. Conversation context ID. See Session ID. Default: null

Request example with all headers and parameters

curl -X POST \
  "http://$LANGFLOW_URL/api/v1/run/$FLOW_ID?stream=true" \
  -H "Content-Type: application/json" \
  -H "accept: application/json" \
  -H "x-api-key: sk-..." \
  -d '{
    "input_value": "Tell me a story",
    "input_type": "chat",
    "output_type": "chat",
    "output_component": "chat_output",
    "session_id": "chat-123",
    "tweaks": {
      "component_id": {
        "parameter_name": "value"
      }
    }
  }'

Webhook run flow

Use the /webhook endpoint to start a flow by sending an HTTP POST request.

:::tip After you add a Webhook component to a flow, open the API access pane, and then click the Webhook cURL tab to get an automatically generated POST /webhook request for your flow. :::

curl -X POST \
  "$LANGFLOW_URL/api/v1/webhook/$FLOW_ID" \
  -H "Content-Type: application/json" \
  -d '{"data": "example-data"}'

Result

```json { "message": "Task started in the background", "status": "in progress" } ```

For more information, see Webhook component and Trigger flows with webhooks.

Deprecated flow trigger endpoints

The following endpoints are deprecated and replaced by the /run endpoint:

• /process
• /predict