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Run flows

After you build a flow, you probably want to run it within an application, such as a chatbot within a mobile app or website.

Langflow provides several ways to run flows from external applications:

Although you can use these options with an isolated, local Langflow instance, they are typically more valuable when you have deployed a Langflow server or packaged Langflow as a dependency of an application. For package dependencies, see Develop an application with Langflow and Package a flow as a Docker image.

Use the Langflow API to run flows​

The Langflow API is the primary way to access your flows and Langflow servers programmatically.

Try it

For an example of a script that calls the Langflow API, see the Quickstart.

Generate API code snippets​

To help you embed Langflow API requests in your scripts, Langflow automatically generates Python, JavaScript, and curl code snippets for your flows. To get these code snippets, do the following:

  1. In Langflow, open the flow that you want to embed in your application.

  2. Click Share, and then select API access.

    These code snippets call the /v1/run/$FLOW_ID endpoint, and they automatically populate minimum values, like the Langflow server URL, flow ID, headers, and request parameters.

    Windows

    The paths generated by the API access pane assume a *nix environment. If you use Microsoft Windows or WSL, you might need to adjust the filepaths given in the code snippets.

    API access pane

  3. Optional: Click Input Schema to modify component parameters in the code snippets without changing the flow itself.

  4. Copy the snippet for the language that you want to use.

  5. Run the snippet as is, or use the snippet in the context of a larger script.

For more information and examples of other Langflow API endpoints, see Get started with the Langflow API.

Langflow API authentication​

In Langflow versions 1.5 and later, most API endpoints require authentication with a Langflow API key, even if AUTO_LOGIN is set to True. The only exceptions are the MCP endpoints /v1/mcp, /v1/mcp-projects, and /v2/mcp, which never require authentication.

Code snippets generated in the API access pane include a script that checks for a LANGFLOW_API_KEY environment variable set in the local terminal session. This script doesn't check for Langflow API keys set anywhere besides the local terminal session.

For this script to work, you must set a LANGFLOW_API_KEY variable in the terminal session where you intend to run the code snippet, such as export LANGFLOW_API_KEY="sk...".

Alternatively, you can edit the code snippet to include an x-api-key header and ensure that the request can authenticate to the Langflow API.

For more information, see API keys and Get started with the Langflow API

Input Schema (tweaks)​

Tweaks are one-time overrides that modify component parameters at runtime, rather than permanently modifying the flow itself. For an example of tweaks in a script, see the Quickstart.

tip

Tweaks make your flows more dynamic and reusable.

You can create one flow and use it for multiple applications by passing application-specific tweaks in each application's Langflow API requests.

In the API access pane, click Input Schema to add tweaks to the request payload in a flow's code snippets.

Changes to a flow's Input Schema are saved exclusively as tweaks for that flow's API access code snippets. These tweaks don't change the flow parameters set in the Workspace, and they don't apply to other flows.

Adding tweaks through the Input Schema can help you troubleshoot formatting issues with tweaks that you manually added to Langflow API requests.

For example, the following curl command includes a tweak that disables the Store Messages setting in a flow's Chat Input component:


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curl --request POST \
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--url "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" \
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--header "Content-Type: application/json" \
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--header "x-api-key: LANGFLOW_API_KEY" \
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--data '{
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"input_value": "Text to input to the flow",
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"output_type": "chat",
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"input_type": "chat",
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"tweaks": {
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"ChatInput-4WKag": {
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"should_store_message": false
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}
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}
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}'

Use a flow ID alias​

If you want your requests to use an alias instead of the actual flow ID, you can rename the flow's /v1/run/$FLOW_ID endpoint:

  1. In Langflow, open the flow, click Share, and then select API access.

  2. Click Input Schema.

  3. In the Endpoint Name field, enter an alias for your flow's ID, such as a memorable, human-readable name.

    The name can contain only letters, numbers, hyphens, and underscores, such as flow-customer-database-agent.

  4. To save the change, close the Input Schema pane.

The automatically generated code snippets now use your new endpoint name instead of the original flow ID, such as url = "http://localhost:7868/api/v1/run/flow-customer-database-agent".

Embed a flow into a website​

For each flow, Langflow provides a code snippet that you can insert into the <body> of your website's HTML to interact with your flow through an embedded chat widget.

Required components

The chat widget only supports flows that have Chat Input and Chat Output components, which are required for the chat experience. Text Input and Text Output components can send and receive messages, but they don't include ongoing LLM chat context.

Attempting to chat with a flow that doesn't have Chat Input component will trigger the flow, but the response only indicates that the input was empty.

Get a langflow-chat snippet​

To get a flow's embedded chat widget code snippet, do the following:

  1. In Langflow, open the flow you want to embed.
  2. Click Share, and then select Embed into site.
  3. Copy the code snippet and use it in the <body> of your website's HTML. For more information, see Embed the chat widget with React, Angular, or HTML.
  4. Add the api_key prop to ensure the widget has permission to run the flow, as explained in Configure the langflow-chat web component.

The chat widget is implemented as a web component called langflow-chat that is loaded from a CDN. For more information, see the langflow-embedded-chat repository.

For example, the following HTML embeds a chat widget for a Basic prompting flow hosted on a Langflow server deployed on ngrok:


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<html>
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<head>
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<script src="https://cdn.jsdelivr.net/gh/langflow-ai/langflow-embedded-chat@main/dist/build/static/js/bundle.min.js"></script>
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</head>
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<body>
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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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></langflow-chat>
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</body>
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</html>

When this code is deployed to a live site, it renders as a responsive chatbot. If a user interacts with the chatbot, the input triggers the specified flow, and then the chatbot returns the output from the flow run.

Default chat widget

Try it

Use the Langflow embedded chat CodeSandbox for an interactive live demo of the embedded chat widget that uses your own flow. For more information, see the langflow-embedded-chat README.

Embed the chat widget with React, Angular, or HTML​

The following examples show how to use embedded chat widget in React, Angular, and plain HTML.

To use the chat widget in your React application, create a component that loads the widget script and renders the chat interface:

  1. Declare your web component, and then encapsulate it in a React component:


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    //Declaration of langflow-chat web component
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    declare global {
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    namespace JSX {
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    interface IntrinsicElements {
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    "langflow-chat": any;
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    }
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    }
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    }
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    //Definition for langflow-chat React component
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    export default function ChatWidget({ className }) {
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    return (
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    <div className={className}>
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    <langflow-chat
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    host_url="https://c822-73-64-93-151.ngrok-free.app"
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    flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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    api_key="$LANGFLOW_API_KEY"
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    ></langflow-chat>
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    </div>
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    );
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    }

  2. Place the component anywhere in your code to render the chat widget.

    In the following example, the React widget component is located at docs/src/components/ChatWidget/index.tsx, and index.tsx includes a script to load the chat widget code from CDN, along with the declaration and definition from the previous step:


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    import React, { useEffect } from 'react';
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    // Component to load the chat widget script
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    const ChatScriptLoader = () => {
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    useEffect(() => {
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    if (!document.querySelector('script[src*="langflow-embedded-chat"]')) {
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    const script = document.createElement('script');
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    script.src = 'https://cdn.jsdelivr.net/gh/langflow-ai/langflow-embedded-chat@main/dist/build/static/js/bundle.min.js';
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    script.async = true;
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    document.body.appendChild(script);
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    }
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    }, []);
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    return null;
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    };
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    //Declaration of langflow-chat web component
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    declare global {
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    namespace JSX {
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    interface IntrinsicElements {
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    "langflow-chat": any;
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    }
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    }
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    }
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    //Definition for langflow-chat React component
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    export default function ChatWidget({ className }) {
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    return (
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    <div className={className}>
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    <ChatScriptLoader />
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    <langflow-chat
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    host_url="https://c822-73-64-93-151.ngrok-free.app"
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    flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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    api_key="$LANGFLOW_API_KEY"
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    ></langflow-chat>
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    </div>
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    );
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    }

  3. Import the langflow-chat React component to make it available for use on a page. Modify the following import statement with your React component's name and path:


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    import ChatWidget from '@site/src/components/ChatWidget';

  4. To display the widget, call your langflow-chat component in the desired location on the page. Modify the following reference for your React component's name and the desired className:


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    <ChatWidget className="my-chat-widget" />

Configure the langflow-chat web component​

To use the embedded chat widget in your HTML, the langflow-chat web component must include the following minimum inputs (also known as props in React):

  • host_url: Your Langflow server URL. Must be HTTPS. Don't include a trailing slash (/).
  • flow_id: The ID of the flow you want to embed.
  • api_key: A Langflow API key. This prop is recommended to ensure the widget has permission to run the flow.

The minimum inputs are automatically populated in the Embed into site code snippet that is generated by Langflow.

You can use additional inputs (props) to modify the embedded chat widget. For a list of all props, types, and descriptions, see the langflow-embedded-chat README.

Example: Langflow API key prop

The api_key prop stores a Langflow API key that the chat widget can use to authenticate the underlying Langflow API request.

The Langflow team recommends following industry best practices for handling sensitive credentials. For example, securely store your API key, and then retrieve with an environment variable:


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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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></langflow-chat>

Example: Style props

There are many props you can use to customize the style and positioning of the embedded chat widget. Many of these props are of type JSON, and they require specific formatting, depending on where you embed the langflow-chat web component.

In React and plain HTML, JSON props are expressed as JSON objects or stringified JSON, such as \{"key":"value"\}:


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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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chat_window_style='{
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"backgroundColor": "#1a0d0d",
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"border": "4px solid #b30000",
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"borderRadius": "16px",
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"boxShadow": "0 8px 32px #b30000",
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"color": "#fff",
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"fontFamily": "Georgia, serif",
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"padding": "16px"
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}'
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window_title="Custom Styled Chat"
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height="600"
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width="400"
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></langflow-chat>

For Angular applications, use property binding syntax to pass JSON props as JavaScript objects. For example:


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import { Component } from '@angular/core';
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@Component({
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selector: 'app-root',
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template: `
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<div class="container">
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<h1>Langflow Chat Test</h1>
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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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[chat_window_style]='{"backgroundColor": "#ffffff"}'
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[bot_message_style]='{"color": "#000000"}'
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[user_message_style]='{"color": "#000000"}'
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height="600"
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width="400"
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chat_position="bottom-right"
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></langflow-chat>
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</div>
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`,
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styles: [`
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.container {
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padding: 20px;
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text-align: center;
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}
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`]
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})
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export class AppComponent {
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title = 'Langflow Chat Test';
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}

Example: Session ID prop

The following example adds a custom session ID to help identify flow runs started by the embeded chat widget:


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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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session_id="$SESSION_ID"
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></langflow-chat>

Example: Tweaks prop

Use the tweaks prop to modify flow parameters at runtime. The available keys for the tweaks object depend on the flow you are serving through the embedded chat widget.

In React and plain HTML, tweaks are declared as a JSON object, similar to how you would pass them to a Langflow API endpoint like /v1/run/$FLOW_ID. For example:


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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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tweaks='{
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"model_name": "llama-3.1-8b-instant"
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}'
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></langflow-chat>

For Angular applications, use property binding syntax to pass JSON props as JavaScript objects. For example:


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import { Component } from '@angular/core';
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@Component({
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selector: 'app-root',
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template: `
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<div class="container">
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<h1>Langflow Chat Test</h1>
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<langflow-chat
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host_url="https://c822-73-64-93-151.ngrok-free.app"
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flow_id="dcbed533-859f-4b99-b1f5-16fce884f28f"
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api_key="$LANGFLOW_API_KEY"
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[tweaks]='{"model_name": "llama-3.1-8b-instant"}'
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></langflow-chat>
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</div>
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`,
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styles: [`
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.container {
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padding: 20px;
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text-align: center;
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}
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`]
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})
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export class AppComponent {
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title = 'Langflow Chat Test';
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}

Serve flows through a Langflow MCP server​

Each Langflow project has an MCP server that exposes the project's flows as tools that MCP clients can use to generate responses.

In addition to serving flows through Langflow MCP servers, you can use Langflow as an MCP client to access any MCP server, including Langflow MCP servers.

Interactions with Langflow MCP servers happen through the Langflow API's /mcp endpoints.

For more information, see Use Langflow as an MCP server and Use Langflow as an MCP client.

See also​

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