> ## Documentation Index > Fetch the complete documentation index at: https://docs.vectorshift.ai/llms.txt > Use this file to discover all available pages before exploring further. # Listen — Button > Present users with clickable buttons during a conversation and wait for their selection. Add it in Python with `pipeline.add(name="...").listen(...)`. See the SDK reference. The Button node (a variant of the Listen node) presents users with clickable buttons during a chatbot conversation and pauses the flow until the user selects one. Use it to build guided conversational experiences — for example, letting a user choose between "Check Balance", "Transfer Funds", and "Contact Support", or presenting approval options like "Approve" and "Reject" in a compliance review flow. ## Core Functionality * Displays one or more clickable buttons to the user at a specific step in the conversation * Pauses the conversation flow until the user clicks a button (or sends a message, if allowed) * Routes the conversation to a different path based on which button was clicked * Optionally allows the user to type a free-text message instead of clicking a button ## Tool Inputs * `Button 1`, `Button 2`, `Button 3`, etc. — Text. The label displayed on each button. Default: `Button 1`. Add more buttons with the **+ Add Buttons** button. Remove buttons with the trash icon. * `Allow user message` — Toggle. Default: `No`. When enabled, the user can type a free-text message in addition to clicking a button. The message is routed to the `User Message` output path. ## Tool Outputs Each button creates a corresponding output path: * `button_1` — Path. Activates when the user clicks Button 1. * `button_2` — Path. Activates when the user clicks Button 2. * `button_3` — Path. Activates when the user clicks Button 3. (One output per button.) * `user_message` — Path. Activates when the user sends a typed message instead of clicking a button. Only available when `Allow user message` is enabled. * `complete` — Path. Advanced output. Activates when any selection is made. *** ### Overview In workflows, the Button node sits in a conversational workflow and presents the user with a set of choices. When the conversation reaches this node, the chatbot displays the buttons and waits. Each button's output path connects to a different branch of the workflow, enabling conditional logic based on the user's selection. This is ideal for building menu-driven chatbots, multi-step approval flows, or guided decision trees. listen button connect with nodes ### Use Cases * Present account action options ("Check Balance", "Transfer Funds", "View Statements") in a banking chatbot and route to the appropriate workflow branch * Build an approval flow where reviewers click "Approve" or "Reject" to trigger different downstream actions * Create a guided troubleshooting flow where users select their issue type from a set of buttons * Offer product tier selection ("Basic", "Professional", "Enterprise") in a sales chatbot to route to the right pricing workflow * Implement a feedback collection step with sentiment buttons ("Satisfied", "Neutral", "Dissatisfied") at the end of a support conversation ### How It Works #### Step 1: Add a Start Node The Button node requires a Start node on the canvas. If no Start node is present, a dialog appears: *"To use this node, drag a start node onto the canvas."* Add a Start node from the **Start** tab first. #### Step 2: Add the Button Node In the workflow canvas, click the **Chat** tab in the node palette, click **Listen**, then select **Button** from the variant list. Drag it onto the canvas. listen button drag into canvas #### Step 3: Configure Buttons The node starts with one button (`Button 1`). Edit the label text for each button. Click **+ Add Buttons** to add more options. Remove unwanted buttons with the trash icon. #### Step 4: Configure Allow User Message (Optional) Toggle `Allow user message` to `Yes` if you want the user to be able to type a free-text response instead of clicking a button. When enabled, a `User Message` output path appears on the node. #### Step 5: Connect Output Paths Each button creates a separate output path handle (`button_1`, `button_2`, etc.). Connect each handle to the downstream nodes or branches that should execute when that button is clicked. If `Allow user message` is enabled, also connect the `User Message` output to a branch that handles free-text input. #### Step 6: Test the Flow Deploy the workflow as a chatbot and verify that buttons appear at the correct step. Click each button and confirm it routes to the expected branch. ### Settings | Setting | Type | Default | Description | | ------------------------------ | ------ | -------- | --------------------------------------------------------------------- | | `Button 1`, `Button 2`, etc. | Text | Button 1 | The label displayed on each button. | | `Allow user message` | Toggle | No | Allow the user to type a message instead of clicking a button. | | `Show Success/Failure Outputs` | Toggle | Off | Show additional success/failure output handles. **Advanced setting.** | ### Best Practices * **Use clear, action-oriented button labels.** Labels like "Check Balance" or "Approve Transfer" are better than generic "Option A" or "Yes" — they tell the user exactly what will happen. * **Limit buttons to 3–5 options.** Too many buttons overwhelm users. If you need more choices, consider cascading Button nodes (first select a category, then a sub-option). * **Enable Allow user message for flexibility.** In many conversational flows, users may want to ask a question or provide context instead of picking a predefined option. Enable this toggle and route the free-text path to an LLM for handling. * **Use the complete output for shared logic.** If some downstream processing should happen regardless of which button was clicked, connect the `complete` advanced output to that shared branch. * **Pair with Talk nodes.** Place a Talk (Message) node before the Button node to explain the choices — for example, "How can I help you today?" followed by the button options. ### Related Templates Handles common customer inquiries and support tickets through conversational AI. Assists banking customers with account inquiries, transactions, and product questions. Provides real-time customer support directly embedded within a website interface. Reviews and routes refund or expense requests based on policy rules and approval thresholds. ### Common Issues For help with common configuration issues, see the [Common Issues](/support) page.