Answer Node

The Answer node is used to return a final answer to users in a workflow. It typically serves as the endpoint of chat flows or conversational workflows, sending processed results back to users.

Use Cases

Typical Applications

Chatbot Replies - Return AI-generated responses in conversation workflows
Q&A Systems - Return answers from knowledge base retrieval or LLM generation
Form Processing Feedback - Return submission confirmation to users
Query Result Display - Show data query or calculation results
Workflow Status Notifications - Inform users of operation execution status

Node Configuration

Basic Settings (Parameters Panel)

Answer Content

The content to return to users. This is the only required parameter.

Field Properties:

Required field
Supports expressions
Supports multi-line text input
Supports Markdown format

Configuration Examples:

javascript

// 1. Direct text input
"Thank you for your submission, we'll process it shortly."

// 2. Reference LLM node output
$('LLM').output

// 3. Combine data from multiple nodes
`Hello ${$('Chat Trigger').userName}!

Based on your query, we found the following information:
${$('Knowledge Retrieval').result}

Feel free to reach out if you need further assistance.`

// 4. Use conditional expressions
$('AI Classifier').class === 'urgent'
  ? 'We have marked your issue as urgent. Customer service will contact you within 10 minutes.'
  : 'Thank you for your feedback, we will respond within 24 hours.'

// 5. Format data display
`Query Results:

- Order ID: ${$('HTTP Request').orderId}
- Status: ${$('HTTP Request').status}
- Amount: $${$('HTTP Request').amount}
- Created: ${$('HTTP Request').createdAt}`

Advanced Settings (Settings Panel)

Node Description

Add custom description to help team members understand node purpose.

yaml

nodeDescription: "Return order query results to user"

Output Data

The Answer node typically serves as the workflow endpoint with no subsequent nodes. However, if you need to record or process the returned content, you can access its output:

javascript

// Get the returned answer content
$('Answer').answer

Workflow Examples

Example 1: Simple Q&A Bot

Chat Trigger
  → LLM Node
    System Prompt: "You are a friendly customer service assistant"
    User Prompt: $('Chat Trigger').userMessage
  → Answer Node
    Answer: $('LLM').output

Example 2: Knowledge Base Q&A System

Chat Trigger
  → Knowledge Retrieval
    Query: $('Chat Trigger').question
  → LLM Node
    System Prompt: "Answer user questions based on the following knowledge base content"
    Context: $('Knowledge Retrieval').results
    User Question: $('Chat Trigger').question
  → Answer Node
    Answer: $('LLM').output

Example 3: Differentiated Replies After Classification

Chat Trigger
  → AI Classifier
    Input: $('Chat Trigger').message
    Classes: ["Technical Issue", "Account Problem", "General Inquiry"]
  → Conditional Branch
    → [Technical Issue] → LLM (Technical Expert Role) → Answer
    → [Account Problem] → Knowledge Retrieval (Account Docs) → LLM → Answer
    → [General Inquiry] → LLM (Customer Service Role) → Answer

Example 4: Multi-step Task Completion Notification

Chat Trigger
  → HTTP Request (Create Order)
  → HTTP Request (Send Confirmation Email)
  → HTTP Request (Update CRM)
  → Answer Node
    Answer: `Your order has been created successfully!

Order Details:
- Order ID: ${$('HTTP Request').orderId}
- Total Amount: $${$('HTTP Request').totalAmount}
- Estimated Delivery: ${$('HTTP Request').estimatedDelivery}

A confirmation email has been sent to your inbox.`

Example 5: Error Handling with Friendly Messages

Chat Trigger
  → Conditional Branch (Validate Input)
    → [Valid] → Processing Logic → Answer (Success Message)
    → [Invalid] → Answer Node
      Answer: "Sorry, your input format is incorrect. Please provide a valid order number (format: ORD-XXXXXX)."

Best Practices

1. Clear and Friendly Content

Use Structured Format

javascript

// ✅ Good answer - Clear structure
`Query completed!

Your account information:
- Username: ${$('Data Query').username}
- Membership Level: ${$('Data Query').level}
- Points Balance: ${$('Data Query').points}

For help, type "help"`

// ❌ Poor answer - Information dump
`${$('Data Query').username} ${$('Data Query').level} ${$('Data Query').points}`

Use Friendly Tone

javascript

// ✅ Friendly
"Thank you for your patience! I've found the relevant information for you..."

// ❌ Blunt
"Query results below:"

2. Handle Different Scenarios

Different Feedback for Success and Failure

javascript

$('HTTP Request').statusCode === 200
  ? `Operation successful! Your request has been processed.`
  : `Operation failed: ${$('HTTP Request').error.message}

Please try again later or contact support for assistance.`

Adjust Reply Based on Data Volume

javascript

$('Knowledge Retrieval').results.length > 0
  ? `Found ${$('Knowledge Retrieval').results.length} relevant items:

${$('Knowledge Retrieval').results.map(r => `- ${r.title}`).join('\n')}`
  : `Sorry, no relevant information found.

You can:
- Try different keywords
- Contact human support
- Visit help center`

3. Keep It Concise

Avoid Overly Long Replies

javascript

// ✅ Concise and clear
`Order ${$('Query').orderId} status: ${$('Query').status}

Estimated delivery: ${$('Query').eta}`

// ❌ Too verbose
// Contains excessive unnecessary details...

Use Step-by-step Guidance

javascript

// For complex operations, guide users step by step
`Step 1 complete! ✓

Next, please provide your contact information to continue.`

4. Support Multi-language

javascript

// Return different content based on user language
$('Chat Trigger').language === 'zh'
  ? `您好！${$('LLM').output}`
  : `Hello! ${$('LLM').output_en}`

5. Add Follow-up Guidance

javascript

`${$('LLM').output}

---
💡 Other useful commands:
- Type "menu" to view all features
- Type "support" to contact human support
- Type "history" to view conversation history`

FAQ

Q1: What's the difference between Answer node and LLM node?

LLM Node: Calls large language model to generate content, an intermediate processing step
Answer Node: Returns final results to users, the workflow endpoint

Typical Usage:

LLM Node (Generate Content) → Answer Node (Return to User)

Q2: Can I use multiple Answer nodes in one workflow?

A: Yes, you can use multiple Answer nodes in different conditional branches.

Example:

AI Classifier
  → Conditional Branch
    → [Type A] → Answer Node (Reply A)
    → [Type B] → Answer Node (Reply B)
    → [Type C] → Answer Node (Reply C)

Only the Answer node in the executed branch will take effect.

Q3: What formats does the Answer node support?

A: The Answer node supports:

Plain Text: Regular text
Markdown: Formatted text (depending on frontend support)
Expressions: Dynamic content and conditional logic
Multi-line Text: Using template strings

Q4: How to include line breaks in answers?

A: Use template strings (backticks):

javascript

`First line
Second line
Third line`

Or use \n:

javascript

"First line\nSecond line\nThird line"

Q5: Will long answer content be truncated?

A: Depends on frontend display limits. Recommendations:

Break long content into sections
Provide summary + detail links
Use pagination or "see more" approach

javascript

// Provide summary
`Found ${$('Search').total} results, here are the first 5:

${$('Search').results.slice(0, 5).map(r => r.title).join('\n')}

Type "more" to view complete list`

Q6: How to handle special characters in answers?

A: Be careful with escaping in expressions:

javascript

// Use template strings to avoid escaping issues
`Price: $${$('Product').price}
Discount: ${$('Product').discount}%
Description: ${$('Product').description}`

Q7: Can I embed links or buttons in answers?

A: Depends on frontend support. If Markdown is supported:

javascript

`Operation successful!

[View Details](https://example.com/order/${$('Order').id})
[Contact Support](https://example.com/support)`

If not supported, use plain text links:

javascript

`Operation successful!

View Details: https://example.com/order/${$('Order').id}
Contact Support: https://example.com/support`

Next Steps

LLM Node - Learn how to generate AI responses
Conditional Branch - Implement differentiated replies for different conditions
Knowledge Retrieval - Get answer content from knowledge base

Chat Trigger - Learn how to receive user messages
Expression Syntax - Learn how to dynamically generate answer content

Trigger Nodes

Chat Trigger

Action Nodes

Control Nodes

Tool Nodes

Group Nodes

Answer Node

Use Cases

Typical Applications

Node Configuration

Basic Settings (Parameters Panel)

Answer Content

Advanced Settings (Settings Panel)

Node Description

Output Data

Workflow Examples

Example 1: Simple Q&A Bot

Example 2: Knowledge Base Q&A System

Example 3: Differentiated Replies After Classification

Example 4: Multi-step Task Completion Notification

Example 5: Error Handling with Friendly Messages

Best Practices

1. Clear and Friendly Content

2. Handle Different Scenarios

3. Keep It Concise

4. Support Multi-language

5. Add Follow-up Guidance

FAQ

Q1: What's the difference between Answer node and LLM node?

Q2: Can I use multiple Answer nodes in one workflow?

Q3: What formats does the Answer node support?

Q4: How to include line breaks in answers?

Q5: Will long answer content be truncated?

Q6: How to handle special characters in answers?

Q7: Can I embed links or buttons in answers?

Next Steps

Chat Trigger

Answer Node ​

Use Cases ​

Typical Applications ​

Node Configuration ​

Basic Settings (Parameters Panel) ​

Answer Content ​

Advanced Settings (Settings Panel) ​

Node Description ​

Output Data ​

Workflow Examples ​

Example 1: Simple Q&A Bot ​

Example 2: Knowledge Base Q&A System ​

Example 3: Differentiated Replies After Classification ​

Example 4: Multi-step Task Completion Notification ​

Example 5: Error Handling with Friendly Messages ​

Best Practices ​

1. Clear and Friendly Content ​

2. Handle Different Scenarios ​

3. Keep It Concise ​

4. Support Multi-language ​

5. Add Follow-up Guidance ​

FAQ ​

Q1: What's the difference between Answer node and LLM node? ​

Q2: Can I use multiple Answer nodes in one workflow? ​

Q3: What formats does the Answer node support? ​

Q4: How to include line breaks in answers? ​

Q5: Will long answer content be truncated? ​

Q6: How to handle special characters in answers? ​

Q7: Can I embed links or buttons in answers? ​

Next Steps ​

Related Resources ​

Answer Node

Use Cases

Typical Applications

Node Configuration

Basic Settings (Parameters Panel)

Answer Content

Advanced Settings (Settings Panel)

Node Description

Output Data

Workflow Examples

Example 1: Simple Q&A Bot

Example 2: Knowledge Base Q&A System

Example 3: Differentiated Replies After Classification

Example 4: Multi-step Task Completion Notification

Example 5: Error Handling with Friendly Messages

Best Practices

1. Clear and Friendly Content

2. Handle Different Scenarios

3. Keep It Concise

4. Support Multi-language

5. Add Follow-up Guidance

FAQ

Q1: What's the difference between Answer node and LLM node?

Q2: Can I use multiple Answer nodes in one workflow?

Q3: What formats does the Answer node support?

Q4: How to include line breaks in answers?

Q5: Will long answer content be truncated?

Q6: How to handle special characters in answers?

Q7: Can I embed links or buttons in answers?

Next Steps

Related Resources