!Banner image

n8n-nodes-perplexity

This is an n8n community node that integrates with the Perplexity AI API. It allows you to use Perplexity's search-grounded AI models in your n8n workflows.

Perplexity AI provides real-time search-grounded AI responses using various models including Sonar, Sonar Pro, and specialized research models.

Installation

Follow the installation guide in the n8n community nodes documentation.

$3

1. Go to Settings > Community Nodes.
2. Select Install.
3. Enter n8n-nodes-perplexity in Enter npm package name.
4. Agree to the risks of using community nodes: select I understand the risks of installing unverified code from a public source.
5. Select Install.

After installing the node, you can use it like any other node in your workflows.

$3

To get started install the package in your n8n root directory:

``bash
npm install n8n-nodes-perplexity
`

For Docker-based deployments add the following line before the font installation command in your n8n Dockerfile:

`dockerfile
RUN cd /usr/local/lib/node_modules/n8n && npm install n8n-nodes-perplexity
`

Credentials

You need to configure Perplexity API credentials to use this node:

1. Create a new credential of type Perplexity API
2. Enter your Perplexity API key
- Get your API key from Perplexity AI Settings

Supported Operations

$3

Generate AI responses using Perplexity's search-grounded models.

#### Available Models

- Sonar Deep Research (sonar-deep-research): Comprehensive, expert-level research with detailed reports
- Sonar Reasoning Pro (sonar-reasoning-pro): Premier reasoning with Chain of Thought powered by DeepSeek R1
- Sonar Pro (sonar-pro): Premier search offering with advanced query support
- Sonar (sonar): Lightweight and cost-effective search-grounded responses
- R1-1776 (r1-1776): Uncensored, unbiased version of DeepSeek R1

#### Parameters

Required:
- Model: Choose from available Perplexity models
- Messages: Array of conversation messages with roles (system, user, assistant)
- Text Only: Simple text messages
- Multi-modal: Text with images (base64 or HTTPS URLs)

Optional:
- Max Tokens: Maximum number of tokens to generate (default: 1000)
- Temperature: Controls randomness (0-2, default: 0.7)
- Top P: Controls diversity via nucleus sampling (0-1, default: 1)
- Stream: Enable streaming responses (default: false)
- Presence Penalty: Penalize new tokens based on presence (-2 to 2, default: 0)
- Frequency Penalty: Penalize tokens based on frequency (-2 to 2, default: 0)
- Search Filters: Domain filtering, date ranges, user location, context size
- Image Options: Include images, filter by type and size

#### Response Format

Configure structured output formats:

- Text: Default text response
- JSON Schema: Structured JSON output with schema validation
- Regex: Output matching a specific regex pattern

Usage Examples

$3

`json
{
"model": "sonar-pro",
"messages": [
{
"role": "system",
"content": "You are a helpful AI assistant."
},
{
"role": "user",
"content": "What are the latest developments in AI?"
}
]
}
`

$3

`json
{
"model": "sonar-deep-research",
"messages": [
{
"role": "user",
"content": "Provide a comprehensive analysis of renewable energy trends in 2024"
}
],
"max_tokens": 2000
}
`

$3

`json
{
"model": "sonar",
"messages": [
{
"role": "user",
"content": "Extract key information about Apple Inc."
}
],
"response_format": {
"type": "json_schema",
"json_schema": {
"schema": {
"type": "object",
"properties": {
"company_name": {"type": "string"},
"founded": {"type": "string"},
"headquarters": {"type": "string"},
"ceo": {"type": "string"}
}
}
}
}
}
`

$3

`json
{
"model": "sonar-pro",
"messages": [
{
"role": "user",
"content": "What are the latest AI research papers on transformer models?"
}
],
"searchFilters": {
"search_domain_filter": ["academic"],
"search_recency_filter": "week",
"search_context_size": "detailed"
},
"imageOptions": {
"include_images": true,
"image_filter": "graphics"
}
}
`

$3

`json
{
"model": "sonar-pro",
"messages": [
{
"role": "user",
"contentType": "multimodal",
"textContent": "Can you describe this image and tell me what you see?",
"images": {
"imageValues": [
{
"imageType": "url",
"imageUrl": "https://example.com/path/to/image.jpg"
}
]
}
}
]
}
`

$3

`json
{
"model": "sonar-pro",
"messages": [
{
"role": "user",
"contentType": "multimodal",
"textContent": "Analyze this screenshot for any issues",
"images": {
"imageValues": [
{
"imageType": "base64",
"imageFormat": "png",
"base64Data": "iVBORw0KGgoAAAANSUhEUgAA..."
}
]
}
}
]
}
`

Features

- ✅ Full Perplexity API support
- ✅ All available models (Sonar, Sonar Pro, Deep Research, R1-1776)
- ✅ Conversation history with multiple message roles
- ✅ Advanced parameters (temperature, top_p, penalties)
- ✅ Structured output formats (JSON Schema, Regex)
- ✅ Streaming support
- ✅ Search domain filtering (Academic, YouTube, Reddit, Wolfram Alpha, etc.)
- ✅ Date range and recency filtering
- ✅ User location-based search
- ✅ Search context size control
- ✅ Image search and filtering options
- ✅ Multi-modal support (text + images)
- ✅ Base64 image upload (PNG, JPEG, WEBP, GIF up to 5MB)
- ✅ HTTPS URL image references
- ✅ Built-in credential testing
- ✅ Comprehensive error handling

API Reference

This node is built according to the Perplexity API documentation. For detailed API information, visit:

- Getting Started
- Model Cards
- Structured Outputs
- Prompt Guide

Important Notes

$3


- Base64 images: Maximum 5MB per image
- Supported formats: PNG, JPEG, WEBP, GIF
- HTTPS URLs: Must be publicly accessible and point directly to image files
- Model compatibility: sonar-deep-research` does not support image input
- Structured outputs: Image and regex cannot be used together in the same request

$3

- Domain filters work with all Sonar models
- Academic filter provides research-focused results
- Date range filters help find recent or historical information
- User location enables localized search results

Compatibility

- n8n version: 1.0.0+
- Node.js version: 20.15+

Resources

- n8n community nodes documentation
- Perplexity AI Documentation
- Perplexity AI Website

License

MIT