Perplexed: AI Content Generation for Obsidian

Perplexed is an Obsidian plugin that enables AI-powered content generation with source citations using Perplexity, Anthropic Claude, Google Gemini (with Google Search grounding), and Perplexica / Vane (self-hosted). This plugin brings research-grade AI capabilities directly into your Obsidian workspace, allowing you to generate well-cited content for your notes.

🎯 Key Features

• Source-Cited AI Responses: Get AI-generated content with proper citations and references
  • Default format:

  Citations

[1]: 2024, Dec 13. What is GRC (Governance, Risk and Compliance) - Metricstream. Published: 2024-05-01 | Updated: 2024-12-13

[2]: 2025, Jun 16. Governance, risk and compliance (GRC): Definitions and resources. Published: 2025-05-27 | Updated: 2025-06-16

• Multiple AI Providers: Support for Perplexity, Anthropic Claude, Google Gemini (with Google Search grounding), Perplexica / Vane (self-hosted), and LM Studio (local)
• Streaming Responses: Real-time streaming of AI responses for better UX
• Flexible Configuration: Customizable endpoints, models, and parameters
• Deep Research Mode: Comprehensive research across hundreds of sources
• Local LLM Support: Integration with LM Studio for local AI processing

Network use and accounts

Perplexed contacts these remote services on your behalf when you invoke their respective commands. Nothing is sent automatically — only the prompts you submit through a command modal, and any text you have explicitly selected when invoking selection-based commands.

When Gemini's google_search grounding is enabled, the plugin also issues follow-up GET requests to vertexaisearch.cloud.google.com/grounding-api-redirect/… URLs to resolve them to the real source page (so your ### Citations footer contains durable source URLs rather than short-lived Google redirects). The follow-up requests go through Obsidian's requestUrl (Node-side), not the browser fetch — no cross-origin permissions involved, and the request is strictly URL-resolution, no auth header.

The plugin does not collect telemetry, ship vault content anywhere else, or update itself — Obsidian handles plugin updates through the community plugin directory.

📋 Table of Contents

• User Onboarding
  • Installation
  • Initial Setup
  • Using Perplexity
  • Using Google Gemini
  • Using Perplexica / Vane
  • Using LM Studio
  • Command Reference
  • Directory Templates
• Developer Onboarding
  • Project Structure
  • Development Setup
  • Architecture Overview
  • Contributing

User Onboarding

Installation

1. Download the Plugin:

   • Download the latest release from the releases page
   • Extract the ZIP file to your Obsidian plugins folder

2. Enable in Obsidian:

   • Open Obsidian Settings → Community Plugins
   • Turn off Safe Mode
   • Click "Install plugin from file"
   • Select the extracted plugin folder
   • Enable the "Perplexed" plugin

Initial Setup

1. Configure Perplexity (Recommended for most users)

Perplexity is a commercial AI service that provides high-quality, source-cited responses.

1. Get API Key:

   • Visit Perplexity AI
   • Sign up for an account
   • Navigate to API settings to get your API key

2. Configure in Plugin:

   • Open Obsidian Settings → Community Plugins → Perplexed
   • Enter your Perplexity API key
   • The default endpoint should work: https://api.perplexity.ai/chat/completions

2. Configure Google Gemini (Free tier available)

Google Gemini is Google's commercial AI service. The google_search grounding tool returns per-segment citation attribution — meaning each cited sentence is mapped back to the specific URL it came from, which becomes the verbatim quote in your ### Citations footer. AI Studio's free tier requires no credit card to get started.

1. Get API key:

   • Visit Google AI Studio
   • Sign in with a Google account
   • Click "Create API key" → copy the AIza… string

2. Configure in plugin:

   • Open Obsidian Settings → Community Plugins → Perplexed
   • Scroll to Gemini (Google)
   • Paste your API key into "Gemini API key"
   • Default model: gemini-flash-latest (always-current Flash, free-tier friendly) — gemini-pro-latest and pinned gemini-2.5-pro / gemini-2.5-flash also available
   • Leave Enable Google search grounding by default on for source-cited research
   • Leave Resolve citation urls on — this is what turns the grounding-redirect URLs into the real source URLs in your citations footer

3. Configure Perplexica / Vane (self-hosted — requires local install)

Perplexica / Vane is a free, open-source AI search engine that you run locally on your own machine. This plugin does not bundle the server or proxy to a hosted instance — you must install and run it yourself before the "Ask Perplexica / Vane" command will work.

Note on naming: The maintainer (ItzCrazyKns) renamed the open-source self-hosted repo from Perplexica to Vane on 2026-03-09 (commit feat(app): rename to 'vane'). The old GitHub URL ItzCrazyKns/Perplexica redirects to ItzCrazyKns/Vane. A hosted service at perplexica.io remains live under the Perplexica name — that's a separate hosted product, not what you self-install for use with this plugin. The local API surface this plugin talks to (/api/search, focus modes, optimization modes) is unchanged across the rename.

1. Install Perplexica / Vane locally:

   • Repo and full installation docs: github.com/ItzCrazyKns/Vane
   • Docker is the recommended install path; the repo's README walks through docker-compose setup, configuring SearXNG, and choosing your local LLM provider (Ollama, LM Studio, OpenAI-compatible endpoints, etc.).
   • Confirm the server is running and reachable, e.g.: curl http://localhost:3030/api/search

2. Configure in this plugin:

   • Open Obsidian Settings → Community Plugins → Perplexed
   • Set the Perplexica / Vane endpoint to where your local server is listening (default: http://localhost:3030/api/search)
   • Pick a focus mode, optimization mode, and the local model you've configured the server to use

4. Configure LM Studio (Optional)

For local AI processing without internet dependency:

1. Install LM Studio:

   • Download from LM Studio
   • Install and start the application

2. Configure in Plugin:

   • Set LM Studio endpoint: http://localhost:1234/v1/chat/completions
   • Choose your preferred local model

Using Perplexity

Quick Start

1. Open Command Palette: Ctrl/Cmd + Shift + P
2. Run Command: Type "Ask Perplexity" and select it
3. Enter Your Question: Type your research question
4. Configure Options:
   • Model: Choose from available Perplexity models
   • Citations: Enable/disable source citations
   • Images: Include image results
   • Recency Filter: Filter results by time period
   • Streaming: Enable real-time response streaming

Available Models

• sonar-pro: Balanced performance and quality (recommended)
• sonar-small: Fast responses, good for simple queries
• sonar-deep-research: Comprehensive research across hundreds of sources
• llama-3.1-sonar-small-128k-online: Extended context window
• llama-3.1-sonar-large-128k-online: Large model with extended context

Example Usage

Basic Research Query

Question: "What are the latest developments in quantum computing?"
Model: sonar-pro
Citations: Enabled
Recency: Past month

Deep Research Analysis

Question: "Analyze the impact of AI on healthcare in the last 5 years"
Model: sonar-deep-research
Citations: Enabled
Recency: Past 5 years

Note: Deep research mode conducts exhaustive analysis across hundreds of sources and may take 30-60 seconds.

Response Format

Perplexity responses include:

• Main Answer: Comprehensive response to your question
• Citations: Numbered references with source links
• Images: Relevant images (if enabled)
• Related Questions: Additional questions for exploration (if enabled)

Text Enhancement

Enhance selected text using Perplexity AI to improve clarity, add details, and make content more comprehensive.

Quick Start

1. Select Text: Highlight the text you want to enhance in your note
2. Open Command Palette: Ctrl/Cmd + Shift + P
3. Run Command: Type "Enhance Selected Text with Perplexity" and select it
4. Configure Options:
   • Model: Choose from available Perplexity models
   • Citations: Enable/disable source citations
   • Images: Include image results
   • Streaming: Enable real-time response streaming

Enhancement Options

• Replace Original: Replace the selected text with the enhanced version
• Insert Below: Insert the enhanced text below the current cursor position
• Preview: Review the enhanced text before applying changes

Example Usage

Original Text:

AI is changing how we work.

Enhanced Text:

Artificial Intelligence (AI) is fundamentally transforming how we work across various industries and sectors. From automating routine tasks to enabling more sophisticated decision-making processes, AI technologies are reshaping traditional workflows and creating new opportunities for productivity and innovation.

Using Google Gemini

Quick start

1. Open Command Palette: Ctrl/Cmd + Shift + P
2. Run Command: Type "Ask Gemini" and select it
3. Enter your question in the textarea
4. Configure options in the modal:
   • Model: gemini-flash-latest (recommended, free-tier friendly), gemini-pro-latest, or pinned 2.5 versions
   • Enable Google search grounding: server-side google_search tool; emits per-segment citations
   • Append Google searches list: appends a Markdown bullet list of the queries Gemini ran, each linked to google.com/search (Markdown-native substitute for Google's required Search Suggestions chip)
   • Resolve citation urls: resolves the vertexaisearch.cloud.google.com grounding-redirect URLs to durable source URLs + real page titles before writing the citations footer
   • Stream response: incremental writing to the note as the response arrives

Available models

• gemini-flash-latest: Google's always-current Flash alias, free-tier friendly (recommended default)
• gemini-pro-latest: Always-current Pro alias for deepest reasoning
• gemini-2.5-pro: Pinned Pro version (free-tier quota typically exhausted; paid tier required)
• gemini-2.5-flash: Pinned Flash version for reproducibility

Why Gemini's citations are different

Gemini's groundingSupports[] carries per-segment attribution that survives the full response round-trip — meaning the ### Citations footer contains the verbatim quote per source, attached to the prose above it. Compare to Claude's web_search_20260209, where the dynamic-filter sandbox post-processes search results and per-claim attachment doesn't survive: text blocks come back with citations: null.

The plugin walks two layers of provenance:

Page-level chunks become URL-and-title fallbacks; segment-level supports enrich them with the verbatim quote Gemini grounded against. Citation footer mirrors Claude's exactly ([N]: [Title](url). > cited_text) so cite-wide's hex-substitution pass works on Gemini output too.

Example usage

Basic research with grounding

Question: "Who won the 2024 Nobel Prize in Physics and what was the citation?"
Model: gemini-flash-latest
Grounding: Enabled
Resolve URLs: Enabled

Lands in the note with prose like:

The 2024 Nobel Prize in Physics was jointly awarded to John J. Hopfield and Geoffrey Hinton.

The Nobel Prize Committee cited them "for foundational discoveries and inventions that enable machine learning with artificial neural networks".

…followed by a ### Google Searches section listing the queries Gemini issued, and a ### Citations footer where each entry is [N]: [Real Page Title](https://nobelprize.org/…) with the verbatim segment as a blockquote.

Using Perplexica / Vane

Quick Start

1. Open Command Palette: Ctrl/Cmd + Shift + P
2. Run Command: Type "Ask Perplexica / Vane" and select it
3. Enter Your Question: Type your research question
4. Configure Options:
   • Focus Mode: Choose search specialization
   • Optimization: Balance speed vs. quality
   • Streaming: Enable real-time response streaming

Focus Modes

• webSearch: General web search (default)
• academicSearch: Academic and research papers
• writingAssistant: Writing and content creation
• wolframAlpha: Mathematical and computational queries
• youtubeSearch: Video content search
• redditSearch: Reddit community discussions

Optimization Modes

• speed: Fastest responses
• balanced: Good balance of speed and quality
• quality: Highest quality responses

Example Usage

Academic Research

Question: "What are the current theories about dark matter?"
Focus Mode: academicSearch
Optimization: quality

Content Writing

Question: "Help me write an introduction about climate change"
Focus Mode: writingAssistant
Optimization: balanced

Using LM Studio

Quick Start

1. Open Command Palette: Ctrl/Cmd + Shift + P
2. Run Command: Type "Ask LM Studio" and select it
3. Enter Your Question: Type your question
4. Configure Options:
   • Model: Choose your local model
   • System Prompt: Customize AI behavior
   • Temperature: Control response creativity
   • Max Tokens: Limit response length

Example Usage

Creative Writing

Question: "Write a short story about a robot learning to paint"
Model: ibm/granite-3.2-8b
Temperature: 0.8
System Prompt: "You are a creative storyteller who writes engaging narratives."

Technical Analysis

Question: "Explain how neural networks work"
Model: microsoft/phi-4-reasoning-plus
Temperature: 0.3
System Prompt: "You are a technical expert who explains complex concepts clearly."

Command Reference

Perplexity Commands

Google Gemini Commands

Perplexica / Vane Commands

LM Studio Commands

Keyboard Shortcuts

You can set custom keyboard shortcuts for any command:

1. Open Obsidian Settings → Hotkeys
2. Search for "Perplexed" commands
3. Assign your preferred shortcuts

Directory Templates

Per-folder content generation — one template fills a whole category of files.

Originally specced as "prompt outlines"; the shipped paradigm is broader and is called directory templates throughout the code and command palette. Full reference: docs/directory-templates.md. Engineering changelog: changelog/2026-05-10_01.md.

Why this exists

A working Obsidian vault collects categories of files that share a shape — concepts, vocabulary terms, sources, tooling profiles. Filling them out one editor-callback at a time is untenable when you have hundreds or thousands. A directory template is a single markdown file that says "for any file under concepts/**, here is the structure to fill and the system prompt to use," and the runtime applies it to one file or a whole folder via Perplexity research with streaming writes.

The three primitives

1. Template — a markdown file in Content-Dev/Templates/ with frontmatter (applies-to-paths glob), a fenced cft config block (provider, model, return flags, system prompt with interpolation tokens like {{basename}} and {{frontmatter.tags}}), and a heading skeleton that becomes the user prompt. Everything below the first *** divider is excluded from the request — it's your scratch space.
2. Commands — Apply directory template to current file auto-matches via the glob; Apply directory template to folder runs a batch with a confirmation modal; Stop directory template batch halts a running batch.
3. Cleanup pipeline — after the SSE stream completes, the runtime wraps <think> blocks, swaps [IMAGE N: <description>] markers for real embeds (with a fallback # Images section when the model didn't emit markers but Perplexity returned images), strips unreplaced placeholders, appends a # Sources footer in the format cite-wide can convert to hex citations, and stamps cf_last_run + cf_last_run_model into the target's frontmatter.

Partials and preambles — shared guidance across templates

Two peer folders alongside templates/ keep editorial rules vault-visible and DRY:

Content-Dev/
├── templates/         (your four profile templates)
├── partials/          (reusable snippets: mermaid-discipline, etc.)
│   └── mermaid-discipline.md
└── preambles/         (auto-attached to every request as system / user messages)
    ├── inline-citation.md
    ├── image-placement.md
    └── research-framing.md

• {{include: name}} in a template body splices in partials/name.md recursively (depth-limited, cycle-detected). Missing files show as inline [[include: name — file not found]] markers so typos stay visible.
• Preambles auto-attach to every Perplexity request with bundled defaults as fallback. Settings tab exposes Partials root, Preambles root, System preambles (default: inline-citation), User preambles (default: image-placement when return-images is on).
• Per-template overrides in the cft fence: preambles: { system: [...], skip-user: [...], skip-all: true }.

Fix the mermaid quoting rule once in partials/mermaid-discipline.md and every future template generation picks it up — no template editing required.

Shipped templates

Four templates ship inlined into the plugin and seed into your vault on first plugin load:

All four use Perplexity's sonar-pro (deep-research is unreliable for image return).

Auto-seed behavior

On first plugin load, Perplexed writes the four templates plus a user-facing README.md to Content-Dev/Templates/ in your vault. The seeder uses a two-tier policy:

• README — always ensured present; if you delete it, the next plugin load writes it back.
• Templates — only seeded when the templates folder is missing or contains no non-README markdown. A folder with even one shipped template is treated as user-managed and left alone.

A Re-seed templates button in Settings → Directory templates writes any shipped file whose filename doesn't already exist — useful for pulling in a new template after a plugin update without overwriting your edits.

Writing your own template

Copy any shipped template under a new filename, change the frontmatter (title, description, applies-to-paths glob), rewrite the cft block's system: prompt for your domain, and rewrite the heading skeleton with the structure you want. Save in Content-Dev/Templates/. The plugin picks it up on the next palette invocation — no reload needed.

For interpolation tokens, the full cft block grammar, the cleanup pipeline mechanics, the editorial stance rationale, frontmatter stamps, and known limits — see docs/directory-templates.md.

Developer Onboarding

Project Structure

perplexed-plugin/
├── main.ts                 # Main plugin file with all functionality
├── manifest.json           # Plugin metadata and requirements
├── package.json            # Dependencies and build scripts
├── esbuild.config.mjs      # Build configuration
├── tsconfig.json           # TypeScript configuration
├── styles.css              # Plugin styles (if any)
└── README.md              # This file

Development Setup

Prerequisites

• Node.js (v18 or higher)
• pnpm (recommended) or npm
• Obsidian desktop application
• Git

Installation

1. Clone the Repository:

   git clone https://github.com/lossless-group/perplexed-plugin.git
   cd perplexed-plugin
   

2. Install Dependencies:

pnpm install

3. **Build the Plugin**:
```bash
pnpm build

4. Development Mode:

pnpm dev

### Testing Your Plugin

1. **Create Symbolic Link** (macOS/Linux):
   ```bash
   ln -s /path/to/your/plugin /path/to/obsidian/vault/.obsidian/plugins/perplexed

2. Windows (PowerShell):

   New-Item -ItemType SymbolicLink -Path "C:\path\to\obsidian\vault\.obsidian\plugins\perplexed" -Target "C:\path\to\your\plugin"
   

3. Enable in Obsidian:

   • Open Obsidian Settings → Community Plugins
   • Disable Safe Mode
   • Enable the "Perplexed" plugin

Architecture Overview

Core Components

1. PerplexedPlugin Class (main.ts):

   • Main plugin class extending Obsidian's Plugin
   • Manages settings, commands, and UI components
   • Handles API interactions with all providers

2. Settings Management:

   • PerplexedPluginSettings interface defines all configurable options
   • PerplexedSettingTab provides the settings UI
   • Settings are persisted using Obsidian's data API

3. Command Registration:

   • registerPerplexityCommands(): Perplexity-specific commands
   • registerPerplexicaCommands(): Perplexica-specific commands
   • registerLMStudioCommands(): LM Studio-specific commands

4. API Integration:

   • queryPerplexity(): Handles Perplexity API calls
   • queryPerplexica(): Handles Perplexica API calls
   • queryLMStudio(): Handles LM Studio API calls

Key Features Implementation

Streaming Responses

// Example from queryPerplexity method
if (useStreaming) {
    const reader = response.body?.getReader();
    while (true) {
        const { done, value } = await reader.read();
        if (done) break;
        
        const chunk = new TextDecoder().decode(value);
        // Process and display chunk in real-time
    }
}

Modal Interfaces

Each command uses Obsidian's Modal class to create user-friendly input forms:

const modal = new (class extends Modal {
    private queryInput!: HTMLTextAreaElement;
    
    onOpen() {
        // Create form elements
    }
    
    async onSubmit() {
        // Handle form submission
    }
})(this.app, this, editor);

Error Handling

Comprehensive error handling for API failures, network issues, and invalid configurations:

try {
    const response = await fetch(endpoint, options);
    if (!response.ok) {
        throw new Error(`HTTP error! status: ${response.status}`);
    }
} catch (error) {
    new Notice(`Error: ${error.message}`);
    console.error('API Error:', error);
}

Configuration Management

The plugin supports extensive configuration through the settings interface:

interface PerplexedPluginSettings {
    perplexityApiKey: string;
    perplexityEndpoint: string;
    perplexicaEndpoint: string;
    lmStudioEndpoint: string;
    defaultModel: string;
    defaultOptimizationMode: string;
    defaultFocusMode: string;
    // ... additional settings
}

Build System

The project uses esbuild for fast compilation:

// esbuild.config.mjs
import esbuild from 'esbuild';
import process from 'process';
import builtins from 'builtin-modules';

const banner =
`/*
THIS IS A GENERATED/BUNDLED FILE BY ESBUILD
if you want to view the source, please visit the github repository of this plugin
*/
`;

const prod = (process.argv[2] === 'production');

esbuild.build({
    banner: {
        js: banner,
    },
    entryPoints: ['main.ts'],
    bundle: true,
    external: [
        'obsidian',
        'electron',
        '@codemirror/autocomplete',
        '@codemirror/collab',
        '@codemirror/commands',
        '@codemirror/language',
        '@codemirror/lint',
        '@codemirror/search',
        '@codemirror/state',
        '@codemirror/view',
        '@lezer/common',
        '@lezer/highlight',
        '@lezer/lr',
        ...builtins],
    format: 'cjs',
    watch: !prod,
    target: 'es2018',
    logLevel: "info",
    sourcemap: prod ? false : 'inline',
    treeShaking: true,
    outfile: 'main.js',
}).catch(() => process.exit(1));

Contributing

Development Workflow

1. Create Feature Branch:

   git checkout -b feature/your-feature-name
   

2. Make Changes:

   • Follow TypeScript best practices
   • Add proper error handling
   • Include JSDoc comments for public methods

3. Test Your Changes:

   pnpm build
   # Test in Obsidian

4. Submit Pull Request:
   • Include clear description of changes
   • Add tests if applicable
   • Update documentation

Code Style Guidelines

• Use TypeScript strict mode
• Follow Obsidian plugin conventions
• Use async/await for API calls
• Implement proper error handling
• Add JSDoc comments for public APIs

Testing

Currently, testing is manual through Obsidian. To test:

1. Build the plugin: pnpm build
2. Enable in Obsidian
3. Test all commands and settings
4. Verify error handling with invalid configurations

Common Development Tasks

Adding a New AI Provider

1. Add Settings:

   interface PerplexedPluginSettings {
       newProviderEndpoint: string;
       newProviderApiKey: string;
       // ... other settings
   }
   

2. Add Query Method:

   public async queryNewProvider(query: string, options: any): Promise<void> {
       // Implementation
   }
   

3. Register Commands:

   private registerNewProviderCommands(): void {
       this.addCommand({
           id: 'ask-new-provider',
           name: 'Ask New Provider',
           editorCallback: (editor: Editor) => {
               // Modal implementation
           }
       });
   }
   

4. Update Settings UI: Add configuration options to PerplexedSettingTab.display()

Modifying Response Format

The plugin inserts responses directly into the editor. To modify the format:

// In query methods, modify the headerText
const headerText = `\n\n***\n## Custom Header\n**Question:** ${query}\n\n### **Response**:\n\n`;

Troubleshooting

Common Issues

1. API Key Not Working:

   • Verify API key is correct
   • Check API key permissions
   • Ensure endpoint URL is correct

2. Network Errors:

   • Check internet connection
   • Verify firewall settings
   • Test endpoint accessibility

3. Plugin Not Loading:

   • Check Obsidian console for errors
   • Verify plugin is enabled
   • Check for conflicting plugins

Debug Mode

Enable debug logging by checking the browser console:

1. Open Obsidian
2. Press Ctrl/Cmd + Shift + I (Developer Tools)
3. Check Console tab for plugin logs

Getting Help

• Check the Issues page
• Review the Discussions forum
• Contact the development team

About The Lossless Group

The Lossless Group is a loose collection of individuals and organizations interested in creating winning formulae for using AI and Collaborative Tooling. We consult, invest in startups, run Venture Capital Funds, host Hackathons, build products, write content, and contribute to open source projects.

We are committed to playing on the frontiers of technology and staying curious and engaged.

License: MIT
Author: The Lossless Group
Support: GitHub Issues