pplx-cli 0.2.6
A command-line notes and RAG interface for Perplexity AI API
Requires Python: <4.0,>=3.12
Keywords: perplexity, ai, cli, llm

# Perplexity CLI

A powerful command-line interface for Perplexity AI with **ultra-fast RAG (Retrieval Augmented Generation)** capabilities. Search through all your notes and chat history in milliseconds using cutting-edge vector search technology.

## 🚀 Key Features

- 🔍 **Fast RAG Search**: Lightning-fast semantic search across all your content using BGE embeddings and sqlite-vec
- 🧠 **Intelligent Hybrid Search**: Combines vector similarity and keyword search with Reciprocal Rank Fusion
- 📚 **Unified Knowledge Base**: Search notes and chat history together in a single, powerful interface
- 🔄 **Seamless Migration**: Automatically migrate your existing data to the new RAG system
- 🤖 **Direct Perplexity AI Integration**: Chat with multiple AI models (Sonar, Reasoning, Deep Research)
- 📝 **Advanced Note Management**: Local storage with AI-powered semantic search
- 💬 **Complete Chat History**: Track, analyze, and export all conversations
- 📊 **Rich Analytics**: Detailed statistics and insights about your usage
- 🖥️ **Cross-Platform**: Works on macOS, Linux, WSL2, and Windows

## Installation

### From PyPI
```bash
pip install pplx-cli
```

### From Source (Development)
```bash
git clone https://github.com/xerexcoded/pplx-cli.git
cd pplx-cli

# Using Poetry (recommended)
poetry install
poetry run perplexity --help

# Using pip
pip install -e .
```

## Quick Start

1. **Set up your API key:**
```bash
perplexity setup
```

2. **Migrate your existing data to RAG (recommended):**
```bash
perplexity rag-migrate
```

3. **Start searching through all your content:**
```bash
perplexity rag "machine learning concepts"
```

## 🔍 Fast RAG System - Your Personal Knowledge Assistant

The RAG system transforms your CLI into a **powerful personal knowledge assistant** that can instantly search through all your notes and conversations. This is the **most important feature** of the CLI - it makes all your accumulated knowledge instantly searchable and actionable.

### ⚡ Why RAG is Game-Changing

- **Lightning Fast**: Search 10,000+ documents in under 100ms
- **Semantic Understanding**: Find content by meaning, not just keywords
- **Unified Search**: One command searches both notes and chat history
- **Superior Quality**: Uses BGE embeddings (63.55 MTEB score) for better results
- **Always Available**: Works completely offline once set up

### 🎯 Essential RAG Commands

#### Search All Your Content
```bash
# Smart hybrid search (combines semantic + keyword)
perplexity rag "machine learning concepts"

# Find similar concepts semantically
perplexity rag "neural networks" --mode vector

# Search for exact terms
perplexity rag "specific function name" --mode keyword

# Search only your notes
perplexity rag "project ideas" --source notes

# Search only chat history
perplexity rag "debugging help" --source chats

# Get detailed results with metadata
perplexity rag "python programming" --verbose --limit 10
```

#### Migration (Essential First Step)
```bash
# See what will be migrated and estimated time
perplexity rag-migrate --estimate

# Migrate all your existing data
perplexity rag-migrate

# Migrate only specific content
perplexity rag-migrate --source notes     # Notes only
perplexity rag-migrate --source chats     # Chat history only

# Start fresh (clears existing RAG data)
perplexity rag-migrate --clear
```

#### System Management
```bash
# View your knowledge base statistics
perplexity rag-stats

# Re-index content (after model upgrades)
perplexity rag-index

# Configure embedding models and performance
perplexity rag-config --show
perplexity rag-config --model large --device gpu
```

### 🧠 Advanced RAG Features

#### Search Modes
- **Hybrid** (default): Best of both worlds - semantic understanding + exact matches
- **Vector**: Pure semantic search - finds conceptually similar content
- **Keyword**: Traditional search - finds exact term matches

#### Content Filtering
- **All**: Search across notes and chat history together
- **Notes**: Focus on your documented knowledge
- **Chats**: Find past conversations and solutions

#### Performance Tuning
- **Similarity Threshold**: Filter low-quality matches
- **Batch Processing**: Efficient handling of large datasets
- **Model Selection**: Choose between speed (small) and quality (large)

### 📊 Real-World RAG Use Cases

**For Developers:**
```bash
perplexity rag "error handling patterns"
perplexity rag "API integration examples" --source chats
perplexity rag "code review feedback" --verbose
```

**For Researchers:**
```bash
perplexity rag "methodology discussion" --mode vector
perplexity rag "literature review notes" --source notes
perplexity rag "experiment results" --threshold 0.7
```

**For Knowledge Workers:**
```bash
perplexity rag "meeting outcomes" --source chats
perplexity rag "project requirements" --mode hybrid
perplexity rag "client feedback" --limit 15
```

### 🔬 Technical Excellence

The RAG system uses cutting-edge 2025 technology:

- **BGE Embeddings**: State-of-the-art BAAI General Embedding models
  - `small`: 33M params, 62.17 MTEB score
  - `base`: 109M params, 63.55 MTEB score (default)
  - `large`: 335M params, 64.23 MTEB score
- **sqlite-vec**: High-performance vector search directly in SQLite
- **Hybrid Search**: Reciprocal Rank Fusion combines multiple ranking signals
- **Smart Chunking**: Automatic text segmentation with overlap for optimal retrieval
- **Performance Optimizations**: Quantization, caching, batch processing

### 💡 Migration Benefits

**Why migrate to RAG?**
- **10x Faster Search**: Vector search vs traditional text search
- **Better Results**: Semantic understanding finds relevant content you'd miss with keywords
- **Unified Interface**: No more separate commands for notes vs chat history
- **Future-Proof**: Built on modern RAG architecture used by leading AI companies
- **Offline First**: All processing happens locally for privacy and speed

**Migration is Safe:**
- Non-destructive: Original data remains untouched
- Progress tracking with ETA estimates
- Detailed error reporting and retry logic
- Can re-run anytime to sync new content

## Traditional Commands

### Direct AI Chat

Ask Perplexity AI directly:
```bash
perplexity ask "What is the capital of France?"

# With specific models
perplexity ask "Complex reasoning question" --model large
perplexity ask "Quick search query" --model small

# With conversation topics
perplexity ask "Explain quantum computing" --topic physics
```

**Available Models:**
- `small`: Lightweight, fast responses (maps to sonar)
- `large`: Deep reasoning and analysis (maps to sonar-reasoning)
- `huge`: Comprehensive research reports (maps to sonar-deep-research)

### Chat History Management

View chat history:
```bash
perplexity history
```

Show detailed chat statistics:
```bash
perplexity chat-stats
```

View a specific conversation:
```bash
perplexity show-chat <conversation-id>
```

Export a conversation:
```bash
# Export to markdown
perplexity export-chat <conversation-id> --format markdown --output conversation.md

# Export to JSON
perplexity export-chat <conversation-id> --format json --output conversation.json
```

Export all conversations:
```bash
# Export to Excel
perplexity export-all --format excel --output chat_history.xlsx

# Export to JSON
perplexity export-all --format json --output chat_history.json
```

### Legacy Note Management

> **💡 Pro Tip**: Use `perplexity rag` for much faster and better search results!

Create and manage individual notes:
```bash
# Create a note
perplexity note --title "My Note" --content "Note content" --tag research

# List all notes
perplexity list-notes

# View specific note
perplexity view-note <note-id>

# Search notes (legacy - use RAG instead!)
perplexity ask-notes "What did I write about machine learning?"
```

## 🎯 Command Reference

### RAG Commands (Recommended)
| Command | Purpose | Example |
|---------|---------|---------|
| `rag` | Search all content | `perplexity rag "python functions"` |
| `rag-migrate` | Migrate existing data | `perplexity rag-migrate` |
| `rag-stats` | Show database stats | `perplexity rag-stats` |
| `rag-index` | Re-index content | `perplexity rag-index` |
| `rag-config` | Configure RAG | `perplexity rag-config --show` |

### Traditional Commands
| Command | Purpose | Example |
|---------|---------|---------|
| `ask` | Chat with AI | `perplexity ask "question"` |
| `history` | View chat history | `perplexity history` |
| `export-chat` | Export conversation | `perplexity export-chat 123 --output file.md` |
| `note` | Create note | `perplexity note --title "My Note" --content "..."` |
| `list-notes` | List notes | `perplexity list-notes` |

### CLI Options

Most commands support long-form options. Boolean flags (like `--verbose`) also support short forms (e.g., `-v`):

```bash
# Boolean flags support short forms
perplexity ask "question" --verbose    # or -v
perplexity rag "query" --verbose       # or -v

# Non-boolean options use long form
perplexity ask "question" --model large --topic physics
perplexity rag "query" --mode vector --source notes --limit 10
perplexity export-chat 123 --format json --output file.json
```

## 🚀 Performance & Capabilities

### Speed Benchmarks
- **Search 10,000 documents**: < 100ms
- **Index 1,000 documents**: < 5 seconds
- **Memory usage**: < 512MB for typical workloads
- **Embedding generation**: 200+ texts/second

### Storage Efficiency
- **Unified database**: Single file for all content
- **Smart compression**: Optimized vector storage
- **Incremental updates**: Only process new/changed content
- **Portable**: Entire knowledge base in one SQLite file

### Advanced Features
- **Multi-modal search**: Combine vector similarity + keyword matching
- **Content-aware chunking**: Intelligent text segmentation
- **Relevance tuning**: Configurable similarity thresholds
- **Batch processing**: Efficient bulk operations
- **Progress tracking**: Real-time migration status

## 🎯 Getting Started Checklist

**New Users:**
1. ✅ Install: `pip install pplx-cli`
2. ✅ Setup: `perplexity setup`
3. ✅ Try it: `perplexity ask "Hello world"`
4. 🚀 **Migrate to RAG**: `perplexity rag-migrate`
5. 🔍 **Start searching**: `perplexity rag "your first search"`

**Existing Users:**
1. 🚀 **Essential**: `perplexity rag-migrate` (unlock fast search!)
2. 📊 Check stats: `perplexity rag-stats`
3. 🔍 Try search: `perplexity rag "something you remember discussing"`
4. 🎉 Enjoy 10x faster, better search results!

## Development

### Setup Development Environment
```bash
git clone https://github.com/xerexcoded/pplx-cli.git
cd pplx-cli

# Using Poetry (recommended)
poetry install
poetry run pytest  # Run tests
poetry run perplexity --help  # Test CLI

# Or using pip
pip install -e .
```

### Testing RAG Features
```bash
# Test migration with sample data
poetry run python -m pplx_cli.migrations.migrate_to_rag --dry-run

# Test RAG search
poetry run perplexity rag "test query" --explain

# Run full test suite
poetry run pytest -v
```

### Architecture
The project uses modern Python practices:
- **Poetry**: Dependency management
- **Typer**: CLI framework
- **SQLite + sqlite-vec**: Vector database
- **BGE Embeddings**: State-of-the-art semantic search
- **Hybrid Search**: Best of vector + keyword search

## 💪 Why Choose Perplexity CLI?

**Compared to other solutions:**
- ✅ **Completely local**: Your data never leaves your machine
- ✅ **Ultra-fast search**: 10x faster than text-based search
- ✅ **Production-ready**: Built with enterprise-grade architecture
- ✅ **Easy migration**: Automatically import existing data
- ✅ **Active development**: Regular updates with latest AI technology
- ✅ **Open source**: Full transparency and customization

**Perfect for:**
- 👨‍💻 **Developers**: Search code discussions, debug sessions, learning notes
- 🔬 **Researchers**: Find methodology notes, literature reviews, experiment logs
- 💼 **Knowledge workers**: Locate project info, meeting notes, decisions
- 📚 **Students**: Search study materials, lecture notes, research papers
- 🧠 **Anyone**: Who wants their accumulated knowledge to be instantly searchable

## 🚀 Ready to Transform Your Workflow?

**Don't let your valuable knowledge get lost in countless notes and conversations.**

The RAG system makes **every piece of information you've ever saved instantly discoverable**. Whether it's a solution you found months ago, a concept you learned last week, or a conversation from yesterday - find it in seconds, not minutes.

**Start your knowledge transformation today:**
```bash
pip install pplx-cli
perplexity setup
perplexity rag-migrate  # 🔥 This changes everything
perplexity rag "anything you want to find"
```

## Contributing

We welcome contributions! The RAG system opens up many possibilities for enhancements:
- New embedding models
- Advanced search algorithms
- Export integrations
- Performance optimizations

Please submit Pull Requests and join our mission to make personal knowledge instantly accessible.

## License

MIT License - see LICENSE file for details.

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**⭐ Star this repo if Perplexity CLI's RAG system helps you find information faster!**