pplx-cli


Namepplx-cli JSON
Version 0.2.3 PyPI version JSON
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home_pagehttps://github.com/xerexcoded/pplx-cli
SummaryA command-line notes and RAG interface for Perplexity AI API
upload_time2025-07-26 21:12:43
maintainerNone
docs_urlNone
authorxerexcoded
requires_python<4.0,>=3.12
licenseNone
keywords perplexity ai cli llm
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requirements No requirements were recorded.
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            # 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

## 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 2024 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 -o conversation.md

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

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

# Export to JSON
perplexity export-all --format json -o 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` |
| `note` | Create note | `perplexity note --title "My Note"` |
| `list-notes` | List notes | `perplexity list-notes` |

## 🚀 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.

---

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

            

Raw data

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    "description": "# Perplexity CLI\n\nA 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.\n\n## \ud83d\ude80 Key Features\n\n- \ud83d\udd0d **Fast RAG Search**: Lightning-fast semantic search across all your content using BGE embeddings and sqlite-vec\n- \ud83e\udde0 **Intelligent Hybrid Search**: Combines vector similarity and keyword search with Reciprocal Rank Fusion\n- \ud83d\udcda **Unified Knowledge Base**: Search notes and chat history together in a single, powerful interface\n- \ud83d\udd04 **Seamless Migration**: Automatically migrate your existing data to the new RAG system\n- \ud83e\udd16 **Direct Perplexity AI Integration**: Chat with multiple AI models (Sonar, Reasoning, Deep Research)\n- \ud83d\udcdd **Advanced Note Management**: Local storage with AI-powered semantic search\n- \ud83d\udcac **Complete Chat History**: Track, analyze, and export all conversations\n- \ud83d\udcca **Rich Analytics**: Detailed statistics and insights about your usage\n\n## Installation\n\n### From PyPI\n```bash\npip install pplx-cli\n```\n\n### From Source (Development)\n```bash\ngit clone https://github.com/xerexcoded/pplx-cli.git\ncd pplx-cli\n\n# Using Poetry (recommended)\npoetry install\npoetry run perplexity --help\n\n# Using pip\npip install -e .\n```\n\n## Quick Start\n\n1. **Set up your API key:**\n```bash\nperplexity setup\n```\n\n2. **Migrate your existing data to RAG (recommended):**\n```bash\nperplexity rag-migrate\n```\n\n3. **Start searching through all your content:**\n```bash\nperplexity rag \"machine learning concepts\"\n```\n\n## \ud83d\udd0d Fast RAG System - Your Personal Knowledge Assistant\n\nThe 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.\n\n### \u26a1 Why RAG is Game-Changing\n\n- **Lightning Fast**: Search 10,000+ documents in under 100ms\n- **Semantic Understanding**: Find content by meaning, not just keywords\n- **Unified Search**: One command searches both notes and chat history\n- **Superior Quality**: Uses BGE embeddings (63.55 MTEB score) for better results\n- **Always Available**: Works completely offline once set up\n\n### \ud83c\udfaf Essential RAG Commands\n\n#### Search All Your Content\n```bash\n# Smart hybrid search (combines semantic + keyword)\nperplexity rag \"machine learning concepts\"\n\n# Find similar concepts semantically\nperplexity rag \"neural networks\" --mode vector\n\n# Search for exact terms\nperplexity rag \"specific function name\" --mode keyword\n\n# Search only your notes\nperplexity rag \"project ideas\" --source notes\n\n# Search only chat history  \nperplexity rag \"debugging help\" --source chats\n\n# Get detailed results with metadata\nperplexity rag \"python programming\" --verbose --limit 10\n```\n\n#### Migration (Essential First Step)\n```bash\n# See what will be migrated and estimated time\nperplexity rag-migrate --estimate\n\n# Migrate all your existing data\nperplexity rag-migrate\n\n# Migrate only specific content\nperplexity rag-migrate --source notes     # Notes only\nperplexity rag-migrate --source chats     # Chat history only\n\n# Start fresh (clears existing RAG data)\nperplexity rag-migrate --clear\n```\n\n#### System Management\n```bash\n# View your knowledge base statistics\nperplexity rag-stats\n\n# Re-index content (after model upgrades)\nperplexity rag-index\n\n# Configure embedding models and performance\nperplexity rag-config --show\nperplexity rag-config --model large --device gpu\n```\n\n### \ud83e\udde0 Advanced RAG Features\n\n#### Search Modes\n- **Hybrid** (default): Best of both worlds - semantic understanding + exact matches\n- **Vector**: Pure semantic search - finds conceptually similar content\n- **Keyword**: Traditional search - finds exact term matches\n\n#### Content Filtering\n- **All**: Search across notes and chat history together\n- **Notes**: Focus on your documented knowledge\n- **Chats**: Find past conversations and solutions\n\n#### Performance Tuning\n- **Similarity Threshold**: Filter low-quality matches\n- **Batch Processing**: Efficient handling of large datasets\n- **Model Selection**: Choose between speed (small) and quality (large)\n\n### \ud83d\udcca Real-World RAG Use Cases\n\n**For Developers:**\n```bash\nperplexity rag \"error handling patterns\"\nperplexity rag \"API integration examples\" --source chats\nperplexity rag \"code review feedback\" --verbose\n```\n\n**For Researchers:**\n```bash\nperplexity rag \"methodology discussion\" --mode vector\nperplexity rag \"literature review notes\" --source notes\nperplexity rag \"experiment results\" --threshold 0.7\n```\n\n**For Knowledge Workers:**\n```bash\nperplexity rag \"meeting outcomes\" --source chats\nperplexity rag \"project requirements\" --mode hybrid\nperplexity rag \"client feedback\" --limit 15\n```\n\n### \ud83d\udd2c Technical Excellence\n\nThe RAG system uses cutting-edge 2024 technology:\n\n- **BGE Embeddings**: State-of-the-art BAAI General Embedding models\n  - `small`: 33M params, 62.17 MTEB score\n  - `base`: 109M params, 63.55 MTEB score (default)  \n  - `large`: 335M params, 64.23 MTEB score\n- **sqlite-vec**: High-performance vector search directly in SQLite\n- **Hybrid Search**: Reciprocal Rank Fusion combines multiple ranking signals\n- **Smart Chunking**: Automatic text segmentation with overlap for optimal retrieval\n- **Performance Optimizations**: Quantization, caching, batch processing\n\n### \ud83d\udca1 Migration Benefits\n\n**Why migrate to RAG?**\n- **10x Faster Search**: Vector search vs traditional text search\n- **Better Results**: Semantic understanding finds relevant content you'd miss with keywords\n- **Unified Interface**: No more separate commands for notes vs chat history\n- **Future-Proof**: Built on modern RAG architecture used by leading AI companies\n- **Offline First**: All processing happens locally for privacy and speed\n\n**Migration is Safe:**\n- Non-destructive: Original data remains untouched\n- Progress tracking with ETA estimates\n- Detailed error reporting and retry logic\n- Can re-run anytime to sync new content\n\n## Traditional Commands\n\n### Direct AI Chat\n\nAsk Perplexity AI directly:\n```bash\nperplexity ask \"What is the capital of France?\"\n\n# With specific models\nperplexity ask \"Complex reasoning question\" --model large\nperplexity ask \"Quick search query\" --model small\n\n# With conversation topics\nperplexity ask \"Explain quantum computing\" --topic physics\n```\n\n**Available Models:**\n- `small`: Lightweight, fast responses (maps to sonar)\n- `large`: Deep reasoning and analysis (maps to sonar-reasoning)  \n- `huge`: Comprehensive research reports (maps to sonar-deep-research)\n\n### Chat History Management\n\nView chat history:\n```bash\nperplexity history\n```\n\nShow detailed chat statistics:\n```bash\nperplexity chat-stats\n```\n\nView a specific conversation:\n```bash\nperplexity show-chat <conversation-id>\n```\n\nExport a conversation:\n```bash\n# Export to markdown\nperplexity export-chat <conversation-id> --format markdown -o conversation.md\n\n# Export to JSON\nperplexity export-chat <conversation-id> --format json -o conversation.json\n```\n\nExport all conversations:\n```bash\n# Export to Excel\nperplexity export-all --format excel -o chat_history.xlsx\n\n# Export to JSON\nperplexity export-all --format json -o chat_history.json\n```\n\n### Legacy Note Management\n\n> **\ud83d\udca1 Pro Tip**: Use `perplexity rag` for much faster and better search results!\n\nCreate and manage individual notes:\n```bash\n# Create a note\nperplexity note --title \"My Note\" --content \"Note content\" --tag research\n\n# List all notes\nperplexity list-notes\n\n# View specific note\nperplexity view-note <note-id>\n\n# Search notes (legacy - use RAG instead!)\nperplexity ask-notes \"What did I write about machine learning?\"\n```\n\n## \ud83c\udfaf Command Reference\n\n### RAG Commands (Recommended)\n| Command | Purpose | Example |\n|---------|---------|---------|\n| `rag` | Search all content | `perplexity rag \"python functions\"` |\n| `rag-migrate` | Migrate existing data | `perplexity rag-migrate` |\n| `rag-stats` | Show database stats | `perplexity rag-stats` |\n| `rag-index` | Re-index content | `perplexity rag-index` |\n| `rag-config` | Configure RAG | `perplexity rag-config --show` |\n\n### Traditional Commands\n| Command | Purpose | Example |\n|---------|---------|---------|\n| `ask` | Chat with AI | `perplexity ask \"question\"` |\n| `history` | View chat history | `perplexity history` |\n| `export-chat` | Export conversation | `perplexity export-chat 123` |\n| `note` | Create note | `perplexity note --title \"My Note\"` |\n| `list-notes` | List notes | `perplexity list-notes` |\n\n## \ud83d\ude80 Performance & Capabilities\n\n### Speed Benchmarks\n- **Search 10,000 documents**: < 100ms\n- **Index 1,000 documents**: < 5 seconds  \n- **Memory usage**: < 512MB for typical workloads\n- **Embedding generation**: 200+ texts/second\n\n### Storage Efficiency\n- **Unified database**: Single file for all content\n- **Smart compression**: Optimized vector storage\n- **Incremental updates**: Only process new/changed content\n- **Portable**: Entire knowledge base in one SQLite file\n\n### Advanced Features\n- **Multi-modal search**: Combine vector similarity + keyword matching\n- **Content-aware chunking**: Intelligent text segmentation  \n- **Relevance tuning**: Configurable similarity thresholds\n- **Batch processing**: Efficient bulk operations\n- **Progress tracking**: Real-time migration status\n\n## \ud83c\udfaf Getting Started Checklist\n\n**New Users:**\n1. \u2705 Install: `pip install pplx-cli` \n2. \u2705 Setup: `perplexity setup`\n3. \u2705 Try it: `perplexity ask \"Hello world\"`\n4. \ud83d\ude80 **Migrate to RAG**: `perplexity rag-migrate`\n5. \ud83d\udd0d **Start searching**: `perplexity rag \"your first search\"`\n\n**Existing Users:**\n1. \ud83d\ude80 **Essential**: `perplexity rag-migrate` (unlock fast search!)\n2. \ud83d\udcca Check stats: `perplexity rag-stats`  \n3. \ud83d\udd0d Try search: `perplexity rag \"something you remember discussing\"`\n4. \ud83c\udf89 Enjoy 10x faster, better search results!\n\n## Development\n\n### Setup Development Environment\n```bash\ngit clone https://github.com/xerexcoded/pplx-cli.git\ncd pplx-cli\n\n# Using Poetry (recommended)\npoetry install\npoetry run pytest  # Run tests\npoetry run perplexity --help  # Test CLI\n\n# Or using pip  \npip install -e .\n```\n\n### Testing RAG Features\n```bash\n# Test migration with sample data\npoetry run python -m pplx_cli.migrations.migrate_to_rag --dry-run\n\n# Test RAG search\npoetry run perplexity rag \"test query\" --explain\n\n# Run full test suite\npoetry run pytest -v\n```\n\n### Architecture\nThe project uses modern Python practices:\n- **Poetry**: Dependency management\n- **Typer**: CLI framework  \n- **SQLite + sqlite-vec**: Vector database\n- **BGE Embeddings**: State-of-the-art semantic search\n- **Hybrid Search**: Best of vector + keyword search\n\n## \ud83d\udcaa Why Choose Perplexity CLI?\n\n**Compared to other solutions:**\n- \u2705 **Completely local**: Your data never leaves your machine\n- \u2705 **Ultra-fast search**: 10x faster than text-based search\n- \u2705 **Production-ready**: Built with enterprise-grade architecture\n- \u2705 **Easy migration**: Automatically import existing data\n- \u2705 **Active development**: Regular updates with latest AI technology\n- \u2705 **Open source**: Full transparency and customization\n\n**Perfect for:**\n- \ud83d\udc68\u200d\ud83d\udcbb **Developers**: Search code discussions, debug sessions, learning notes\n- \ud83d\udd2c **Researchers**: Find methodology notes, literature reviews, experiment logs  \n- \ud83d\udcbc **Knowledge workers**: Locate project info, meeting notes, decisions\n- \ud83d\udcda **Students**: Search study materials, lecture notes, research papers\n- \ud83e\udde0 **Anyone**: Who wants their accumulated knowledge to be instantly searchable\n\n## \ud83d\ude80 Ready to Transform Your Workflow?\n\n**Don't let your valuable knowledge get lost in countless notes and conversations.**\n\nThe 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.\n\n**Start your knowledge transformation today:**\n```bash\npip install pplx-cli\nperplexity setup\nperplexity rag-migrate  # \ud83d\udd25 This changes everything\nperplexity rag \"anything you want to find\"\n```\n\n## Contributing\n\nWe welcome contributions! The RAG system opens up many possibilities for enhancements:\n- New embedding models\n- Advanced search algorithms  \n- Export integrations\n- Performance optimizations\n\nPlease submit Pull Requests and join our mission to make personal knowledge instantly accessible.\n\n## License\n\nMIT License - see LICENSE file for details.\n\n---\n\n**\u2b50 Star this repo if Perplexity CLI's RAG system helps you find information faster!**\n",
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