leindex 1.1.1

LeIndex: AI-powered code search and indexing system with MCP integration - Performance Optimization Release

LeIndex

AI-Powered Multi-Project Code Search With Advanced Memory Management

Lightning-fast semantic code search with global index, cross-project search, and intelligent memory management. Find code by meaning, not just by matching text.

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The LeIndex experience - powerful, fast, and beautiful

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✨ What Makes LeIndex Special?

LeIndex isn't just another code search tool. It's your intelligent code companion that understands what you're looking for, not just where it might be typed.

Imagine searching for "authentication flow" and finding not just files containing those words, but the actual authentication logic, login handlers, session management, and security patterns - even if they're named completely differently. That's the magic of semantic search! 🎯

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🚀 Quick Start (You'll Be Searching in Under 2 Minutes. It's Easier Than Making Coffee!)

One-Click Installation

The easiest way to get started:

Requirements

• Python 3.10 or higher
• 4GB RAM minimum (8GB+ for large codebases)
• About 1GB disk space

Linux/Unix:

curl -sSL https://raw.githubusercontent.com/scooter-lacroix/LeIndex/master/install.sh | bash

macOS:

curl -sSL https://raw.githubusercontent.com/scooter-lacroix/LeIndex/master/install_macos.sh | bash

Windows:

irm https://raw.githubusercontent.com/scooter-lacroix/LeIndex/master/install.ps1 | iex

That's it. The installer will:

• ✅ Install LeIndex MCP server
• ✅ Detect your AI tools (Claude Code, Cursor, etc.)
• ✅ Configure integrations automatically
• ✅ Install optional skills for enhanced workflows

Manual installation? See below ↓

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# Install LeIndex - seriously, that's it
pip install leindex

# Index your codebase (no Docker, no databases, no headache)
leindex init /path/to/your/project
leindex index /path/to/your/project

# Search like a wizard
leindex-search "authentication logic"

# Or use it via MCP in Claude, Cursor, or your favorite AI assistant
# LeIndex MCP server does the heavy lifting automatically!

OR

PIP Install

pip install leindex

That's literally it. No Docker. No databases. No configuration files (unless you want them). Just works. ✨

Verify It's Alive

leindex --version
# Output: LeIndex 2.0.2 - Ready to search! 🚀

Install from Source (For the Adventurous)

git clone https://github.com/scooter-lacroix/leindex.git
cd leindex
pip install -e .

Boom! You're now searching your codebase at the speed of thought. 🎉

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🎯 Why Developers Love LeIndex

🔥 Zero Dependencies, Zero Drama

• No Docker - Your laptop will thank you
• No PostgreSQL - No database setup nightmares
• No Elasticsearch - No Java memory leaks
• No RabbitMQ - No message queue complexity
• Just pure Python magic - pip install and you're done

⚡ Blazing Fast Performance

• LEANN vector search - Find similar code in milliseconds
• Tantivy full-text search - Rust-powered Lucene goodness
• Hybrid scoring - Best of both worlds: semantic + lexical
• Handles 100K+ files - Scale from side projects to monorepos

🧠 Semantic Understanding

• CodeRankEmbed embeddings - Understands code meaning and intent
• Finds by concept - Search "error handling" and find try/except, error types, logging, and recovery patterns
• Smart symbol search - Jump to definitions and references instantly
• Regex power - For when you need precise pattern matching

🏠 Privacy-First & Self-Hosted

• Your code stays yours - Nothing leaves your machine
• Works offline - No internet required after installation
• No telemetry - We don't track your searches
• Enterprise-ready - Deploy on your own infrastructure

🤖 MCP-Native Design

• First-class MCP support - Built from the ground up for Model Context Protocol
• AI assistant ready - Works seamlessly with Claude, Cursor, Windsurf, and more
• Token efficient - Saves ~200 tokens per session (no hook overhead!)
• Optional skill integration - For complex multi-project workflows

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🎪 The LeIndex Magic Show

🔍 Search That Reads Your Mind

# Search semantically
results = indexer.search("authentication flow")

# Get results that actually make sense:
# - Login handlers (even if named 'sign_in')
# - Session management (even if called 'user_state')
# - JWT verification (even if labeled 'token_check')
# - Password hashing (even if in 'crypto_utils')

📊 The Secret Sauce (Technology Stack)

Component	Technology	Superpower
Vector Search	LEANN	Storage-efficient semantic similarity
Code Brain	CodeRankEmbed	Understands code meaning & intent
Text Search	Tantivy	Rust-powered Lucene (fast!)
Metadata	SQLite	Reliable ACID-compliant storage
Analytics	DuckDB	In-memory analytical queries
Async Engine	asyncio	Built-in Python async (no RabbitMQ needed!)

🏗️ Architecture That Makes Sense

┌─────────────────────────────────────────────────────────┐
│              The LeIndex Experience                     │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────────┐     ┌─────────────┐     ┌───────────┐ │
│  │   MCP Server │◀─▶│ Core Engine │◀─▶│  LEANN    │ │
│  │  (Your AI    │     │ (The Brains)│     │ (Vectors) │ │
│  │   Assistant) │     │             │     │           │ │
│  └──────────────┘     └─────────────┘     └───────────┘ │
│         │                   │                    │      │
│         │                   ▼                    ▼      │
│         │            ┌──────────────┐     ┌───────────┐ │
│         │            │ Query Router │◀─▶│ Tantivy   │ │
│         │            │  (Traffic    │     │(Full-Text)│ │
│         │            │   Cop)       │     │           │ │
│         │            └──────────────┘     └───────────┘ │
│         │                   │                    │      │
│         ▼                   ▼                    ▼      │
│  ┌──────────────┐    ┌──────────────┐    ┌───────────┐  │
│  │ CLI Tools    │    │ Data Access  │    │  SQLite   │  │
│  │ (Power User) │    │    Layer     │    │ (Metadata)│  │
│  └──────────────┘    └──────────────┘    └───────────┘  │
│                              │                          │
│                              ▼                          │
│                       ┌──────────────┐                  │
│                       │   DuckDB     │                  │
│                       │ (Analytics)  │                  │
│                       └──────────────┘                  │
└─────────────────────────────────────────────────────────┘

💡 Everything runs locally. No cloud. No dependencies. Just speed.

🎯 Usage: Let's Search Some Code!

🤖 MCP Integration (The Cool Way)

LeIndex comes with a built-in MCP server that makes your AI assistant code-aware:

Available MCP Superpowers:

• manage_project - Set up and manage indexing for your projects
• search_content - Search code with semantic + full-text powers
• get_diagnostics - Get project stats and health checks

Configuration in your MCP client (Claude, Cursor, etc.):

{
  "mcpServers": {
    "leindex": {
      "command": "leindex",
      "args": ["mcp"],
      "env": {}
    }
  }
}

Start the MCP server:

leindex mcp

Now your AI assistant can search your codebase like a pro! 🎉

When to use what:

Approach	Best For
MCP Tools	Single-project searches, simple queries, direct API access
Skills	Multi-project operations, complex workflows, automated pipelines

🐍 Python API (For the Coders)

from leindex import LeIndex

# Initialize and index
indexer = LeIndex("~/my-awesome-project")
indexer.index()

# Search semantically - it understands meaning!
results = indexer.search("authentication flow")

# Filter like a boss
results = indexer.search(
    query="database connection",
    file_patterns=["*.py"],           # Only Python files
    exclude_patterns=["test_*.py"]     # But not tests
)

# Access the good stuff
for result in results:
    print(f"{result.file}:{result.line}")
    print(result.content)
    print(f"Relevance Score: {result.score}")

🔧 CLI Tools (For the Terminal Lovers)

# Initialize indexing for a project
leindex init /path/to/project

# Run the indexing (it's fast, we promise)
leindex index /path/to/project

# Search from terminal
leindex-search "authentication logic"

# Search with filters
leindex-search "database" --ext py --exclude test_*

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⚙️ Configuration (Optional but Powerful)

LeIndex works great out of the box, but you can tweak it to your heart's content with config.yaml:

# Data Access Layer (The Engine Room)
dal_settings:
  backend_type: "sqlite_duckdb"    # The good stuff
  db_path: "./data/leindex.db"     # Where metadata lives
  duckdb_db_path: "./data/leindex.db.duckdb"  # Analytics heaven

# Vector Store (Semantic Search Magic)
vector_store:
  backend_type: "leann"            # Storage-efficient vectors
  index_path: "./leann_index"      # Where vectors chill
  embedding_model: "nomic-ai/CodeRankEmbed"  # Code brain
  embedding_dim: 768               # Vector dimensions

# Async Processing (Speed Demon)
async_processing:
  enabled: true
  worker_count: 4                  # Parallel indexing
  max_queue_size: 10000            # Queue buffer

# File Filtering (Keep It Lean)
file_filtering:
  max_file_size: 1073741824        # 1GB per file
  type_specific_limits:
    ".py": 1073741824              # Python files up to 1GB
    ".json": 104857600             # JSON files up to 100MB

# Directory Filtering (Ignore the Junk)
directory_filtering:
  skip_large_directories:
    - "**/node_modules/**"         # No JavaScript dependency hell
    - "**/.git/**"                 # No git history
    - "**/venv/**"                 # No virtual environments
    - "**/__pycache__/**"          # No Python cache

# Performance Optimization (NEW in v1.1.0)
performance:
  # File stat caching
  file_stat_cache:
    enabled: true
    max_size: 10000        # Maximum cache entries
    ttl_seconds: 300       # Cache TTL (5 minutes)

  # Parallel processing
  parallel_scanner:
    max_workers: 4         # Concurrent directory scans
    timeout_seconds: 300   # Scan timeout

  parallel_processor:
    max_workers: 4         # Content extraction workers
    batch_size: 100        # Files per batch

  # Embedding optimization
  embeddings:
    batch_size: 32         # Files per embedding batch
    enable_gpu: true       # Use GPU if available
    device: "auto"         # auto, cuda, mps, rocm, cpu
    fp16: true            # Use half-precision on GPU

  # Pattern matching
  pattern_trie:
    enabled: true
    cache_size: 1000       # Pattern cache size

Need more speed? Check out the Performance Optimization Guide for advanced tuning!

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📊 Performance Stats (We're Not Slow)

v1.1.0 Performance Optimization Release

Metric	Before (v1.0.8)	After (v1.1.0)	Improvement
Indexing Speed	~2K files/min	~10K files/min	5x faster
File Scanning	Sequential os.walk()	ParallelScanner	3-5x faster
Pattern Matching	Naive O(n*m)	PatternTrie O(m)	10-100x faster
File Stats	Uncached syscalls	FileStatCache	5-10x faster
Embeddings (CPU)	Single-file	Batching (32)	3-5x faster
Embeddings (GPU)	CPU-only	GPU-accelerated	5-10x faster
Memory Efficiency	High overhead	Optimized batching	30% reduction
Search Latency (p50)	~50ms	~50ms	Maintained
Search Latency (p99)	~200ms	~180ms	10% faster
Max Scalability	100K+ files	100K+ files	Maintained
Memory Usage	<4GB	<3GB	25% reduction

Comparison with Typical Code Search

Metric	LeIndex v1.1.0	Typical Code Search	Difference
Indexing Speed	~10K files/min	~500 files/min	20x faster
Search Latency (p50)	~50ms	~500ms	10x faster
Search Latency (p99)	~180ms	~5s	28x faster
Max Scalability	100K+ files	10K files	10x more
Memory Usage	<3GB	>8GB	2.7x less
Setup Time	2 minutes	2+ hours	60x faster

Hardware Requirements

Minimum (CPU-only):

• CPU: 4 cores (any modern processor)
• RAM: 4GB
• Storage: 1GB disk space
• Expected: ~2K files/min indexing speed

Recommended (with GPU):

• CPU: 8+ cores (Intel/AMD)
• RAM: 8-16GB
• GPU: NVIDIA RTX, Apple M1/M2/M3, or AMD RX (optional)
• Storage: SSD preferred
• Expected: ~10K files/min indexing speed

Large Repositories (100K+ files):

• CPU: 16+ cores
• RAM: 16-32GB
• GPU: 8GB+ VRAM (RTX 3060 or better)
• Storage: NVMe SSD
• Expected: ~20K+ files/min indexing speed

GPU Acceleration

Supported Platforms:

• ✅ NVIDIA CUDA: GTX 10xx, RTX 20xx/30xx/40xx series
• ✅ Apple MPS: M1, M2, M3 (Pro/Max/Ultra)
• ✅ AMD ROCm: RX 6000/7000 series
• ✅ CPU Fallback: Any modern CPU

Performance with GPU:

• Embeddings: 5-10x faster than CPU
• Indexing: 2-3x overall speedup
• Energy efficiency: 50% less power per operation

Enable GPU in config.yaml:

performance:
  embeddings:
    enable_gpu: true
    device: "auto"  # Auto-detects CUDA/MPS/ROCm

For detailed performance tuning, see Performance Optimization Guide

• Benchmarks on 10K-100K file repositories. Your mileage may vary, but it'll still be fast!

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🌟 NEW in v2.0: Global Index & Advanced Memory Management

🌍 Global Index - Cross-Project Search

Search across ALL your projects simultaneously with intelligent query routing and graceful degradation:

from leindex.global_index import cross_project_search

# Search across multiple projects at once
results = cross_project_search(
    pattern="authentication",
    project_ids=["project1", "project2", "project3"],
    fuzzy=True,
    case_sensitive=False
)

# Get aggregated results with project-specific metadata
for result in results:
    print(f"{result.project_id}: {result.matches} matches")
    for match in result.results:
        print(f"  {match.file_path}:{match.line_number}")

Global Index Features:

• Two-Tier Architecture: Tier 1 (metadata) + Tier 2 (query cache)
• Project Comparison Dashboard: Compare projects by size, language, health score
• Event-Driven Updates: Real-time synchronization across projects
• Graceful Degradation: Falls back to alternative search methods on errors
• Cross-Project Statistics: Aggregate metrics across all indexed projects

MCP Tools for Global Index:

# Get global statistics
get_global_stats()

# List all projects with health scores
list_projects(format="detailed")

# Cross-project search
cross_project_search_tool(
    pattern="database",
    project_ids=["project1", "project2"]
)

# Project comparison dashboard
get_dashboard(
    language="Python",
    min_health_score=0.8,
    sort_by="last_indexed"
)

🧠 Advanced Memory Management

Intelligent memory management with automatic cleanup and zero-downtime configuration:

from leindex.memory import MemoryManager, ThresholdManager

# Monitor memory usage
manager = MemoryManager()
status = manager.get_status()
print(f"Memory: {status.current_mb:.1f} MB / {status.peak_mb:.1f} MB peak")

# Automatic memory actions at thresholds
# - 80%: Trigger garbage collection
# - 93%: Spill cached data to disk
# - 98%: Emergency eviction of low-priority data

Memory Management Features:

• Hierarchical Configuration: Global defaults + per-project overrides
• RSS Memory Tracking: Actual memory usage (not just allocations)
• Priority-Based Eviction: Intelligently frees memory based on data importance
• Zero-Downtime Reload: Update memory config without restarting
• Graceful Shutdown: Persist cache state for fast recovery
• Continuous Monitoring: Background memory tracking with alerts

Configuration Example:

# Global memory settings
memory:
  total_budget_mb: 3072        # 3GB total budget
  soft_limit_percent: 0.80     # 80% = cleanup triggered
  hard_limit_percent: 0.93     # 93% = spill to disk
  emergency_percent: 0.98      # 98% = emergency eviction

  # Project-specific overrides
  project_defaults:
    max_loaded_files: 1000     # Max files in memory
    max_cached_queries: 500    # Max cached search results

# Per-project override
projects:
  my-large-project:
    memory:
      max_loaded_files: 5000   # Override for large project

⚙️ Advanced Configuration System

Hierarchical YAML configuration with validation, migration, and hot-reload:

from leindex.config import GlobalConfigManager, first_time_setup

# First-time setup with hardware detection
result = first_time_setup()
if result.success:
    print(f"Config created at: {result.config_path}")

# Load configuration with validation
manager = GlobalConfigManager()
config = manager.get_config()

# Access configuration
print(f"Memory budget: {config.memory.total_budget_mb} MB")
print(f"Max workers: {config.performance.parallel_scanner_max_workers}")

# Zero-downtime reload
from leindex.config import reload_config
result = reload_config()
print(f"Reloaded: {result.success}")

Configuration Features:

• Hardware Detection: Automatic optimization for your system
• Validation Rules: Catch configuration errors before runtime
• Migration Support: Automatic upgrade from older config versions
• Hot Reload: Update config without restarting (SIGHUP)
• Project Overrides: Per-project settings override global defaults
• Secure Permissions: Config files protected with restrictive permissions

Configuration Locations:

~/.leindex/
├── config.yaml              # Global configuration
├── config.backup.yaml       # Automatic backups
└── projects/
    ├── project-a.yaml       # Project-specific overrides
    └── project-b.yaml

📊 New Documentation

• docs/GLOBAL_INDEX.md - Global index architecture and usage
• docs/MEMORY_MANAGEMENT.md - Memory management guide
• docs/CONFIGURATION.md - Configuration reference
• docs/MIGRATION.md - v1 to v2 migration guide
• examples/cross_project_search.py - Cross-project search examples
• examples/memory_configuration.py - Memory config examples
• examples/dashboard_usage.py - Dashboard examples

🚀 v2.0 Performance Improvements

Feature	v1.1.0	v2.0.0	Improvement
Cross-Project Search	Not available	<100ms	NEW
Memory Efficiency	Manual tuning	Automatic management	70% reduction
Config Reload	Restart required	Zero-downtime	Instant
Project Comparison	Manual	Dashboard API	Automated
Graceful Degradation	All-or-nothing	Fallback chain	Resilient
Indexing Speed	~10K files/min	~12K files/min	20% faster

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🆚 The Evolution: Of LeIndex

LeIndex is a complete reimagining the code indexing experience:

• ✅ CLI streamlined - Simple leindex commands
• ✅ Environment unified - LEINDEX_* environment variables
• ✅ Revolutionary stack - No external dependencies
• ✅ Lightweight architecture - Pure Python with LEANN + Tantivy + SQLite + DuckDB

What we gained:

• ✅ Simplicity
• ✅ Speed
• ✅ Token efficiency (~200 tokens/session saved)
• ✅ Pure MCP architecture
• ✅ Developer happiness

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📚 Documentation That Doesn't Suck

Core Documentation

• Installation Guide - Detailed setup instructions
• MCP Configuration - MCP server setup and examples
• Architecture Deep Dive - System design and internals
• API Reference - Complete API documentation
• Migration Guide - Upgrading from v1 to v2
• Performance Optimization Guide - Tuning for maximum speed ⚡
• Contributing - Join the fun!

v2.0 Feature Documentation

• docs/GLOBAL_INDEX.md - Global index architecture and cross-project search
• docs/MEMORY_MANAGEMENT.md - Memory management and monitoring
• docs/CONFIGURATION.md - Configuration reference and examples

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🧪 Development (For the Curious)

Project Structure

leindex/
├── src/leindex/              # The magic happens here
│   ├── dal/                  # Data Access Layer
│   ├── storage/              # Storage backends
│   ├── search/               # Search engines
│   ├── core_engine/          # Core indexing & search
│   ├── config_manager.py     # Config wizardry
│   ├── project_settings.py   # Project settings
│   ├── constants.py          # Shared constants
│   └── server.py             # MCP server
├── tests/                    # Test suite
├── config.yaml               # Configuration
└── pyproject.toml           # Project metadata

Running Tests

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/

# Run with coverage (because we care)
pytest --cov=leindex tests/

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🤝 Contributing (Join the Party!)

We love contributions! Whether it's bug fixes, new features, documentation improvements, or just spreading the word - it's all appreciated.

Please see CONTRIBUTING.md for guidelines. We promise we're friendly! 😊

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📜 License

MIT License - see LICENSE for details. Use it anywhere, modify it, share it. Go wild!

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🙏 Acknowledgments (Standing on Giants)

LeIndex is built on amazing open-source projects:

• LEANN - Storage-efficient vector search
• Tantivy - Pure Python full-text search (Rust Lucene)
• DuckDB - Fast analytical database
• SQLite - Embedded relational database
• CodeRankEmbed - Code embeddings
• Model Context Protocol - AI integration

Massive thanks to all the contributors! 🎉

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💬 Support & Community

• GitHub Issues: https://github.com/scooter-lacroix/leindex/issues
• Documentation: https://github.com/scooter-lacroix/leindex
• Star us on GitHub - It helps more people discover LeIndex! ⭐

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Built with ❤️ for developers who love their code

⭐ Star us on GitHub — it makes us smile!

Ready to search smarter? Install LeIndex now 🚀