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l0l1

SQL that learns. AI that validates. Privacy that protects.

l0l1 is a developer toolkit for SQL analysis that combines AI-powered validation with continuous learning. It detects PII, suggests improvements, and gets smarter from your successful queries.

Features

Quick Start

Installation

# Clone and install with uv (recommended)
git clone https://github.com/skelf-research/l0l1-api.git
cd l0l1-api
uv sync

# Configure
export OPENAI_API_KEY="sk-..."

CLI Usage

# Validate a SQL query
l0l1 validate "SELECT * FROM users WHERE id = 1"

# Explain a query
l0l1 explain "SELECT u.name, COUNT(o.id) FROM users u JOIN orders o ON u.id = o.user_id GROUP BY u.name"

# Check for PII
l0l1 check-pii "SELECT * FROM users WHERE email = 'john@example.com'"

API Server

# Start the API server
uv run l0l1-serve

# Or use uvicorn directly with hot reload
uv run uvicorn l0l1.api.main:app --reload

The API is available at http://localhost:8000 with interactive docs at /docs.

Python SDK

from l0l1.models.factory import ModelFactory
from l0l1.services.pii_detector import PIIDetector

# Initialize
model = ModelFactory.get_default_model()
pii_detector = PIIDetector()

# Validate
result = await model.validate_sql_query(
    "SELECT * FROM users WHERE id = 1",
    schema_context="users(id, name, email)"
)

# Check PII
pii_findings = pii_detector.detect_pii("SELECT * FROM users WHERE email = 'john@example.com'")

Architecture

l0l1/
├── api/           # FastAPI REST API
├── cli/           # Typer CLI
├── core/          # Configuration
├── models/        # AI providers (OpenAI, Anthropic)
├── services/      # Core services
│   ├── pii_detector.py      # PII detection (Presidio)
│   ├── learning_service.py  # Pattern learning
│   ├── database_service.py  # DB connections
│   └── schema_service.py    # Schema management
└── integrations/
    ├── jupyter/   # Notebook integration
    └── ide/       # LSP server

Next Steps

License

l0l1 is released under the MIT License.

Built by Skelf Research