⚙️ Schema Analysis

SLM Database Migrator

Analyzes legacy database schemas and generates zero-downtime, CPU-optimized migrations and modern ORM model definitions offline.

🚀 Overview & Capabilities

Analyzes legacy database schemas and generates zero-downtime, CPU-optimized migrations and modern ORM model definitions offline.

Key Features

Direct SQL table schema analysis and dependency mapping
Automatic compatibility matching for migrations
Generates modern SQLAlchemy and Django ORM models
Suggests structural indexing plans for performance improvement

💻 Installation

Install the local CPU-optimized package using pip:

Terminal

              # Install local CPU-optimized package
pip install slm-db-migration
            

🐙 Checkout from GitHub

Clone only this agent's folder from the monorepo using Git sparse-checkout — no need to download the full repository:

Option 1 — Sparse Checkout (Recommended)

Terminal — Git Sparse Checkout

              # 1. Create and enter a new directory
$ mkdir slm_db_migration && cd slm_db_migration

# 2. Initialise empty git repo and add remote
$ git init
$ git remote add origin https://github.com/t00114218-stack/SLMAgents.git

# 3. Enable sparse-checkout and set target folder
$ git sparse-checkout init --cone
$ git sparse-checkout set slm_db_migration

# 4. Pull only that agent's source
$ git pull origin main
            

Option 2 — Full Repository Clone

Terminal — Full Clone

              $ git clone https://github.com/t00114218-stack/SLMAgents.git
$ cd SLMAgents/slm_db_migration
            

💡 Tip: After checkout, install the package locally with pip install -e ./slm_db_migration to run in editable mode without publishing to PyPI.

⚙️ Configuration API

Constructor Parameters

Instantiate SLMDBMigrator with performance options:

Parameter	Type / Default	Description
model_path	str \| None	Explicit path to ONNX model weights. If omitted, downloads standard checkpoints.
cache_dir	str \| None	Directory to store model weights offline. Defaults to `~/.cache/slm-db-migration/`. Also settable via SLM_DATABASE_MIGRATOR_CACHE_DIR.
n_threads	int \| 4	CPU thread count for ONNX inference. Optimize for CPU core count. Also settable via SLM_DATABASE_MIGRATOR_N_THREADS.

Methods

Method Signature	Return Type	Description
`generate_migration(from_schema, to_schema, system_prompt=None, user_input=None)`	`str`	Compares two SQL schemas and outputs ALTER TABLE SQL migration commands.

Method Parameters (Execution Customization)

All main execution methods accept optional system routing parameters:

Parameter	Type / Default	Description
system_prompt	str \| None	Optional custom system prompt instruction to override the default system template response parameters.
user_input	str \| None	Optional additional user-supplied target text variables or contextual keys.

Quick Start

from slm_db_migration import SLMDBMigrator

migrator = SLMDBMigrator()
migration_sql = migrator.generate_migration(
    from_schema=from_schema,
    to_schema=to_schema,
    system_prompt="Strict zero-downtime rules",
    user_input="Postgres compatibility"
)
print(migration_sql)

Environment Variables

Configure agent parameters globally using environment values:

Environment Variable	Default	Purpose
SLM_DATABASE_MIGRATOR_N_THREADS	4	Sets CPU inference execution threads.
SLM_DATABASE_MIGRATOR_CACHE_DIR	~/.cache/slm-db-migration/	Default directory to store downloaded ONNX weights.

CPU Performance Tuning

To run the SLMDBMigrator engine efficiently on CPU under 1.5 GB memory footprint:

Match Threads to Core Count: Set n_threads or SLM_DATABASE_MIGRATOR_N_THREADS to match the physical CPU core count.
Sequential Processing: Avoid concurrent processing when batch files are large.
Garbage Collection: Clear variables and run gc.collect() to release model RAM blocks after execution.

Verified Input & Output Logs

Diagnostic execution console response running locally on CPU:

→ INPUT (To-Schema):
CREATE TABLE users (id INT PRIMARY KEY, name TEXT, email TEXT);

← OUTPUT:
{
  'migration_sql': 'ALTER TABLE users ADD COLUMN email TEXT;',
  'sandbox_result': 'Migration verified successfully in SQLite sandbox.'
}