scaliseraoul/ambrogio

First prototype of Ambrogio (2025), built before the company was accelerated by Antler: a dev agent for tech debt (unit tests, docstrings). The commercial product lives at ambrogio.tech. Ambrogio officially closed in June 2026. Archived.

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Ambrogio - tech debt agent

Ambrogio is an intelligent dev agent that helps tackle technical debt in your codebase. Starting with docstring improvements, it systematically enhances code quality and maintainability through automated analysis and improvements.

๐ŸŽฏ Mission

Our mission is to help development teams maintain high-quality codebases by automatically identifying and addressing technical debt, starting with comprehensive and accurate docstrings. Ambrogio uses advanced language models to understand your code and generate meaningful documentation.

โœจ Features

Current Features

  • โœ… Smart Docstring Generation: Automatically adds clear, comprehensive docstrings to classes and methods
  • โœ… Multi-Provider Support: Works with various LLM providers through LiteLLM integration
  • โœ… Unit Test Generation (Beta): Analyzes code coverage and generates missing unit tests

๐Ÿš€ Upcoming Features

  • Pre-PR test runs to prevent regressions
  • Improve existing docstrings in modified methods
  • Documentation generation for easier understanding
  • Type safety refactoring
  • Spaghetti code cleanup
  • Code formatting and best practices enforcement

๐Ÿ“ฆ Installation

pip install ambrogio

๐Ÿš€ Usage

Basic Usage

# Run docstring generation with default settings (uses OPENAI_API_KEY from environment)
ambrogio

# Run with custom configuration
ambrogio \
  --path /path/to/your/project \
  --api-key your-api-key \
  --model gpt-4 \
  --max-api-calls 20

# Run unit test generation (Beta)
ambrogio \
  --mode coverage \
  --max-iterations 5

โš ๏ธ Note: The unit test generation feature is currently in beta. It must be run within your virtual environment. You need pytest installed.

Advanced Usage

# Use Azure OpenAI
ambrogio \
  --api-key your-azure-key \
  --api-base https://your-azure-deployment.openai.azure.com \
  --model gpt-4

# Use Anthropic's Claude
ambrogio \
  --api-key your-anthropic-key \
  --model claude-2

Available Options

Common Options:
--path           Path to the Python project (default: current directory)
--api-key        API key for your LLM provider (default: OPENAI_API_KEY from env)
--model          Model to use (default: gpt-4o-mini)
--api-base       Base URL for API endpoint (required for Azure, optional for others)
--mode           Mode to run in ('docstring' or 'coverage'). Default: docstring

Docstring Mode Options:
--max-api-calls  Maximum number of API calls per run (default: 12)

Coverage Mode Options:
--max-iterations Maximum number of test generation attempts per file (default: 3)

Environment Variables

  • OPENAI_API_KEY: Default API key if not provided via command line

๐Ÿ”ง Supported LLM Providers

Ambrogio uses LiteLLM for multi-provider support. You can use any of these providers:

  • OpenAI (GPT-3.5, GPT-4)
  • Azure OpenAI
  • Anthropic (Claude)
  • And many more! Check LiteLLM's documentation for the full list

๐Ÿค Contributing

Contributions are welcome! Feel free to:

  • Report bugs
  • Suggest new features
  • Submit pull requests

๐Ÿ“ License

This project is licensed under the GPL-3.0 License - see the LICENSE file for details.

Maintainers

Contributors

scaliseraouldeepsource-autofix[bot]deepsource-io[bot]

Issues