analogai-foundation 0.1.252

AnalogAI Foundation - A foundation framework for AI agents

AnalogAI Foundation

A comprehensive Python package for building AI agent systems with advanced capabilities including emotional intelligence, inference mechanisms, and multi-database support.

Installation

Install the package in editable mode:

pip install -e .

Install with development dependencies:

pip install -e ".[dev]"

Project Structure

Foundation/
├── src/
│   └── analogai/
│       └── foundation/
│           ├── common/         # Shared utilities, logging, DTOs, enums
│           ├── core/           # Core domain value objects and observables
│           ├── extensions/     # Auth, authorization, conversation, queries, etc.
│           ├── infrastructure/ # Repositories, storage adapters, services
│           ├── modules/        # Domain modules (beliefs, notions, inference)
│           ├── setup/          # Factories and wiring helpers
│           └── tests/          # Functional and unit tests
├── pyproject.toml       # Unified package configuration
├── setup.py             # Setup helper
├── MANIFEST.in          # Package manifest
└── README.md

Modules

Common (src/analogai/foundation/common/)

• Design Patterns: Chain of responsibility, singleton, state machine
• Logging: Application logging utilities
• Utils: Serialization, modifiers, lemmatization helpers

Core (src/analogai/foundation/core/)

• Value Objects: Time, relation, modifiers, attributes
• Observables: Notion and statement observables

Extensions (src/analogai/foundation/extensions/)

• Authentication / Authorization: Token & auth services
• Conversation / Belief Query / Contradictions: Extension services and adapters

Infrastructure (src/analogai/foundation/infrastructure/)

• Repositories: In-memory, MongoDB, Neo4j
• Storage Adapters: Vector storage and query adapters
• Gateways: Database gateways and services

Modules (src/analogai/foundation/modules/)

• Belief / Notion / Agent / User: Domain services and entities
• Inference: Categorical & conditional deduction, contradictions

Requirements

• Python >= 3.12
• See pyproject.toml for complete dependency list

Development

Running Tests

The project uses Python's built-in unittest framework:

python -m unittest discover -s src -p "test_*.py"

Code Quality

Format code with black:

black src/

Lint with ruff:

ruff check src/

Type check with mypy:

mypy src/

Coverage

Run coverage report:

coverage run -m unittest discover -s src -p "test_*.py"
coverage report
coverage html

License

MIT