autobots-devtools-shared-lib 0.1.6

Shared library functions to be used for all autobots projects

Motivation

The author team spent a lot time researching open source frameworks to convert "working" prompts into production ready application. So we embarked on the journey to help you in your ViberEnt (read vibrant)- Vibe Coder for Enterprise journey.

Introduction

Dynamic Agent (DynAgent) framework - the core of the Autobots DevTools Shared Library (ADSL) package - provides supporting capabilities for turning your agent AI automation workflows into enterprise grade apps that can run production workloads. You can convert a business process into an LLM assisted UI chatbot and/or unsupervised workflow in an order of hours, even lesser if you have your prompts handy. DynAgent handles the heavy lifting for you out of the box: multi LLM, chatbot, observabilit and more, while you to focus on your prompts, output schemas and converting business process into works.

Features

• DynAgent Framework: Framework for building dynamic AI agents
• Multi LLM Support: Swap LLMs like swapping batteries
• Chainlit UI Integration: Pre-built UI components for Chainlit applications
• OAUTH Integration: Chainlit UI can be
• LLM Tools: Reusable tools for language model integrations
• Batch Processing: Utilities for batch operations
• Observability: Logging and monitoring helpers
• Containerization: Docker images with bundled dependencies
• Prompt Versioning: Prompts as source model
• Prompt Evaluation: Enables tweaking prompts

Batteries Included

It also provides a suite of helpers that work seamlessly with the DynAgent framework

Helper

• File Server -
• Workspace Management -
• Context Management - with caching and durable storage
• Jenkins Integration -

Quickstart

Want to see DynAgent in action - head to Jarvis

Contributing

If you are interested in adding more features to DynAgent then follow the next section.

Prerequisites

• Python 3.12+
• Poetry (install with brew install poetry on macOS)

Workspace Setup

This library is part of a multi-repository workspace (ws-multi). Follow these steps to set up the workspace:

1. Clone the Workspace

# Clone or create the workspace directory
cd /Users/pralhad/work/src
git clone <pk-multi-workspace-url> ws-multi
cd ws-multi

2. Create Shared Virtual Environment

# From the workspace root
make setup

This creates a shared .venv at the workspace root that all repositories use.

3. Clone This Repository

# From workspace root
git clone https://github.com/Pratishthan/autobots-devtools-shared-lib.git
cd autobots-devtools-shared-lib

4. Install Dependencies

# Install with development dependencies
make install-dev

# Or install runtime dependencies only
make install

5. Install Pre-commit Hooks

make install-hooks

Development

Available Commands

Run these commands from the autobots-devtools-shared-lib/ directory:

# Testing
make test              # Run tests with coverage
make test-cov          # Run tests with HTML coverage report
make test-fast         # Run tests without coverage (faster)
make test-one TEST=tests/unit/test_example.py::test_function

# Code Quality
make format            # Format code with Ruff
make lint              # Lint with Ruff (auto-fix enabled)
make check-format      # Check formatting without modifying
make type-check        # Run Pyright type checker
make all-checks        # Run all checks (format, type, test)

# Dependencies
make install           # Install runtime dependencies
make install-dev       # Install with dev dependencies
make update-deps       # Update dependencies

# Other
make clean             # Remove cache files and build artifacts
make build             # Build package
make help              # Show all available commands

Workspace-Level Commands

From the workspace root (/Users/pralhad/work/src/pk-multi/):

make test           # Run tests across all repos
make lint           # Lint all repos
make format         # Format all repos
make type-check     # Type check all repos
make all-checks     # Run all checks across all repos

Project Structure

autobots-devtools-shared-lib/
├── src/
│   └── autobots_devtools_shared_lib/
│       ├── __init__.py
│       ├── py.typed              # PEP 561 type stub marker
│       ├── chainlit_ui/          # Chainlit UI components
│       ├── DynAgent/             # DynAgent framework
│       ├── llm_tools/            # LLM tool integrations
│       ├── observability/        # Observability helpers
│       └── batch_processing/     # Batch processing utilities
├── tests/
│   ├── unit/                     # Unit tests
│   ├── integration/              # Integration tests
│   └── e2e/                      # End-to-end tests
├── .github/workflows/            # GitHub Actions CI/CD
├── pyproject.toml                # Dependencies and tool config
├── poetry.toml                   # Poetry settings (uses workspace .venv)
├── Makefile                      # Development commands
├── CONTRIBUTING.md               # Contribution guidelines
└── PUBLISHING.md                 # PyPI publishing guide

Code Quality Standards

This project maintains high code quality standards:

• Type Safety: Type annotations required (Pyright basic mode)
• Testing: Comprehensive test coverage with pytest
• Formatting: Ruff formatter (line length: 100)
• Linting: Ruff linter with strict rules
• Pre-commit Hooks: Automated checks on every commit

Testing

# Run all tests
make test

# Run specific test file
make test-one TEST=tests/unit/test_example.py

# Run with coverage report
make test-cov

Tests are organized into:

• Unit tests (tests/unit/): Test individual functions and classes
• Integration tests (tests/integration/): Test component interactions
• E2E tests (tests/e2e/): Test complete workflows

Type Checking

# Run Pyright type checker
make type-check

All code should have type annotations. The project uses Pyright in basic mode.

Contributing

See CONTRIBUTING.md for development guidelines and workflow.

Publishing

See PUBLISHING.md for instructions on publishing to PyPI.

License

MIT

Authors

• Pra1had
  • Email: [e-mail]
  • Github:pra1had

Questions?

If you have questions or need help, please open an issue on the project repository.