Distributed toolsets for pantheon-agents, provide service via magique message transfer server.
Project description
Work in progress
Toolsets
- Python Interpreter
- R Interpreter
- Web toolset ()
- Web fetch with link resolution
- Web search using DDGS (DuckDuckGo)
- Web browse (legacy)
- Duckduckgo search
- Crawl4ai
- Code search ()
- File pattern search (glob)
- Content search (grep)
- Directory listing (ls)
- Notebook toolset (Jupyter)
- Read, edit, create notebooks
- Cell management (add, delete, move)
- Professional templates
- ScraperAPI
- Google search
- Web crawl
- Shell
- Convert toolset to MCP(Model Context Protocol)
- File editor/Filesystem access ()
- File transfer
- RAG system
- Todo/Task management (Claude Code style)
- Code search (glob, grep, ls)
- Jupyter notebook editing
- LaTeX compiler
- Browser-use
Installation
git clone https://github.com/aristoteleo/magique-ai.git
cd magique-ai
pip install -e ".[dev]"
Additional Dependencies
For enhanced web functionality:
pip install ddgs # For reliable web search
pip install beautifulsoup4 # For better HTML parsing
For notebook functionality:
pip install nbformat # For Jupyter notebook handling
All toolsets use Rich for beautiful console output, which is included in the base installation.
Usage
Built-in toolsets:
| Toolset | Package path | Description |
|---|---|---|
| Python Interpreter | pantheon.toolsets.python |
Run Python code in an interpreter. |
| R Interpreter | pantheon.toolsets.r |
Run R code in an interpreter. |
| Shell | pantheon.toolsets.shell |
Run shell commands. |
| Web Toolset | pantheon.toolsets.web |
** web fetch and search with DDGS.** |
| Code Search | pantheon.toolsets.code_search |
** file search with glob, grep, ls.** |
| Notebook Toolset | pantheon.toolsets.notebook |
Edit and manage Jupyter notebooks (no execution). |
| File Editor | pantheon.toolsets.file_editor |
** file editing with diffs.** |
| File Manager | pantheon.toolsets.file_manager |
General filesystem access and management. |
| Web Browse (legacy) | pantheon.toolsets.web_browse |
Legacy web search using DuckDuckGo and Crawl4ai. |
| ScraperAPI | pantheon.toolsets.scraper |
Use ScraperAPI to perform google search and web crawl. |
| Vector RAG | pantheon.toolsets.vector_rag |
Query a vector based RAG database. |
| File Transfer | pantheon.toolsets.file_transfer |
Transfer files between different systems. |
| Todo Management | pantheon.toolsets.todo |
Claude Code-style task management with status tracking. |
| Endpoint Hub | pantheon.toolsets.endpoint |
Manage and coordinate multiple toolset endpoints. |
Toolsets
The following toolsets provide Claude Code-like functionality for enhanced developer experience:
Web Toolset (pantheon.toolsets.web)
- web_fetch: Fetch web content with intelligent link resolution and markdown conversion
- web_search: Search using DDGS (DuckDuckGo Search) library - reliable and fast
Code Search Toolset (pantheon.toolsets.code_search)
- glob: Find files by patterns (e.g.,
*.py,**/*.ts) - grep: Search content across files with regex support
- ls: List directory contents with detailed information
Notebook Toolset (pantheon.toolsets.notebook)
- read_notebook: Display notebook contents with beautiful formatting
- edit_notebook_cell: Edit specific cells (code/markdown)
- add_notebook_cell: Add new cells at specific positions
- create_notebook: Create new notebooks with professional templates
File Editor Toolset (pantheon.toolsets.file_editor)
- read_file: Read files with line numbers
- edit_file: Edit files with diff display
- write_file: Create new files
Todo Management Toolset (pantheon.toolsets.todo)
- add_todo: Add new todo items with status tracking
- show_todos: Display todos in Claude Code style with checkboxes
- update_todo_status: Change status (pending ☐, in_progress ◐, completed ☑)
- complete_todo: Mark todos as completed
- start_todo: Mark todos as in progress
- remove_todo: Delete todos
- clear_completed_todos: Remove all completed tasks
Start a toolset, for example, the python interpreter from the command line:
python -m pantheon.toolsets.python
Example usage of new toolsets:
# Start web toolset for web fetch and search
python -m pantheon.toolsets.web
# Start code search toolset for file operations
python -m pantheon.toolsets.code_search
# Start notebook toolset for Jupyter editing
python -m pantheon.toolsets.notebook
See help with:
python -m pantheon.toolsets.python -- --help
NAME
__main__.py
SYNOPSIS
__main__.py <flags>
FLAGS
-s, --service_name=SERVICE_NAME
Type: str
Default: 'python-interpreter'
--mcp=MCP
Type: bool
Default: False
--mcp_kwargs=MCP_KWARGS
Type: dict
Default: {}
-t, --toolset_kwargs=TOOLSET_KWARGS
Type: dict
Default: {}
Development
Project structure:
- Built-in Toolsets
Test the package
Please start a magique message transfer server first.
python -m magique.server
Then export the server url and run the test:
export MAGIQUE_SERVER_URL=ws://localhost:8765/ws
pytest -s tests/
Environment configration
Firstly, you need docker and buildx installed. See docker docs and buildx docs for installation.
Magique-ai's built-in environments are stored in the environments folder.
And all environments could be managed by the environment/build_images.py script:
$ python environment/build_images.py -h
usage: build_images.py [-h] [-a] [-l] [-b TARGET] [--registry REGISTRY_PATH] [--push]
Docker image build automation
options:
-h, --help show this help message and exit
-a, --all Build all detected images
-l, --list List available Docker configurations
-b TARGET, --build TARGET
Build specific image by target name
--registry REGISTRY_PATH
Specify Docker registry path (e.g., ghcr.io/username)
--push Push the image(s) to the specified registry after building
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