pygent 0.3.4

Pygent is a minimalist coding assistant that runs commands in a Docker container when available and falls back to local execution.

Pygent

Pygent is a coding assistant that executes each request inside an isolated Docker container (meaning the container is discarded after use) whenever possible. If Docker is unavailable (for instance on some Windows setups) the commands are executed locally instead. Full documentation is available in the docs/ directory and at pygent-ai.com.

Features

• Runs commands in ephemeral containers (default image python:3.12-slim).
• Integrates with OpenAI-compatible models (models adhering to the OpenAI API specification) to orchestrate each step.
• Persists the conversation history during the session.
• Optionally save the history to a JSON file for later recovery.
• Persist the workspace across sessions by setting PYGENT_WORKSPACE.
• Provides a small Python API for use in other projects.
• Optional web interface via pygent ui (also available as pygent-ui).
• Optional FastAPI server to manage tasks over HTTP.
• Register your own tools and customise the system prompt.
• Extend the CLI with custom commands.
• Build custom interactive sessions by subclassing the Session API.
• Execute a config.py script on startup for advanced configuration.
• Set environment variables from the command line.
• Each session begins with a short plan that you can approve before execution.
• The assistant can leverage the bash tool to run shell commands in a sandboxed environment.

Installation

The recommended way to install Pygent is using pip:

pip install pygent

To include optional features like Docker support, the web UI, or the FastAPI server, you can specify extras:

pip install pygent[docker,ui,server]

Python ≥ 3.9 is required. The package now bundles the openai client for model access. To run commands in Docker containers, Docker must be installed separately.

If you are a developer or want the latest unreleased changes, you can install from source:

pip install -e .

Python ≥ 3.9 is required. The package now bundles the openai client for model access. To run commands in Docker containers, Docker must be installed separately. If installing from source, you can include Docker support with pip install -e .[docker,ui,server].

Configuration

Behaviour can be adjusted via environment variables (see docs/configuration.md for a complete list):

• OPENAI_API_KEY – key used to access the OpenAI API. Set this to your API key or a key from any compatible provider.
• OPENAI_BASE_URL – base URL for OpenAI-compatible APIs (defaults to https://api.openai.com/v1).
• PYGENT_MODEL – model name used for requests (default gpt-4.1-mini).
• PYGENT_IMAGE – Docker image to create the container (default python:3.12-slim).
• PYGENT_USE_DOCKER – set to 0 to disable Docker and run locally.
• PYGENT_MAX_TASKS – maximum number of concurrent delegated tasks (default 3).

Settings can also be read from a pygent.toml file. See examples/sample_config.toml and the accompanying config_file_example.py script for a working demonstration that generates tests using a delegated agent.

CLI usage

After installing run:

pygent

Use --docker to run commands inside a container (requires pygent[docker]). Use --no-docker or set PYGENT_USE_DOCKER=0 to force local execution. When the session starts the CLI shows the persona name and whether it is running locally or in Docker so you can easily tell which agent is active. Pass --confirm-bash if you want to approve each bash command before it runs. Use --ban-cmd CMD to disallow specific commands entirely (repeat to ban multiple). Pass --config path/to/pygent.toml to load settings from a file. Use --cwd to run inside the current directory instead of a temporary workspace.

Type messages normally; use /exit to end the session. Each command is executed in the container and the result shown in the terminal. Interactive programs that expect input (e.g. running python without a script) are not supported and will exit immediately. For a minimal web interface run pygent ui instead (requires pygent[ui]). To expose the API over HTTP run uvicorn pygent.fastapi_app:create_app (requires pygent[server]). Use /help for a list of built-in commands or /help <cmd> for details. Use /save DIR to snapshot the current environment for later use. Use /tools to enable or disable tools during the session. Use /banned to list or update banned commands. Use /confirm-bash on|off to toggle confirmation before running bash commands. Resume from a snapshot with pygent --load DIR or by setting PYGENT_SNAPSHOT=DIR. Additional commands can be registered programmatically with pygent.commands.register_command(). The CLI loads a config.py script if present (or passed with --pyconfig) and environment variables may be set directly with -e NAME=value.

API usage

You can also interact directly with the Python code:

from pygent import Agent

ag = Agent()
ag.step("echo 'Hello World'")
# ... more steps
ag.runtime.cleanup()

See the examples folder for more complete scripts. Models can be swapped by passing an object implementing the Model interface when creating the Agent. The default uses an OpenAI-compatible API, but custom models are easy to plug in. They can also trigger tools by returning a message with tool_calls as demonstrated in examples/custom_model_with_tool.py.

Custom models can also be configured globally:

from pygent.models import set_custom_model
set_custom_model(MyModel())

All new agents and delegated tasks will use this model unless another one is passed explicitly.

You can also override how the assistant builds the system prompt:

from pygent.agent import set_system_message_builder

def my_builder(persona, disabled_tools=None):
    return f"{persona.name}: ready to work"

set_system_message_builder(my_builder)

Passing None restores the default prompt generation.

Using OpenAI and other providers

Set your OpenAI key:

export OPENAI_API_KEY="sk-..."

To use a different provider, set OPENAI_BASE_URL to the provider endpoint and keep OPENAI_API_KEY pointing to the correct key:

export OPENAI_BASE_URL="https://openrouter.ai/api/v1"
export OPENAI_API_KEY="your-provider-key"

Development

1. Install the test dependencies:

pip install -e .[test]

2. Run the test suite:

pytest

Use mkdocs serve to build the documentation locally and serve it on a local webserver.

License

This project is released under the MIT license. See the LICENSE file for details.