Files
Auto-GPT/autogpt/core/plugin/simple.py
James Collins b9f01330db Re-arch WIP (#3969)
Rough sketching out of a hello world using our refactored autogpt
library. See the tracking issue here: #4770.

# Run instructions

There are two client applications for Auto-GPT included. 

## CLI Application

🌟 **This is the reference application I'm working with for now**
🌟

The first app is a straight CLI application. I have not done anything
yet to port all the friendly display stuff from the
`logger.typewriter_log` logic.

- [Entry
Point](https://github.com/Significant-Gravitas/Auto-GPT/blob/re-arch/hello-world/autogpt/core/runner/cli_app/cli.py)
- [Client
Application](https://github.com/Significant-Gravitas/Auto-GPT/blob/re-arch/hello-world/autogpt/core/runner/cli_app/main.py)

To run, you first need a settings file.  Run

```
 python REPOSITORY_ROOT/autogpt/core/runner/cli_app/cli.py make-settings
 ```

where `REPOSITORY_ROOT` is the root of the Auto-GPT repository on your machine.  This will write a file called `default_agent_settings.yaml` with all the user-modifiable configuration keys to `~/auto-gpt/default_agent_settings.yml` and make the `auto-gpt` directory in your user directory if it doesn't exist).  At a bare minimum, you'll need to set `openai.credentials.api_key` to your OpenAI API Key to run the model.

You can then run Auto-GPT with 

```
python REPOSITORY_ROOT/autogpt/core/runner/cli_app/cli.py make-settings
```

to launch the interaction loop.

## CLI Web App

The second app is still a CLI, but it sets up a local webserver that the client application talks to rather than invoking calls to the Agent library code directly.  This application is essentially a sketch at this point as the folks who were driving it have had less time (and likely not enough clarity) to proceed.

- [Entry Point](https://github.com/Significant-Gravitas/Auto-GPT/blob/re-arch/hello-world/autogpt/core/runner/cli_web_app/cli.py)
- [Client Application](https://github.com/Significant-Gravitas/Auto-GPT/blob/re-arch/hello-world/autogpt/core/runner/cli_web_app/client/client.py)
- [Server API](https://github.com/Significant-Gravitas/Auto-GPT/blob/re-arch/hello-world/autogpt/core/runner/cli_web_app/server/api.py)

To run, you still need to generate a default configuration.  You can do 

```
python REPOSITORY_ROOT/autogpt/core/runner/cli_web_app/cli.py
make-settings
```

It invokes the same command as the bare CLI app, so follow the instructions above about setting your API key.

To run, do 

```
python REPOSITORY_ROOT/autogpt/core/runner/cli_web_app/cli.py client
```

This will launch a webserver and then start the client cli application to communicate with it.

⚠️ I am not actively developing this application.  It is a very good place to get involved if you have web application design experience and are looking to get involved in the re-arch.

---------

Co-authored-by: David Wurtz <davidjwurtz@gmail.com>
Co-authored-by: Media <12145726+rihp@users.noreply.github.com>
Co-authored-by: Richard Beales <rich@richbeales.net>
Co-authored-by: Daryl Rodrigo <darylrodrigo@gmail.com>
Co-authored-by: Daryl Rodrigo <daryl@orkestro.com>
Co-authored-by: Swifty <craigswift13@gmail.com>
Co-authored-by: Nicholas Tindle <nick@ntindle.com>
Co-authored-by: Merwane Hamadi <merwanehamadi@gmail.com>
2023-07-05 12:12:05 -07:00

75 lines
3.0 KiB
Python

from importlib import import_module
from typing import TYPE_CHECKING
from autogpt.core.plugin.base import (
PluginLocation,
PluginService,
PluginStorageFormat,
PluginStorageRoute,
)
if TYPE_CHECKING:
from autogpt.core.plugin.base import PluginType
class SimplePluginService(PluginService):
@staticmethod
def get_plugin(plugin_location: dict | PluginLocation) -> "PluginType":
"""Get a plugin from a plugin location."""
if isinstance(plugin_location, dict):
plugin_location = PluginLocation.parse_obj(plugin_location)
if plugin_location.storage_format == PluginStorageFormat.WORKSPACE:
return SimplePluginService.load_from_workspace(
plugin_location.storage_route
)
elif plugin_location.storage_format == PluginStorageFormat.INSTALLED_PACKAGE:
return SimplePluginService.load_from_installed_package(
plugin_location.storage_route
)
else:
raise NotImplementedError(
f"Plugin storage format {plugin_location.storage_format} is not implemented."
)
####################################
# Low-level storage format loaders #
####################################
@staticmethod
def load_from_file_path(plugin_route: PluginStorageRoute) -> "PluginType":
"""Load a plugin from a file path."""
# TODO: Define an on disk storage format and implement this.
# Can pull from existing zip file loading implementation
raise NotImplemented("Loading from file path is not implemented.")
@staticmethod
def load_from_import_path(plugin_route: PluginStorageRoute) -> "PluginType":
"""Load a plugin from an import path."""
module_path, _, class_name = plugin_route.rpartition(".")
return getattr(import_module(module_path), class_name)
@staticmethod
def resolve_name_to_path(
plugin_route: PluginStorageRoute, path_type: str
) -> PluginStorageRoute:
"""Resolve a plugin name to a plugin path."""
# TODO: Implement a discovery system for finding plugins by name from known
# storage locations. E.g. if we know that path_type is a file path, we can
# search the workspace for it. If it's an import path, we can check the core
# system and the auto_gpt_plugins package.
raise NotImplemented("Resolving plugin name to path is not implemented.")
#####################################
# High-level storage format loaders #
#####################################
@staticmethod
def load_from_workspace(plugin_route: PluginStorageRoute) -> "PluginType":
"""Load a plugin from the workspace."""
plugin = SimplePluginService.load_from_file_path(plugin_route)
return plugin
@staticmethod
def load_from_installed_package(plugin_route: PluginStorageRoute) -> "PluginType":
plugin = SimplePluginService.load_from_import_path(plugin_route)
return plugin