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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>
96 lines
3.4 KiB
Python
96 lines
3.4 KiB
Python
from __future__ import annotations
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import os
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from typing import TYPE_CHECKING, Union
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import yaml
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if TYPE_CHECKING:
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from autogpt.config import Config
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from pydantic import BaseModel
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from autogpt.logs import logger
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from autogpt.plugins.plugin_config import PluginConfig
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class PluginsConfig(BaseModel):
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"""Class for holding configuration of all plugins"""
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plugins: dict[str, PluginConfig]
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def __repr__(self):
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return f"PluginsConfig({self.plugins})"
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def get(self, name: str) -> Union[PluginConfig, None]:
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return self.plugins.get(name)
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def is_enabled(self, name) -> bool:
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plugin_config = self.plugins.get(name)
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return plugin_config is not None and plugin_config.enabled
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@classmethod
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def load_config(cls, global_config: Config) -> "PluginsConfig":
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empty_config = cls(plugins={})
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try:
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config_data = cls.deserialize_config_file(global_config=global_config)
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if type(config_data) != dict:
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logger.error(
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f"Expected plugins config to be a dict, got {type(config_data)}, continuing without plugins"
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)
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return empty_config
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return cls(plugins=config_data)
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except BaseException as e:
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logger.error(
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f"Plugin config is invalid, continuing without plugins. Error: {e}"
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)
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return empty_config
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@classmethod
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def deserialize_config_file(cls, global_config: Config) -> dict[str, PluginConfig]:
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plugins_config_path = global_config.plugins_config_file
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if not os.path.exists(plugins_config_path):
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logger.warn("plugins_config.yaml does not exist, creating base config.")
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cls.create_empty_plugins_config(global_config=global_config)
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with open(plugins_config_path, "r") as f:
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plugins_config = yaml.load(f, Loader=yaml.FullLoader)
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plugins = {}
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for name, plugin in plugins_config.items():
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if type(plugin) == dict:
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plugins[name] = PluginConfig(
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name=name,
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enabled=plugin.get("enabled", False),
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config=plugin.get("config", {}),
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)
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elif type(plugin) == PluginConfig:
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plugins[name] = plugin
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else:
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raise ValueError(f"Invalid plugin config data type: {type(plugin)}")
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return plugins
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@staticmethod
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def create_empty_plugins_config(global_config: Config):
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"""Create an empty plugins_config.yaml file. Fill it with values from old env variables."""
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base_config = {}
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logger.debug(f"Legacy plugin denylist: {global_config.plugins_denylist}")
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logger.debug(f"Legacy plugin allowlist: {global_config.plugins_allowlist}")
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# Backwards-compatibility shim
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for plugin_name in global_config.plugins_denylist:
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base_config[plugin_name] = {"enabled": False, "config": {}}
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for plugin_name in global_config.plugins_allowlist:
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base_config[plugin_name] = {"enabled": True, "config": {}}
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logger.debug(f"Constructed base plugins config: {base_config}")
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logger.debug(f"Creating plugin config file {global_config.plugins_config_file}")
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with open(global_config.plugins_config_file, "w+") as f:
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f.write(yaml.dump(base_config))
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return base_config
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