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Random Values 0.1.0 #86

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1 change: 1 addition & 0 deletions .github/CODEOWNERS
Validating CODEOWNERS rules …
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Expand Up @@ -6,3 +6,4 @@
/src/autogpt_plugins/bing_search @ForestLinSen
/src/autogpt_plugins/news_search @PalAditya
/src/autogpt_plugins/wikipedia_search @pierluigi-failla
/src/autogpt_plugins/random_values @sidewaysthought
1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -59,6 +59,7 @@ For interactionless use, set `ALLOWLISTED_PLUGINS=example-plugin1,example-plugin
| Bing Search | This search plugin integrates Bing search engines into Auto-GPT. | [autogpt_plugins/bing_search](https://github.com/Significant-Gravitas/Auto-GPT-Plugins/tree/master/src/autogpt_plugins/bing_search)
| News Search | This search plugin integrates News Articles searches, using the NewsAPI aggregator into Auto-GPT. | [autogpt_plugins/news_search](https://github.com/Significant-Gravitas/Auto-GPT-Plugins/tree/master/src/autogpt_plugins/news_search)
| Wikipedia Search | This allows AutoGPT to use Wikipedia directly. | [autogpt_plugins/wikipedia_search](https://github.com/Significant-Gravitas/Auto-GPT-Plugins/tree/master/src/autogpt_plugins/wikipedia_search)
| Random Values | Enable AutoGPT to generate various random numbers and strings. | [autogpt_plugins/random_values](https://github.com/Significant-Gravitas/Auto-GPT-Plugins/tree/master/src/autogpt_plugins/random_values)

Some third-party plugins have been created by contributors that are not included in this repository. For more information about these plugins, please visit their respective GitHub pages.

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1 change: 1 addition & 0 deletions requirements.txt
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Expand Up @@ -9,6 +9,7 @@ build
twine
tweepy==4.13.0
pandas
python-lorem
auto_gpt_plugin_template
newsapi-python
pytest
22 changes: 22 additions & 0 deletions src/autogpt_plugins/random_values/README.md
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# Random Values Plugin

The Random Values plugin will enable AutoGPT to generate various random assorted
things like numbers and strings.

## Key Features:
- make_uuids generates 1 or more UUIDs (128-bit label)
- generate_string generates 1 or more alphanumeric strings of at least 2
characters in length
- generate_password generates 1 or more passwords of 6 or more characters
using letters, numbers and punctuation
- generate_placeholder_text generates 1 or more sentences of lorem ipsum text
- random_number draws 1 or more random numbers between min and max

## Installation:
As part of the AutoGPT plugins package, follow the
[installation instructions](https://github.com/Significant-Gravitas/Auto-GPT-Plugins)
on the Auto-GPT-Plugins GitHub reporistory README page.

## AutoGPT Configuration

Set `ALLOWLISTED_PLUGINS=autogpt-random-values,example-plugin1,example-plugin2,etc` in your AutoGPT `.env` file.
240 changes: 240 additions & 0 deletions src/autogpt_plugins/random_values/__init__.py
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"""Wikipedia search integrations."""
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from typing import Any, Dict, List, Optional, Tuple, TypedDict, TypeVar

from auto_gpt_plugin_template import AutoGPTPluginTemplate
from .random_values import _random_number
from .random_values import _make_uuids
from .random_values import _generate_string
from .random_values import _generate_password
from .random_values import _generate_placeholder_text

PromptGenerator = TypeVar("PromptGenerator")


class Message(TypedDict):
role: str
content: str


class AutoGPTRandomValues(AutoGPTPluginTemplate):
"""
Wikipedia search integrations
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"""

def __init__(self):
super().__init__()
self._name = "autogpt-random-values"
self._version = "0.1.0"
self._description = "Enable Auto-GPT with the power of random values."

def can_handle_on_response(self) -> bool:
"""This method is called to check that the plugin can
handle the on_response method.
Returns:
bool: True if the plugin can handle the on_response method."""
return False

def on_response(self, response: str, *args, **kwargs) -> str:
"""This method is called when a response is received from the model."""
pass

def can_handle_post_prompt(self) -> bool:
"""This method is called to check that the plugin can
handle the post_prompt method.
Returns:
bool: True if the plugin can handle the post_prompt method."""
return True

def can_handle_on_planning(self) -> bool:
"""This method is called to check that the plugin can
handle the on_planning method.
Returns:
bool: True if the plugin can handle the on_planning method."""
return False

def on_planning(
self, prompt: PromptGenerator, messages: List[str]
) -> Optional[str]:
"""This method is called before the planning chat completeion is done.
Args:
prompt (PromptGenerator): The prompt generator.
messages (List[str]): The list of messages.
"""
pass

def can_handle_post_planning(self) -> bool:
"""This method is called to check that the plugin can
handle the post_planning method.
Returns:
bool: True if the plugin can handle the post_planning method."""
return False

def post_planning(self, response: str) -> str:
"""This method is called after the planning chat completeion is done.
Args:
response (str): The response.
Returns:
str: The resulting response.
"""
pass

def can_handle_pre_instruction(self) -> bool:
"""This method is called to check that the plugin can
handle the pre_instruction method.
Returns:
bool: True if the plugin can handle the pre_instruction method."""
return False

def pre_instruction(self, messages: List[str]) -> List[str]:
"""This method is called before the instruction chat is done.
Args:
messages (List[str]): The list of context messages.
Returns:
List[str]: The resulting list of messages.
"""
pass

def can_handle_on_instruction(self) -> bool:
"""This method is called to check that the plugin can
handle the on_instruction method.
Returns:
bool: True if the plugin can handle the on_instruction method."""
return False

def on_instruction(self, messages: List[str]) -> Optional[str]:
"""This method is called when the instruction chat is done.
Args:
messages (List[str]): The list of context messages.
Returns:
Optional[str]: The resulting message.
"""
pass

def can_handle_post_instruction(self) -> bool:
"""This method is called to check that the plugin can
handle the post_instruction method.
Returns:
bool: True if the plugin can handle the post_instruction method."""
return False

def post_instruction(self, response: str) -> str:
"""This method is called after the instruction chat is done.
Args:
response (str): The response.
Returns:
str: The resulting response.
"""
pass

def can_handle_pre_command(self) -> bool:
"""This method is called to check that the plugin can
handle the pre_command method.
Returns:
bool: True if the plugin can handle the pre_command method."""
return False

def pre_command(
self, command_name: str, arguments: Dict[str, Any]
) -> Tuple[str, Dict[str, Any]]:
"""This method is called before the command is executed.
Args:
command_name (str): The command name.
arguments (Dict[str, Any]): The arguments.
Returns:
Tuple[str, Dict[str, Any]]: The command name and the arguments.
"""
pass

def can_handle_post_command(self) -> bool:
"""This method is called to check that the plugin can
handle the post_command method.
Returns:
bool: True if the plugin can handle the post_command method."""
return False

def post_command(self, command_name: str, response: str) -> str:
"""This method is called after the command is executed.
Args:
command_name (str): The command name.
response (str): The response.
Returns:
str: The resulting response.
"""
pass

def can_handle_chat_completion(
self,
messages: list[Dict[Any, Any]],
model: str,
temperature: float,
max_tokens: int,
) -> bool:
"""This method is called to check that the plugin can
handle the chat_completion method.
Args:
messages (Dict[Any, Any]): The messages.
model (str): The model name.
temperature (float): The temperature.
max_tokens (int): The max tokens.
Returns:
bool: True if the plugin can handle the chat_completion method."""
return False

def handle_chat_completion(
self,
messages: list[Dict[Any, Any]],
model: str,
temperature: float,
max_tokens: int,
) -> str:
"""This method is called when the chat completion is done.
Args:
messages (Dict[Any, Any]): The messages.
model (str): The model name.
temperature (float): The temperature.
max_tokens (int): The max tokens.
Returns:
str: The resulting response.
"""
return None

def post_prompt(self, prompt: PromptGenerator) -> PromptGenerator:
"""This method is called just after the generate_prompt is called,
but actually before the prompt is generated.
Args:
prompt (PromptGenerator): The prompt generator.
Returns:
PromptGenerator: The prompt generator.
"""

prompt.add_command(
"random_number",
"Random Number",
{"min": "<integer>", "max": "<integer>", "count": "<integer>"},
_random_number
)
prompt.add_command(
"make_uuids",
"Make UUIDs",
{"count": "<integer>"},
_make_uuids
)
prompt.add_command(
"generate_string",
"Generate String",
{"length": "<integer>", "count": "<integer>"},
_generate_string
)
prompt.add_command(
"generate_password",
"Generate Password",
{"length": "<integer>", "count": "<integer>"},
_generate_password
)
prompt.add_command(
"generate_placeholder_text",
"Generate Placeholder Text",
{"count": "<integer>"},
_generate_placeholder_text
)
return prompt
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