Files
Auto-GPT/autogpt/setup.py
Reinier van der Leer db95d4cb84 Agent loop v2: Planning & Task Management (part 1: refactoring) (#4799)
* Move rename module `agent` -> `agents`

* WIP: abstract agent structure into base class and port Agent

* Move command arg path sanitization to decorator

* Add fallback token limit in llm.utils.create_chat_completion

* Rebase `MessageHistory` class on `ChatSequence` class

* Fix linting

* Consolidate logging modules

* Wham Bam Boom

* Fix tests & linting complaints

* Update Agent class docstring

* Fix Agent import in autogpt.llm.providers.openai

* Fix agent kwarg in test_execute_code.py

* Fix benchmarks.py

* Clean up lingering Agent(ai_name=...) initializations

* Fix agent kwarg

* Make sanitize_path_arg decorator more robust

* Fix linting

* Fix command enabling lambda's

* Use relative paths in file ops logger

* Fix test_execute_python_file_not_found

* Fix Config model validation breaking on .plugins

* Define validator for Config.plugins

* Fix Config model issues

* Fix agent iteration budget in testing

* Fix declaration of context_while_think

* Fix Agent.parse_and_process_response signature

* Fix Agent cycle_budget usages

* Fix budget checking in BaseAgent.__next__

* Fix cycle budget initialization

* Fix function calling in BaseAgent.think()

* Include functions in token length calculation

* Fix Config errors

* Add debug thing to patched_api_requestor to investigate HTTP 400 errors

* If this works I'm gonna be sad

* Fix BaseAgent cycle budget logic and document attributes

* Document attributes on `Agent`

* Fix import issues between Agent and MessageHistory

* Improve typing

* Extract application code from the agent (#4982)

* Extract application code from the agent

* Wrap interaction loop in a function and call in benchmarks

* Forgot the important function call

* Add docstrings and inline comments to run loop

* Update typing and docstrings in agent

* Docstring formatting

* Separate prompt construction from on_before_think

* Use `self.default_cycle_instruction` in `Agent.think()`

* Fix formatting

* hot fix the SIGINT handler (#4997)

The signal handler in the autogpt/main.py doesn't work properly because
of the clean_input(...) func. This commit remedies this issue. The issue
is mentioned in
3966cdfd69 (r1264278776)

* Update the sigint handler to be smart enough to actually work (#4999)

* Update the sigint handler to be smart enough to actually work

* Update autogpt/main.py

Co-authored-by: Reinier van der Leer <github@pwuts.nl>

* Can still use context manager

* Merge in upstream

---------

Co-authored-by: Reinier van der Leer <github@pwuts.nl>

* Fix CI

* Fix initial prompt construction

* off by one error

* allow exit/EXIT to shut down app

* Remove dead code

---------

Co-authored-by: collijk <collijk@uw.edu>
Co-authored-by: Cyrus <39694513+cyrus-hawk@users.noreply.github.com>
2023-07-20 17:34:49 +02:00

239 lines
7.7 KiB
Python

"""Set up the AI and its goals"""
import re
from typing import Optional
from colorama import Fore, Style
from jinja2 import Template
from autogpt import utils
from autogpt.config import Config
from autogpt.config.ai_config import AIConfig
from autogpt.llm.base import ChatSequence, Message
from autogpt.llm.utils import create_chat_completion
from autogpt.logs import logger
from autogpt.prompts.default_prompts import (
DEFAULT_SYSTEM_PROMPT_AICONFIG_AUTOMATIC,
DEFAULT_TASK_PROMPT_AICONFIG_AUTOMATIC,
DEFAULT_USER_DESIRE_PROMPT,
)
def prompt_user(
config: Config, ai_config_template: Optional[AIConfig] = None
) -> AIConfig:
"""Prompt the user for input
Params:
config (Config): The Config object
ai_config_template (AIConfig): The AIConfig object to use as a template
Returns:
AIConfig: The AIConfig object tailored to the user's input
"""
# Construct the prompt
logger.typewriter_log(
"Welcome to Auto-GPT! ",
Fore.GREEN,
"run with '--help' for more information.",
speak_text=True,
)
ai_config_template_provided = ai_config_template is not None and any(
[
ai_config_template.ai_goals,
ai_config_template.ai_name,
ai_config_template.ai_role,
]
)
user_desire = ""
if not ai_config_template_provided:
# Get user desire if command line overrides have not been passed in
logger.typewriter_log(
"Create an AI-Assistant:",
Fore.GREEN,
"input '--manual' to enter manual mode.",
speak_text=True,
)
user_desire = utils.clean_input(
config, f"{Fore.LIGHTBLUE_EX}I want Auto-GPT to{Style.RESET_ALL}: "
)
if user_desire.strip() == "":
user_desire = DEFAULT_USER_DESIRE_PROMPT # Default prompt
# If user desire contains "--manual" or we have overridden any of the AI configuration
if "--manual" in user_desire or ai_config_template_provided:
logger.typewriter_log(
"Manual Mode Selected",
Fore.GREEN,
speak_text=True,
)
return generate_aiconfig_manual(config, ai_config_template)
else:
try:
return generate_aiconfig_automatic(user_desire, config)
except Exception as e:
logger.typewriter_log(
"Unable to automatically generate AI Config based on user desire.",
Fore.RED,
"Falling back to manual mode.",
speak_text=True,
)
return generate_aiconfig_manual(config)
def generate_aiconfig_manual(
config: Config, ai_config_template: Optional[AIConfig] = None
) -> AIConfig:
"""
Interactively create an AI configuration by prompting the user to provide the name, role, and goals of the AI.
This function guides the user through a series of prompts to collect the necessary information to create
an AIConfig object. The user will be asked to provide a name and role for the AI, as well as up to five
goals. If the user does not provide a value for any of the fields, default values will be used.
Params:
config (Config): The Config object
ai_config_template (AIConfig): The AIConfig object to use as a template
Returns:
AIConfig: An AIConfig object containing the user-defined or default AI name, role, and goals.
"""
# Manual Setup Intro
logger.typewriter_log(
"Create an AI-Assistant:",
Fore.GREEN,
"Enter the name of your AI and its role below. Entering nothing will load"
" defaults.",
speak_text=True,
)
if ai_config_template and ai_config_template.ai_name:
ai_name = ai_config_template.ai_name
else:
ai_name = ""
# Get AI Name from User
logger.typewriter_log(
"Name your AI: ", Fore.GREEN, "For example, 'Entrepreneur-GPT'"
)
ai_name = utils.clean_input(config, "AI Name: ")
if ai_name == "":
ai_name = "Entrepreneur-GPT"
logger.typewriter_log(
f"{ai_name} here!", Fore.LIGHTBLUE_EX, "I am at your service.", speak_text=True
)
if ai_config_template and ai_config_template.ai_role:
ai_role = ai_config_template.ai_role
else:
# Get AI Role from User
logger.typewriter_log(
"Describe your AI's role: ",
Fore.GREEN,
"For example, 'an AI designed to autonomously develop and run businesses with"
" the sole goal of increasing your net worth.'",
)
ai_role = utils.clean_input(config, f"{ai_name} is: ")
if ai_role == "":
ai_role = "an AI designed to autonomously develop and run businesses with the"
" sole goal of increasing your net worth."
if ai_config_template and ai_config_template.ai_goals:
ai_goals = ai_config_template.ai_goals
else:
# Enter up to 5 goals for the AI
logger.typewriter_log(
"Enter up to 5 goals for your AI: ",
Fore.GREEN,
"For example: \nIncrease net worth, Grow Twitter Account, Develop and manage"
" multiple businesses autonomously'",
)
logger.info("Enter nothing to load defaults, enter nothing when finished.")
ai_goals = []
for i in range(5):
ai_goal = utils.clean_input(
config, f"{Fore.LIGHTBLUE_EX}Goal{Style.RESET_ALL} {i+1}: "
)
if ai_goal == "":
break
ai_goals.append(ai_goal)
if not ai_goals:
ai_goals = [
"Increase net worth",
"Grow Twitter Account",
"Develop and manage multiple businesses autonomously",
]
# Get API Budget from User
logger.typewriter_log(
"Enter your budget for API calls: ",
Fore.GREEN,
"For example: $1.50",
)
logger.info("Enter nothing to let the AI run without monetary limit")
api_budget_input = utils.clean_input(
config, f"{Fore.LIGHTBLUE_EX}Budget{Style.RESET_ALL}: $"
)
if api_budget_input == "":
api_budget = 0.0
else:
try:
api_budget = float(api_budget_input.replace("$", ""))
except ValueError:
logger.typewriter_log(
"Invalid budget input. Setting budget to unlimited.", Fore.RED
)
api_budget = 0.0
return AIConfig(ai_name, ai_role, ai_goals, api_budget)
def generate_aiconfig_automatic(user_prompt: str, config: Config) -> AIConfig:
"""Generates an AIConfig object from the given string.
Returns:
AIConfig: The AIConfig object tailored to the user's input
"""
system_prompt = DEFAULT_SYSTEM_PROMPT_AICONFIG_AUTOMATIC
prompt_ai_config_automatic = Template(
DEFAULT_TASK_PROMPT_AICONFIG_AUTOMATIC
).render(user_prompt=user_prompt)
# Call LLM with the string as user input
output = create_chat_completion(
ChatSequence.for_model(
config.fast_llm,
[
Message("system", system_prompt),
Message("user", prompt_ai_config_automatic),
],
),
config,
).content
# Debug LLM Output
logger.debug(f"AI Config Generator Raw Output: {output}")
# Parse the output
ai_name = re.search(r"Name(?:\s*):(?:\s*)(.*)", output, re.IGNORECASE).group(1)
ai_role = (
re.search(
r"Description(?:\s*):(?:\s*)(.*?)(?:(?:\n)|Goals)",
output,
re.IGNORECASE | re.DOTALL,
)
.group(1)
.strip()
)
ai_goals = re.findall(r"(?<=\n)-\s*(.*)", output)
api_budget = 0.0 # TODO: parse api budget using a regular expression
return AIConfig(ai_name, ai_role, ai_goals, api_budget)