Add docs and format code

This commit is contained in:
Alrik Olson
2023-04-11 09:15:45 -07:00
parent b19eb74874
commit fd1cfd2eff
2 changed files with 112 additions and 27 deletions

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@@ -1,51 +1,78 @@
from promptgenerator import PromptGenerator from promptgenerator import PromptGenerator
def get_prompt(): def get_prompt():
"""
This function generates a prompt string that includes various constraints, commands, resources, and performance evaluations.
Returns:
str: The generated prompt string.
"""
# Initialize the PromptGenerator object
prompt_generator = PromptGenerator() prompt_generator = PromptGenerator()
# Add constraints # Add constraints to the PromptGenerator object
prompt_generator.add_constraint("~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.") prompt_generator.add_constraint(
prompt_generator.add_constraint("If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.") "~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.")
prompt_generator.add_constraint(
"If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.")
prompt_generator.add_constraint("No user assistance") prompt_generator.add_constraint("No user assistance")
prompt_generator.add_constraint('Exclusively use the commands listed in double quotes e.g. "command name"') prompt_generator.add_constraint(
'Exclusively use the commands listed in double quotes e.g. "command name"')
# Add commands # Define the command list
commands = [ commands = [
("Google Search", "google", {"input": "<search>"}), ("Google Search", "google", {"input": "<search>"}),
("Browse Website", "browse_website", {"url": "<url>", "question": "<what_you_want_to_find_on_website>"}), ("Browse Website", "browse_website", {
("Start GPT Agent", "start_agent", {"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"}), "url": "<url>", "question": "<what_you_want_to_find_on_website>"}),
("Message GPT Agent", "message_agent", {"key": "<key>", "message": "<message>"}), ("Start GPT Agent", "start_agent", {
"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"}),
("Message GPT Agent", "message_agent", {
"key": "<key>", "message": "<message>"}),
("List GPT Agents", "list_agents", {}), ("List GPT Agents", "list_agents", {}),
("Delete GPT Agent", "delete_agent", {"key": "<key>"}), ("Delete GPT Agent", "delete_agent", {"key": "<key>"}),
("Write to file", "write_to_file", {"file": "<file>", "text": "<text>"}), ("Write to file", "write_to_file", {
"file": "<file>", "text": "<text>"}),
("Read file", "read_file", {"file": "<file>"}), ("Read file", "read_file", {"file": "<file>"}),
("Append to file", "append_to_file", {"file": "<file>", "text": "<text>"}), ("Append to file", "append_to_file", {
"file": "<file>", "text": "<text>"}),
("Delete file", "delete_file", {"file": "<file>"}), ("Delete file", "delete_file", {"file": "<file>"}),
("Search Files", "search_files", {"directory": "<directory>"}), ("Search Files", "search_files", {"directory": "<directory>"}),
("Evaluate Code", "evaluate_code", {"code": "<full_code_string>"}), ("Evaluate Code", "evaluate_code", {"code": "<full_code_string>"}),
("Get Improved Code", "improve_code", {"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"}), ("Get Improved Code", "improve_code", {
("Write Tests", "write_tests", {"code": "<full_code_string>", "focus": "<list_of_focus_areas>"}), "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"}),
("Write Tests", "write_tests", {
"code": "<full_code_string>", "focus": "<list_of_focus_areas>"}),
("Execute Python File", "execute_python_file", {"file": "<file>"}), ("Execute Python File", "execute_python_file", {"file": "<file>"}),
("Task Complete (Shutdown)", "task_complete", {"reason": "<reason>"}), ("Task Complete (Shutdown)", "task_complete", {"reason": "<reason>"}),
("Generate Image", "generate_image", {"prompt": "<prompt>"}), ("Generate Image", "generate_image", {"prompt": "<prompt>"}),
("Do Nothing", "do_nothing", {}), ("Do Nothing", "do_nothing", {}),
] ]
# Add commands to the PromptGenerator object
for command_label, command_name, args in commands: for command_label, command_name, args in commands:
prompt_generator.add_command(command_label, command_name, args) prompt_generator.add_command(command_label, command_name, args)
# Add resources # Add resources to the PromptGenerator object
prompt_generator.add_resource("Internet access for searches and information gathering.") prompt_generator.add_resource(
"Internet access for searches and information gathering.")
prompt_generator.add_resource("Long Term memory management.") prompt_generator.add_resource("Long Term memory management.")
prompt_generator.add_resource("GPT-3.5 powered Agents for delegation of simple tasks.") prompt_generator.add_resource(
"GPT-3.5 powered Agents for delegation of simple tasks.")
prompt_generator.add_resource("File output.") prompt_generator.add_resource("File output.")
# Add performance evaluation # Add performance evaluations to the PromptGenerator object
prompt_generator.add_performance_evaluation("Continuously review and analyze your actions to ensure you are performing to the best of your abilities.") prompt_generator.add_performance_evaluation(
prompt_generator.add_performance_evaluation("Constructively self-criticize your big-picture behavior constantly.") "Continuously review and analyze your actions to ensure you are performing to the best of your abilities.")
prompt_generator.add_performance_evaluation("Reflect on past decisions and strategies to refine your approach.") prompt_generator.add_performance_evaluation(
prompt_generator.add_performance_evaluation("Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.") "Constructively self-criticize your big-picture behavior constantly.")
prompt_generator.add_performance_evaluation(
"Reflect on past decisions and strategies to refine your approach.")
prompt_generator.add_performance_evaluation(
"Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.")
# Generate prompt string # Generate the prompt string
prompt_string = prompt_generator.generate_prompt_string() prompt_string = prompt_generator.generate_prompt_string()
return prompt_string return prompt_string

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@@ -2,7 +2,14 @@ import json
class PromptGenerator: class PromptGenerator:
"""
A class for generating custom prompt strings based on constraints, commands, resources, and performance evaluations.
"""
def __init__(self): def __init__(self):
"""
Initialize the PromptGenerator object with empty lists of constraints, commands, resources, and performance evaluations.
"""
self.constraints = [] self.constraints = []
self.commands = [] self.commands = []
self.resources = [] self.resources = []
@@ -24,14 +31,28 @@ class PromptGenerator:
} }
def add_constraint(self, constraint): def add_constraint(self, constraint):
"""
Add a constraint to the constraints list.
Args:
constraint (str): The constraint to be added.
"""
self.constraints.append(constraint) self.constraints.append(constraint)
# {CommandLabel}: "{CommandName}", args: "{arg#Name}": "{arg#Prompt}"
def add_command(self, command_label, command_name, args=None): def add_command(self, command_label, command_name, args=None):
"""
Add a command to the commands list with a label, name, and optional arguments.
Args:
command_label (str): The label of the command.
command_name (str): The name of the command.
args (dict, optional): A dictionary containing argument names and their values. Defaults to None.
"""
if args is None: if args is None:
args = {} args = {}
command_args = {arg_key: arg_value for arg_key, arg_value in args.items()} command_args = {arg_key: arg_value for arg_key,
arg_value in args.items()}
command = { command = {
"label": command_label, "label": command_label,
@@ -42,23 +63,60 @@ class PromptGenerator:
self.commands.append(command) self.commands.append(command)
def _generate_command_string(self, command): def _generate_command_string(self, command):
args_string = ', '.join(f'"{key}": "{value}"' for key, value in command['args'].items()) """
Generate a formatted string representation of a command.
Args:
command (dict): A dictionary containing command information.
Returns:
str: The formatted command string.
"""
args_string = ', '.join(
f'"{key}": "{value}"' for key, value in command['args'].items())
return f'{command["label"]}: "{command["name"]}", args: {args_string}' return f'{command["label"]}: "{command["name"]}", args: {args_string}'
def add_resource(self, resource): def add_resource(self, resource):
"""
Add a resource to the resources list.
Args:
resource (str): The resource to be added.
"""
self.resources.append(resource) self.resources.append(resource)
def add_performance_evaluation(self, evaluation): def add_performance_evaluation(self, evaluation):
"""
Add a performance evaluation item to the performance_evaluation list.
Args:
evaluation (str): The evaluation item to be added.
"""
self.performance_evaluation.append(evaluation) self.performance_evaluation.append(evaluation)
def _generate_numbered_list(self, items, item_type='list'): def _generate_numbered_list(self, items, item_type='list'):
"""
Generate a numbered list from given items based on the item_type.
Args:
items (list): A list of items to be numbered.
item_type (str, optional): The type of items in the list. Defaults to 'list'.
Returns:
str: The formatted numbered list.
"""
if item_type == 'command': if item_type == 'command':
return "\n".join(f"{i+1}. {self._generate_command_string(item)}" for i, item in enumerate(items)) return "\n".join(f"{i+1}. {self._generate_command_string(item)}" for i, item in enumerate(items))
else: else:
return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items)) return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items))
def generate_prompt_string(self): def generate_prompt_string(self):
"""
Generate a prompt string based on the constraints, commands, resources, and performance evaluations.
Returns:
str: The generated prompt string.
"""
formatted_response_format = json.dumps(self.response_format, indent=4) formatted_response_format = json.dumps(self.response_format, indent=4)
prompt_string = ( prompt_string = (
f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n" f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n"