Add docs and format code
Alrik Olson
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b19eb74874
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fd1cfd2eff
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@ -1,51 +1,78 @@
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from promptgenerator import PromptGenerator
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def get_prompt():
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"""
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This function generates a prompt string that includes various constraints, commands, resources, and performance evaluations.
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Returns:
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str: The generated prompt string.
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"""
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# Initialize the PromptGenerator object
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prompt_generator = PromptGenerator()
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# Add constraints
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prompt_generator.add_constraint("~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.")
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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.")
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# Add constraints to the PromptGenerator object
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prompt_generator.add_constraint(
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"~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.")
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prompt_generator.add_constraint(
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"If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.")
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prompt_generator.add_constraint("No user assistance")
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prompt_generator.add_constraint('Exclusively use the commands listed in double quotes e.g. "command name"')
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prompt_generator.add_constraint(
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'Exclusively use the commands listed in double quotes e.g. "command name"')
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# Add commands
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# Define the command list
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commands = [
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("Google Search", "google", {"input": "<search>"}),
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("Browse Website", "browse_website", {"url": "<url>", "question": "<what_you_want_to_find_on_website>"}),
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("Start GPT Agent", "start_agent", {"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"}),
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("Message GPT Agent", "message_agent", {"key": "<key>", "message": "<message>"}),
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("Browse Website", "browse_website", {
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"url": "<url>", "question": "<what_you_want_to_find_on_website>"}),
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("Start GPT Agent", "start_agent", {
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"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"}),
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("Message GPT Agent", "message_agent", {
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"key": "<key>", "message": "<message>"}),
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("List GPT Agents", "list_agents", {}),
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("Delete GPT Agent", "delete_agent", {"key": "<key>"}),
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("Write to file", "write_to_file", {"file": "<file>", "text": "<text>"}),
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("Write to file", "write_to_file", {
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"file": "<file>", "text": "<text>"}),
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("Read file", "read_file", {"file": "<file>"}),
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("Append to file", "append_to_file", {"file": "<file>", "text": "<text>"}),
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("Append to file", "append_to_file", {
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"file": "<file>", "text": "<text>"}),
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("Delete file", "delete_file", {"file": "<file>"}),
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("Search Files", "search_files", {"directory": "<directory>"}),
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("Evaluate Code", "evaluate_code", {"code": "<full_code_string>"}),
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("Get Improved Code", "improve_code", {"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"}),
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("Write Tests", "write_tests", {"code": "<full_code_string>", "focus": "<list_of_focus_areas>"}),
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("Get Improved Code", "improve_code", {
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"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"}),
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("Write Tests", "write_tests", {
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"code": "<full_code_string>", "focus": "<list_of_focus_areas>"}),
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("Execute Python File", "execute_python_file", {"file": "<file>"}),
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("Task Complete (Shutdown)", "task_complete", {"reason": "<reason>"}),
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("Generate Image", "generate_image", {"prompt": "<prompt>"}),
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("Do Nothing", "do_nothing", {}),
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]
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# Add commands to the PromptGenerator object
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for command_label, command_name, args in commands:
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prompt_generator.add_command(command_label, command_name, args)
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# Add resources
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prompt_generator.add_resource("Internet access for searches and information gathering.")
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# Add resources to the PromptGenerator object
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prompt_generator.add_resource(
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"Internet access for searches and information gathering.")
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prompt_generator.add_resource("Long Term memory management.")
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prompt_generator.add_resource("GPT-3.5 powered Agents for delegation of simple tasks.")
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prompt_generator.add_resource(
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"GPT-3.5 powered Agents for delegation of simple tasks.")
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prompt_generator.add_resource("File output.")
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# Add performance evaluation
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prompt_generator.add_performance_evaluation("Continuously review and analyze your actions to ensure you are performing to the best of your abilities.")
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prompt_generator.add_performance_evaluation("Constructively self-criticize your big-picture behavior constantly.")
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prompt_generator.add_performance_evaluation("Reflect on past decisions and strategies to refine your approach.")
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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.")
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# Add performance evaluations to the PromptGenerator object
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prompt_generator.add_performance_evaluation(
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"Continuously review and analyze your actions to ensure you are performing to the best of your abilities.")
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prompt_generator.add_performance_evaluation(
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"Constructively self-criticize your big-picture behavior constantly.")
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prompt_generator.add_performance_evaluation(
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"Reflect on past decisions and strategies to refine your approach.")
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prompt_generator.add_performance_evaluation(
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"Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.")
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# Generate prompt string
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# Generate the prompt string
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prompt_string = prompt_generator.generate_prompt_string()
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return prompt_string
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@ -2,7 +2,14 @@ import json
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class PromptGenerator:
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"""
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A class for generating custom prompt strings based on constraints, commands, resources, and performance evaluations.
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"""
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def __init__(self):
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"""
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Initialize the PromptGenerator object with empty lists of constraints, commands, resources, and performance evaluations.
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"""
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self.constraints = []
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self.commands = []
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self.resources = []
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@ -24,14 +31,28 @@ class PromptGenerator:
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}
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def add_constraint(self, constraint):
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"""
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Add a constraint to the constraints list.
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Args:
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constraint (str): The constraint to be added.
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"""
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self.constraints.append(constraint)
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# {CommandLabel}: "{CommandName}", args: "{arg#Name}": "{arg#Prompt}"
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def add_command(self, command_label, command_name, args=None):
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"""
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Add a command to the commands list with a label, name, and optional arguments.
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Args:
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command_label (str): The label of the command.
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command_name (str): The name of the command.
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args (dict, optional): A dictionary containing argument names and their values. Defaults to None.
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"""
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if args is None:
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args = {}
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command_args = {arg_key: arg_value for arg_key, arg_value in args.items()}
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command_args = {arg_key: arg_value for arg_key,
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arg_value in args.items()}
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command = {
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"label": command_label,
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@ -42,23 +63,60 @@ class PromptGenerator:
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self.commands.append(command)
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def _generate_command_string(self, command):
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args_string = ', '.join(f'"{key}": "{value}"' for key, value in command['args'].items())
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"""
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Generate a formatted string representation of a command.
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Args:
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command (dict): A dictionary containing command information.
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Returns:
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str: The formatted command string.
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"""
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args_string = ', '.join(
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f'"{key}": "{value}"' for key, value in command['args'].items())
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return f'{command["label"]}: "{command["name"]}", args: {args_string}'
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def add_resource(self, resource):
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"""
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Add a resource to the resources list.
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Args:
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resource (str): The resource to be added.
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"""
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self.resources.append(resource)
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def add_performance_evaluation(self, evaluation):
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"""
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Add a performance evaluation item to the performance_evaluation list.
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Args:
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evaluation (str): The evaluation item to be added.
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"""
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self.performance_evaluation.append(evaluation)
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def _generate_numbered_list(self, items, item_type='list'):
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"""
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Generate a numbered list from given items based on the item_type.
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Args:
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items (list): A list of items to be numbered.
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item_type (str, optional): The type of items in the list. Defaults to 'list'.
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Returns:
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str: The formatted numbered list.
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"""
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if item_type == 'command':
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return "\n".join(f"{i+1}. {self._generate_command_string(item)}" for i, item in enumerate(items))
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else:
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return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items))
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def generate_prompt_string(self):
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"""
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Generate a prompt string based on the constraints, commands, resources, and performance evaluations.
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Returns:
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str: The generated prompt string.
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"""
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formatted_response_format = json.dumps(self.response_format, indent=4)
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prompt_string = (
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f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n"
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