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| import json | |
| from typing import List | |
| from langchain.tools.base import BaseTool | |
| FINISH_NAME = "finish" | |
| class PromptGenerator: | |
| """A class for generating custom prompt strings. | |
| Does this based on constraints, commands, resources, and performance evaluations. | |
| """ | |
| def __init__(self) -> None: | |
| """Initialize the PromptGenerator object. | |
| Starts with empty lists of constraints, commands, resources, | |
| and performance evaluations. | |
| """ | |
| self.constraints: List[str] = [] | |
| self.commands: List[BaseTool] = [] | |
| self.resources: List[str] = [] | |
| self.performance_evaluation: List[str] = [] | |
| self.response_format = { | |
| "thoughts": { | |
| "text": "thought", | |
| "reasoning": "reasoning", | |
| }, | |
| "command": { | |
| "name": "command name", | |
| "args": { | |
| "goal": "the detailed description and necessary information of the subtask that you hope current command can achieve" | |
| }, | |
| }, | |
| } | |
| def add_constraint(self, constraint: str) -> None: | |
| """ | |
| Add a constraint to the constraints list. | |
| Args: | |
| constraint (str): The constraint to be added. | |
| """ | |
| self.constraints.append(constraint) | |
| def add_tool(self, tool: BaseTool) -> None: | |
| self.commands.append(tool) | |
| def _generate_command_string(self, tool: BaseTool) -> str: | |
| output = f"{tool.name}: {tool.description}" | |
| # json_args = json.dumps(tool.args) if "tool_input" not in tool.args else tool.args[ | |
| # "tool_input" | |
| # ] | |
| # output += f", args json schema: {json_args}" | |
| return output | |
| def add_resource(self, resource: str) -> None: | |
| """ | |
| Add a resource to the resources list. | |
| Args: | |
| resource (str): The resource to be added. | |
| """ | |
| self.resources.append(resource) | |
| def add_performance_evaluation(self, evaluation: str) -> None: | |
| """ | |
| Add a performance evaluation item to the performance_evaluation list. | |
| Args: | |
| evaluation (str): The evaluation item to be added. | |
| """ | |
| self.performance_evaluation.append(evaluation) | |
| def _generate_numbered_list(self, items: list, item_type: str = "list") -> str: | |
| """ | |
| 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": | |
| command_strings = [ | |
| f"{i + 1}. {self._generate_command_string(item)}" | |
| for i, item in enumerate(items) | |
| ] | |
| finish_description = ( | |
| "use this to signal that you have finished all your objectives" | |
| ) | |
| finish_args = ( | |
| '"response": "final response to let ' | |
| 'people know you have finished your objectives"' | |
| ) | |
| finish_string = ( | |
| f"{len(items) + 1}. {FINISH_NAME}: " | |
| f"{finish_description}, args: {finish_args}" | |
| ) | |
| return "\n".join(command_strings + [finish_string]) | |
| else: | |
| return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items)) | |
| def generate_prompt_string(self) -> str: | |
| """Generate a prompt string. | |
| Returns: | |
| str: The generated prompt string. | |
| """ | |
| formatted_response_format = json.dumps(self.response_format, indent=4) | |
| prompt_string = ( | |
| # f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n" | |
| f"Commands:\n" | |
| f"{self._generate_numbered_list(self.commands, item_type='command')}\n\n" | |
| # f"Resources:\n{self._generate_numbered_list(self.resources)}\n\n" | |
| f"Performance Evaluation:\n" | |
| f"{self._generate_numbered_list(self.performance_evaluation)}\n\n" | |
| f"You should only respond in JSON format as described below " | |
| f"\nResponse Format: \n{formatted_response_format} " | |
| f"\nEnsure the response can be parsed by Python json.loads" | |
| ) | |
| return prompt_string | |
| def get_prompt(tools: List[BaseTool]) -> str: | |
| """This function generates a prompt string. | |
| It includes various constraints, commands, resources, and performance evaluations. | |
| Returns: | |
| str: The generated prompt string. | |
| """ | |
| # Initialize the PromptGenerator object | |
| prompt_generator = PromptGenerator() | |
| # 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( | |
| "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( | |
| 'Exclusively use the commands listed in double quotes e.g. "command name"' | |
| ) | |
| # Add commands to the PromptGenerator object | |
| for tool in tools: | |
| prompt_generator.add_tool(tool) | |
| # Add resources to the PromptGenerator object | |
| prompt_generator.add_resource( | |
| "Internet access for searches and information gathering." | |
| ) | |
| 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("File output.") | |
| # 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( | |
| "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 the prompt string | |
| prompt_string = prompt_generator.generate_prompt_string() | |
| return prompt_string | |