Source code for langchain_experimental.autonomous_agents.autogpt.prompt_generator

import json
from typing import List

from langchain.tools.base import BaseTool

FINISH_NAME = "finish"


[docs]class PromptGenerator: """Generator of custom prompt strings. Does this based on constraints, commands, resources, and performance evaluations. """
[docs] 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", "plan": "- short bulleted\n- list that conveys\n- long-term plan", "criticism": "constructive self-criticism", "speak": "thoughts summary to say to user", }, "command": {"name": "command name", "args": {"arg name": "value"}}, }
[docs] 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)
[docs] 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}" output += f", args json schema: {json.dumps(tool.args)}" return output
[docs] 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)
[docs] 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))
[docs] 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
[docs]def get_prompt(tools: List[BaseTool]) -> str: """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