name: "ReplanningFlow" description: "Re-plan given old plan and new information" _target_: Tachi67.ReplanningFlowModule.ReplanningFlow.instantiate_from_default_config input_interface: - "goal" # info on the old plan - "plan" # the old plan - "plan_file_location" output_interface: - "plan" - "status" - "summary" - "result" ### Subflows specification subflows_config: Controller: _target_: Tachi67.PlanWriterFlowModule.PlanWriterCtrlFlow.instantiate_from_default_config backend: api_infos: ??? model_name: openai: gpt-4 azure: azure/gpt-4 input_interface_initialized: - "new_plan" - "feedback" system_message_prompt_template: _target_: langchain.PromptTemplate template: |2- You are in charge of a department of rewriting plans to solve a certain goal. You work with a re-planner, who does all the re-planning job. You are not given the old plan, the planner is aware of the old plan, you do not need to care about the details of it. Your **ONLY** task is to take the user's information about the old plan for you, to decide whether to call the re-planner to write or refine the plan, or to finish the current task. When you need to call the plan writer, call the `write_plan` command with the goal specified. When the plan is written and the user is satisfied, call the `finish` command to terminate the current process with a summary of what was done in one sentence. Whenever you are in doubt, or need to confirm something to the user, call `ask_user` with the question. You **must not** write plans yourself. You only decide whether to call the planner with specified goals or to finish. Your workflow: 0. Whenever the user demands to quit or terminate the current process, call `manual_finish` command. 1. Upon user request, call the `write_plan` with the information given. 2. The planner will write the plan. The user will examine the plan, and provide feedback. 3. Depending on the feedback of the user: 3.1. The user provides feedback on how to change the plan, **call the planner with user's specific requirements again, to ask the planner to refine the plan**. Go back to step 2. 3.2. The user does not provide details about refining the plan, for example, just stating the fact that the user has updated the plan, **this means the user is satisfied with the plan written, call the `finish` command.** 3.3. The user is satisfied with the plan, **call the `finish` command with a summary of what was done** If you have completed all your tasks, make sure to use the "finish" command, with a summary of what was done. Constraints: 1. Exclusively use the commands listed in double quotes e.g. "command name" Your response **MUST** be in the following format: Response Format: { "command": "call plan writer, or to finish", "command_args": { "arg name": "value" } } Ensure your responses can be parsed by Python json.loads Available Functions: {{commands}} input_variables: [ "commands" ] template_format: jinja2 human_message_prompt_template: _target_: flows.prompt_template.JinjaPrompt template: |2- Here is the new plan written by the planner, it might have been updated by the user, depending on the user's feedback: {{new_plan}} Here is the feedback from the user: {{feedback}} input_variables: - "new_plan" - "feedback" template_format: jinja2 init_human_message_prompt_template: _target_: flows.prompt_template.JinjaPrompt template: |2- Here is the information about the old plan: {{goal}} input_variables: - "goal" template_format: jinja2 Executor: _target_: flows.base_flows.BranchingFlow.instantiate_from_default_config subflows_config: write_plan: _target_: Tachi67.InteractivePlanGenFlowModule.InteractivePlanGenFlow.instantiate_from_default_config output_interface: - "new_plan" - "feedback" - "temp_plan_file_location" subflows_config: PlanGenerator: _target_: Tachi67.ReplanningFlowModule.NewPlanGenFlow.instantiate_from_default_config backend: api_infos: ??? model_name: openai: gpt-4 azure: azure/gpt-4 PlanFileEditor: _target_: Tachi67.PlanFileEditFlowModule.PlanFileEditAtomicFlow.instantiate_from_default_config input_interface: - "new_plan" - "plan_file_location" ParseFeedback: _target_: Tachi67.ParseFeedbackFlowModule.ParseFeedbackAtomicFlow.instantiate_from_default_config input_interface: - "temp_plan_file_location" output_interface: - "new_plan" - "feedback" topology: - goal: "Generate plan to achieve the task." input_interface: _target_: flows.interfaces.KeyInterface additional_transformations: - _target_: flows.data_transformations.KeyMatchInput flow: PlanGenerator reset: false - goal: "Write the plan generated to a temp file with instructions to the user" input_interface: _target_: flows.interfaces.KeyInterface additional_transformations: - _target_: flows.data_transformations.KeyMatchInput flow: PlanFileEditor reset: false - goal: "Parse user feedback from the temp file" input_interface: _target_: flows.interfaces.KeyInterface additional_transformations: - _target_: flows.data_transformations.KeyMatchInput flow: ParseFeedback output_interface: _target_: flows.interfaces.KeyInterface keys_to_rename: plan: new_plan reset: false ask_user: _target_: Tachi67.ReplanningFlowModule.ReplanningAskUserFlow.instantiate_from_default_config early_exit_key: "EARLY_EXIT" topology: - goal: "Select the next action and prepare the input for the executor." input_interface: _target_: flows.interfaces.KeyInterface additional_transformations: - _target_: flows.data_transformations.KeyMatchInput flow: Controller output_interface: _target_: ReplanningFlow.detect_finish_or_continue reset: false - goal: "Execute the action specified by the Controller." input_interface: _target_: flows.interfaces.KeyInterface keys_to_rename: command: branch command_args: branch_input_data keys_to_select: ["branch", "branch_input_data"] flow: Executor output_interface: _target_: flows.interfaces.KeyInterface keys_to_rename: branch_output_data: observation keys_to_unpack: ["observation"] reset: false