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name: "Planner/Jarvis" |
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description: "Generates plan with interactions with the user, used for the coder class" |
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_target_: Tachi67.JarvisFlowModule.Planner_JarvisFlow.instantiate_from_default_config |
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input_interface: |
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- "goal" |
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- "memory_files" |
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output_interface: |
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- "plan" |
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- "status" |
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- "summary" |
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subflows_config: |
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Controller: |
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_target_: Tachi67.PlanWriterFlowModule.PlanWriterCtrlFlow.instantiate_from_default_config |
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backend: |
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api_infos: ??? |
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model_name: |
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openai: gpt-4 |
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azure: azure/gpt-4 |
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Executor: |
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_target_: flows.base_flows.BranchingFlow.instantiate_from_default_config |
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subflows_config: |
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write_plan: |
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subflows_config: |
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PlanGenerator: |
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backend: |
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api_infos: ??? |
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model_name: |
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openai: gpt-4 |
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azure: azure/gpt-4 |
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system_message_prompt_template: |
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_target_: flows.prompt_template.JinjaPrompt |
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template: |2- |
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You are the planner for Jarvis, an intelligent agent able to achieve goals by writing and running code, you write step-by-step plans for Jarvis to follow and execute. |
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Jarvis is capable of: |
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1. Generating and running code, given a goal. |
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2. Giving a final answer to the user when the goal is achieved, it is also possible that Jarvis is able to give a final answer without writing and running code. |
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**Your task is: given a goal to achieve, decompose the goal into step-by-step plans for Jarvis, each step of your plan should ONLY involve one of the following: |
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1. Write and run code with a given goal generated by you, the goal should be a sub-goal of the current goal, it should be nicely separated from other-subgoals. |
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2. Give a final answer.** |
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Here are some criteria you should consider in order to write a good plan: |
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1. The plan should be nicely separated into steps, each step should involve either writing & running code, or giving a final answer. |
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2. Decompose the goal into sub-goals, each sub-goal should be nicely separated from other sub-goals, all the sub-goals should be logically linked in order to process each sub-goal to achieve the final goal. |
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Performance Evaluation: |
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1. Your plan must be as explicit, well-indented, and human-readable as possible. |
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2. Your plan must be step-by-step with number indexes, each step involves either writing & running code or giving a final answer. |
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3. You should make plans with as few steps as possible. |
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**Here is an example of a good plan:** |
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Goal: Send an email with the data of the weather in Paris of 19. Dec. 2021 to my friend. |
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Plan: |
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1. Write and run code to get the data of the weather in Paris of 19. Dec. 2021. |
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2. Write and run code to send an email with the data of the weather in Paris of 19. Dec. 2021 to my friend. |
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3. Give a final answer to the user. |
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**It's important that you should only respond in JSON format as described below:** |
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Response Format: |
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{ |
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"plan": "A well indented string, containing a step-by-step plan to finish the given goal", |
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} |
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Ensure your responses can be parsed by Python json.loads |
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**Make sure that the plan you generate is a well-indented human readable string, with numbered indexes for each step.** |
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PlanFileEditor: |
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_target_: Tachi67.PlanFileEditFlowModule.PlanFileEditAtomicFlow.instantiate_from_default_config |
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ParseFeedback: |
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_target_: Tachi67.ParseFeedbackFlowModule.ParseFeedbackAtomicFlow.instantiate_from_default_config |
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input_interface: |
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- "temp_plan_file_location" |
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output_interface: |
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- "plan" |
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- "feedback" |
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ask_user: |
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_target_: Tachi67.PlanWriterFlowModule.PlanWriterAskUserFlow.instantiate_from_default_config |
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early_exit_key: "EARLY_EXIT" |
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topology: |
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- goal: "Select the next action and prepare the input for the executor." |
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input_interface: |
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_target_: flows.interfaces.KeyInterface |
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additional_transformations: |
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- _target_: flows.data_transformations.KeyMatchInput |
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flow: Controller |
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output_interface: |
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_target_: Planner_JarvisFlow.detect_finish_or_continue |
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reset: false |
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- goal: "Execute the action specified by the Controller." |
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input_interface: |
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_target_: flows.interfaces.KeyInterface |
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keys_to_rename: |
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command: branch |
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command_args: branch_input_data |
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keys_to_select: ["branch", "branch_input_data"] |
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flow: Executor |
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output_interface: |
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_target_: flows.interfaces.KeyInterface |
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keys_to_rename: |
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branch_output_data: observation |
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keys_to_unpack: ["observation"] |
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reset: false |
