planner

AutoGPT Planner Plugin

Simple planning commands for planning leveraged with chatgpt3.5 and json objects to keep track of its progress on a list of tasks.

Getting started

After you clone the plugin from the original repo (https://github.com/rihp/autogpt-planner-plugin) Add it to the plugins folder of your AutoGPT repo and then run AutoGPT

Remember to also update your .env to include

ALLOWLISTED_PLUGINS=PlannerPlugin

New commands

prompt.add_command(
    "check_plan",
    "Read the plan.md with the next goals to achieve",
    {},
    check_plan,
)

prompt.add_command(
    "run_planning_cycle",
    "Improves the current plan.md and updates it with progress",
    {},
    update_plan,
)

prompt.add_command(
    "create_task",
    "creates a task with a task id, description and a completed status of False ",
    {
        "task_id": "<int>",
        "task_description": "<The task that must be performed>",
    },
    create_task,
)

prompt.add_command(
    "load_tasks",
    "Checks out the task ids, their descriptionsand a completed status",
    {},
    load_tasks,
)

prompt.add_command(
    "mark_task_completed",
    "Updates the status of a task and marks it as completed",
    {"task_id": "<int>"},
    update_task_status,
)

New config options

By default, the plugin is set ot use what ever your FAST_LLM_MODEL environment variable is set to, if none is set it will fall back to gpt-3.5-turbo. If you want to set it individually to a different model you can do that by setting the environment variable PLANNER_MODEL to the model you want to use (example: gpt-4).

Similarly, the token limit defaults to the FAST_TOKEN_LIMIT environment variable, if none is set it will fall back to 1500. If you want to set it individually to a different limit for the plugin you can do that by setting PLANNER_TOKEN_LIMIT to the desired limit (example: 7500).

And last, but not least, the temperature used defaults to the TEMPERATURE environment variable, if none is set it will fall back to 0.5. If you want to set it individually to a different temperature for the plugin you can do that by setting PLANNER_TEMPERATURE to the desired temperature (example: 0.3).

CODE SAMPLES

Example of generating an improved plan

def generate_improved_plan(prompt: str) -> str:
    """Generate an improved plan using OpenAI's ChatCompletion functionality"""

    import openai

    tasks = load_tasks()

    # Call the OpenAI API for chat completion
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {
                "role": "system",
                "content": "You are an assistant that improves and adds crucial points to plans in .md format.",
            },
            {
                "role": "user",
                "content": f"Update the following plan given the task status below, keep the .md format:\n{prompt}\nInclude the current tasks in the improved plan, keep mind of their status and track them with a checklist:\n{tasks}\Revised version should comply with the contests of the tasks at hand:",
            },
        ],
        max_tokens=1500,
        n=1,
        temperature=0.5,
    )

Testing workflow

Clone the repo and modify the functionality, when you're done you can run

zip -ru ../fork/plugins/planner.zip . ; cd ../fork && python3 -m autogpt --debug 

then you need to cd back to

cd ../autogpt-planner-plugin