This is a node.js fork of the yoheinakajima/babyagi python project.
The README has slight changes for Node.js, but otherwise remains the unchanged.
This Python script is an example of an AI-powered task management system. The system uses OpenAI and Pinecone APIs to create, prioritize, and execute tasks. The main idea behind this system is that it creates tasks based on the result of previous tasks and a predefined objective. The script then uses OpenAI's natural language processing (NLP) capabilities to create new tasks based on the objective, and Pinecone to store and retrieve task results for context. This is a paired-down version of the original Task-Driven Autonomous Agent (Mar 28, 2023).
This README will cover the following:
- How the script works
- How to use the script
- Warning about running the script continuously
The script works by running an infinite loop that does the following steps:
- Pulls the first task from the task list.
- Sends the task to the execution agent, which uses OpenAI's API to complete the task based on the context.
- Enriches the result and stores it in Pinecone.
- Creates new tasks and reprioritizes the task list based on the objective and the result of the previous task. The execution_agent() function is where the OpenAI API is used. It takes two parameters: the objective and the task. It then sends a prompt to OpenAI's API, which returns the result of the task. The prompt consists of a description of the AI system's task, the objective, and the task itself. The result is then returned as a string.
The task_creation_agent() function is where OpenAI's API is used to create new tasks based on the objective and the result of the previous task. The function takes four parameters: the objective, the result of the previous task, the task description, and the current task list. It then sends a prompt to OpenAI's API, which returns a list of new tasks as strings. The function then returns the new tasks as a list of dictionaries, where each dictionary contains the name of the task.
The prioritization_agent() function is where OpenAI's API is used to reprioritize the task list. The function takes one parameter, the ID of the current task. It sends a prompt to OpenAI's API, which returns the reprioritized task list as a numbered list.
Finally, the script uses Pinecone to store and retrieve task results for context. The script creates a Pinecone index based on the table name specified in YOUR_TABLE_NAME variable. Pinecone is then used to store the results of the task in the index, along with the task name and any additional metadata.
To use the script, you will need to follow these steps:
- Install the required packages:
npm install - Copy the .env.example file to .env:
cp .env.example .env. This is where you will set the following variables. - Set your OpenAI and Pinecone API keys in the OPENAI_API_KEY and PINECONE_API_KEY variables.
- Set the Pinecone environment in the PINECONE_ENVIRONMENT variable.
- Set the name of the table where the task results will be stored in the TABLE_NAME variable.
- Set the objective of the task management system in the OBJECTIVE variable. Alternatively you can pass it to the script as a quote argument.
npm run start ["<objective>"]- Set the first task of the system in the FIRST_TASK variable.
- Run the script.
This script is designed to be run continuously as part of a task management system. Running this script continuously can result in high API usage, so please use it responsibly. Additionally, the script requires the OpenAI and Pinecone APIs to be set up correctly, so make sure you have set up the APIs before running the script.
Very appreciative of the PRs, which I've started pulling! I am new to GitHub and open source, so please be patient as I learn to manage this project properly. I run a VC firm by day, so I will generally be checking PRs and issues at night after I get my kids down - which may not be every night. Open to the idea of bringing in support, will be updating this section soon (expectations, visions, etc). Talking to lots of people and learning - hang tight for updates!
BabyAGI is a paired-down version of the original Task-Driven Autonomous Agent (Mar 28, 2023) shared on Twitter. This version is down to 140 lines: 13 comments, 22 blank, 105 code. The name of the repo came up in the reaction to the original autonomous agent - the author does not mean to imply that this is AGI.
Made with love by @yoheinakajima, who happens to be a VC (would love to see what you're building!)