BeeBot is your personal worker bee, an Autonomous AI Assistant designed to perform a wide range of practical tasks autonomously.
BeeBot is currently a work in progress and should be treated as an early stage research project. Its focus is not on production usage at this time. Please be patient as the foundations are still constantly shifting. The world of AI moves fast, and this project needs to move fast to keep up.
To get started with BeeBot, you can clone the repo to your local machine and install its dependencies using poetry
.
These instructions may vary depending on your local development environment.
git clone https://github.com/AutoPackAI/beebot.git
cd beebot
./setup.sh
Windows is officially unsupported but it may work. PRs are welcome for Windows compatibility but will not be a primary focus.
If you would like to enable persistence, start a Postgres database (or use your own), with docker compose up -d
.
Then, set the DATABASE_URL
environment variable in your .env file. If you're using docker, you can set this
to DATABASE_URL=postgresql://postgres:postgres@localhost:5432/postgres
.
To use the CLI run:
poetry run beebot
API (via e2b)
To start the server run:
uvicorn beebot.initiator.api:create_app --factory --timeout-keep-alive=300
If you're doing development on BeeBot itself, you may want to use this command:
uvicorn beebot.initiator.api:create_app --factory --reload --timeout-graceful-shutdown=3 --timeout-keep-alive=300
and then you can call the API using the following commands:
To create a task run:
curl --request POST \
--url http://localhost:8000/agent/tasks \
--header 'Content-Type: application/json' \
--data '{
"input": "Write '\''hello world'\'' to hi.txt"
}'
You will get a response like this:
{
"input": "Write 'hello world' to hi.txt",
"task_id": "103",
"artifacts": []
}
Then to execute one step of the task copy the task_id
you got from the previous request and run:
curl --request POST \
--url http://localhost:8000/agent/tasks/<task-id>/steps
To receive a stream of changes to all the data models in BeeBot, you can subscribe to the websocket connection at
the /notifications
endpoint with the same host/port as the web api, e.g. ws://localhost:8000/notifications. Use your
favorite websocket testing tool to try it out. (I like Insomnia)
We are working on a web interface using Node.js (Remix)
BeeBot's development process is guided by a specific philosophy, emphasizing key principles that shape its development and future direction.
The development of BeeBot is driven by the following priorities, always in this order:
- Functionality: BeeBot aims to achieve a high success rate for tasks within its range of expected capabilities.
- Flexibility: BeeBot strives to be adaptable to a wide range of tasks, expanding that range over time.
- Reliability: BeeBot focuses on reliably completing known tasks with predictability.
- Efficiency: BeeBot aims to execute tasks with minimal steps, optimizing both time and resource usage.
- Convenience: BeeBot aims to provide a user-friendly platform for task automation.
To achieve these priorities, BeeBot follows the following principles:
- Tool-focused: BeeBot carefully selects and describes tools, ensuring their reliable use by LLMs. It will utilize AutoPack as the package manager for its tools.
- LLM specialization: BeeBot will leverage a variety of LLMs best suited for different tasks, while OpenAI remains the primary LLM for planning and decision-making.
- Functionality and flexibility first: BeeBot prioritizes functionality and flexibility over developer quality-of-life, which may limit support for specific platforms and other deployment conveniences.
- Unorthodox methodologies: BeeBot employs unconventional development approaches to increase development speed, such as the absence of unit tests. Instead, end-to-end tests are used, ensuring the entire system works together as expected.
- Proven concepts: BeeBot adopts new concepts only after they have been proven to enhance its five priorities. As a result, it does not have complex memory or a tree of thought.
For further information on the architecture and future plans of BeeBot, please refer to the docs/
directory. The
documentation is currently very light, but will evolve alongside the project as new insights and developments emerge.
Contributions and feedback from the community are highly appreciated.