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https://github.com/AutoPackAI/beebot

An Autonomous AI Agent that works
https://github.com/AutoPackAI/beebot

artificial-intelligence autonomous-agents

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An Autonomous AI Agent that works

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README 

        
# BeeBot



BeeBot is your personal worker bee, an Autonomous AI Assistant designed to perform a wide range of practical tasks

autonomously.





BeeBot Mascot




## Status



Development of BeeBot is currently on hold. I've decided that LLMs as they are now (late 2023) aren't up to the task of generalized autonomous AI. I will revive the project if either:



- LLMs get significantly better at structured thinking, reliable outcomes, and obeying instructions

- I can develop or fine tune a custom model which is trained specifically for Autonomous AI

- I figure out a particular subset of tasks that BeeBot is acceptably good at that I can focus on. (Hint: It's not coding)



Check back here, hopefully this will get re-started.



## Features



- Tool selection via [AutoPack](https://autopack.ai) and the ability to acquire more tools during task execution

- Built-in persistence

- REST API conforming to the [e2b](https://www.e2b.dev/) standard.

- A websocket server to publish all events that occur within BeeBot

- Swappable filesystem emulation so that files can be stored in-memory, on-disk, or in a database

- A Web UI for managing your tasks (coming very soon)

- Dynamic manipulation of history during task execution

- Built-in caching with [Helicone](https://www.helicone.ai/) if enabled.



## Installation



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.



```bash

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.



### Persistence



Persistence is _required_. While SQLite is officially supported and is used in tests, it is highly recommended that

you use Postgres via docker, simply by executing `docker compose up -d`.



## Running



### CLI



To use the CLI run:



```bash

poetry run beebot

```



### API (via [e2b](https://www.e2b.dev/))



To start the server run:



```bash

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:



```bash

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:



```bash

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:



```json

{

  "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:



```bash

curl --request POST \

  --url http://localhost:8000/agent/tasks//steps

```



### Websocket Connection



_Note: Notifications are currently undergoing a rework and may not work at the moment_



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](https://insomnia.rest/))



### Web Interface



We are working on a web interface using Node.js (Remix)



## Philosophy



BeeBot's development process is guided by a specific philosophy, emphasizing key principles that shape its development

and future direction.



### Priorities



The development of BeeBot is driven by the following priorities, always in this order:



1. Functionality: BeeBot aims to achieve a high success rate for tasks within its range of _expected_ capabilities.

2. Flexibility: BeeBot strives to be adaptable to a wide range of tasks, expanding that range over time.

3. Reliability: BeeBot focuses on reliably completing known tasks with predictability.

4. Efficiency: BeeBot aims to execute tasks with minimal steps, optimizing both time and resource usage.

5. Convenience: BeeBot aims to provide a user-friendly platform for task automation.



### Principles



To achieve these priorities, BeeBot follows the following principles:



- Tool-focused: BeeBot carefully selects and describes tools, ensuring their reliable use by LLMs. It

  uses [AutoPack](https://autopack.ai) 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.



## Documentation



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.