Bespoke Automata

Bespoke Automata, An Introduction

About Bespoke Automata

Create and deploy sophisticated Agent AI's to a single API with Bespoke Automata. With Bespoke Automata, you can combine large language models running locally or remotely with instruments for database IO, dictionaries, arrays, logic, APIs and more into powerful Brains capable of pursuing goals set by their designers.

With Bespoke Automata, you can design and test brains via a Directed Graph GUI (powered by litegraph), and deploy them behind a single user friendly API, each brain a different endpoint.

Demo Video

⚠️ READ CAREFULLY, INSTALLATION IS NOT STREAMLINED ⚠️

This is a development release and while the software is maturing, I would recommend you approach the installation process as you would any software under development. If you encounter any problems or would like to propose an improvement, please raise an issue. Join us on Discord, we would love to hear about what you're building with Bespoke Automata.

How to install/run BA and it's stack:

Requirements

• NPM
  • Electron-forge
  • Yarn
• Python
  • flask
  • sentence_transformers

Optional GPU support

• Cuda/Blas/etc setup
• Cuda Toolkit
• NVCC
• For metal support in MAC OSX, llama-cpp-python should work out of the box

GUI

The bespoke automata GUI is a node graph UI using a modified litegraph, so it should be familiar to ComfyUI users

Installation

Clone the repository and open the directory

$ git clone https://github.com/C0deMunk33/bespoke_automata
$ cd bespoke_automata

Use yarn to install and run

$ yarn install
$ yarn run start

work through installing the modules until it works

Llama:

The LLM API uses llama-cpp-python https://github.com/abetlen/llama-cpp-python

• place models in the folder ../models/text

• NOTE THIS IS AT THE SAME LEVEL AS THIS REPO, GGUF work best IMO, get then from Hugging Face.* NOTE: if you are running non-cuda (Apple silicon, AMD, Intel,CPU etc) you will need to follow the instructions on https://github.com/abetlen/llama-cpp-python to compile for your hardware NOTE: llama-cpp-python binaries on Apple M* hardware have been tested to be grand.

• Metal OSX: CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python

• CUDA LINUX: CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python

• CUDA WINDOWS: $env:CMAKE_ARGS = "-DLLAMA_CUBLAS=on" then pip install llama-cpp-python

• CPU: pip install llama-cpp-python

• cd bespoke_automata/APIs/

• python llama_api.py

• work through pip installs until it works

• the server will be your_ip:5000

• endpoint acts like GPT (and defaults to GPT, but that may be broken)

  NOTE: On OSX, port 5000 collides with Airplay Receiver. You can either turn it off in Settings > General > Airdrop & Handoff or switch the port in the config.

Simple Vector DB:

For simple vector DB nodes, you will need to have this running

• cd bespoke_automata/APIs/
• python simple_vector_db_api.py
• work through any pip installs
• endpoint will be your_ip:4999

Back end:

Once completed, a brain can be deployed as API endpoints.

• save brain to bespoke_automata/bespoke_manager/graphs
• cd bespoke_automata/bespoke_manager/
• node server.js
• work through any NPM install issues
• Brains will be your_ip:9999
• your_ip:9999/brains will list brains
• your_ip:9999/brains/[brain filename sans extension] is brain endpoint
• your_ip:9999/brains/[brain filename sans extension]/schema shows IO params for that brain

More Info:

• Demo Brains: ./bespoke_manager/graphs
• Example: https://youtu.be/w_saaTFEuSM
• Issues: Create an issue here or ping me at: https://twitter.com/icodeagents
• Contact: https://twitter.com/icodeagents
• Discord: https://discord.gg/hAd6WuYf

THANKS AND GOOD LUCK!!