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.

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

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

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

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

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.

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

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

• 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