Bumblebee is an LLM driven home assistant. Say the wake word "bumblebee" and ask any question you want to a local LLM model.

Requires a valid API key for PicoVoice (https://picovoice.ai/)

pip install -r requirements.txt

Copy one of the model.json.type files to model.json. This file is used to set the prompt format and ban tokens, the default is ChatML format so it should work with most recent models. Set the llama_endpoint to point to your llama.cpp running in server mode, if it's not on the same container/server as your SumBot service (see below!)

Copy sample.env to .env and put in your PicoVoice API key and the URL for your Bumblebee API (usually localhost port 3000)

uvicorn main:app --host 0.0.0.0 --port 3000 --reload

python3 bumblebee.py

We highly recommend OpenHermes 2.5 Mistral-7b fine tune for this task, as it's currently the best (Nov 2023) that we've tested personally. You can find different quantized versions of the model here:

https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GGUF/tree/main

I'd suggest the Q6 quant for GPU and Q4_K_M for CPU

Go to the llama.cpp releases and download either the win-avx2 package for CPU or the cublas for nvidia cards:

https://github.com/ggerganov/llama.cpp/releases

Extract the files out and run the following for nvidia GPUs:

server.exe -m <model>.gguf -t 4 -c 2048 -ngl 33 --host 0.0.0.0 --port 8086

For CPU only:

server.exe -m <model>.gguf -c 2048 --host 0.0.0.0 --port 8086

Replace with whatever model you downloaded and put into the llama.cpp directory

Follow the install instructions for llama.cpp at https://github.com/ggerganov/llama.cpp

Git clone, compile and run the following for GPU:

./server -m models/<model>.gguf -t 4 -c 2048 -ngl 33 --host 0.0.0.0 --port 8086

For CPU only:

./server -m models/<model>.gguf -c 2048 --host 0.0.0.0 --port 8086

Replace with whatever model you downloaded and put into the llama.cpp/models directory

http://localhost:3000/docs