serve

• Run kobold-assistant serve after installing.
• Give it a while (at least a few minutes) to start up, especially the first time that you run it, as it downloads a few GB of AI models to do the text-to-speech and speech-to-text, and does some time-consuming generation work at startup, to save time later. It runs much more comfortably once it gets to the main conversational loop.
• While running, the system responds to special control commands. See Control Commands, below.

list-mics

Run kobold-assistant list-mics to list available microphones that kobold-assistant can use, when listen for the user's instructions. See the Configuration and Troubleshooting sections below, for more details on list-mics and related settings.

Requirements

• System packages:
  • GCC (c compiler)
  • portaudio development libraries
  • ffmpeg
• KoboldAI, KoboldCPP, or text-generation-webui running locally
  • For now, the only model known to work with this is stable-vicuna-13B-GPTQ. Any Alpaca-like or vicuna model will PROBABLY work. I'll add abstractions so that more models work, soon. Feel free to submit a PR with known-good models, or changes for multiple/other model support.
• Python >=3.7, <3.11
• Ubuntu/Debian

Control Commands

While running, there are two special commands that kobold-assistant responds to:

settings.SLEEP_COMMAND (default: 'Sleep Jenny')

This tells the assistant to go to sleep (to stop listening) until a wake command is given (see below).

settings.WAKE_COMMAND (default: 'Wake up Jenny')

This tells the assistant to start listening again, after it has been told to go to sleep (see above).

Installation

• On a Debian-like system (such as Debian, Ubuntu, Linux Mint, or Pop), run apt-get install -y $(cat requirements.apt). For other distros, read requirements.apt, figure out the equivalents for your distro (search your distro's packages), and ideally submit a PR with a similar requirements.yourdistro file and updated README.md for your distro.

• On the first run, if you are missing portaudio or a C compiler, or if you have an nvidia CPU, you may find that you need a bunch of other packages or libraries, like nvidia's cudnn. These are required by third-party dependencies. Most are covered by the step above. Aside from that, just try to run it and install any missing libraries that it complains about per your distro instructions, and failing that, the nvidia instructions for your distro. If your distro isn't supported by nvidia, all bets are off -- you might be better running it as CPU-only.

I'll try tidy this up the dependency situation in future, using docker or something, so you don't have to worry about dependencies, and it "just works", but nvidia make you sign up to their website to get a few of them right now, so there's probably no easy answer at the moment. Sadly, I don't think this code will get away from any nvidia dependencies for a while.

• Download the *.whl file from the latest release on github (http://github.com/lee-b/kobold_assistant/)
• Run pip install *.whl.

Configuration

To customize the configuration, run kobold_assistant default-config-path, and copy the the file at that path to ~/.config/kobold_assistant/settings.json, then edit it. You can also place config in /etc/kobold_assistant/settings.json.

The most important settings are as follows:

GENERATE_URL = "http://localhost:5000/api/v1/generate"

The KoboldAI API server endpoint, for generating text from a prompt using a large language model. Check the documentation and terminal output of KoboldAI-Client, KoboldCPP, Text-Generation-WebUI, or whichever other compatible server you're using.

MICROPHONE_DEVICE_INDEX: null

The device number of the microphone to listen for instructions on. Run kobold-assistant list-mics for a list. null means choose the default.

NOTE: The default (null) "should" auto-detect this for you; see the For now, see the SpeechRecognition library docs for details on exactly how this works.

AUTO_CALIBRATE_MIC: true

Automatically determine the microphone volume based on ambient noise levels.

STT_ENERGY_THRESHOLD: 1500

Energy level (mic volume) to use when NOT auto-calibrating (per above). Range is from 0 to 4000, with 1500 being reasonable for a well-calibrated mic.

KoboldAI

Really, you should check the KoboldAI instructions, but as a quick guide to getting it running on Debian, Ubuntu, Linux Mint, Pop! OS, or similar Debian-based Linux distros, for the purposes of running this, here's how to do it, at present. No guarantees that this will continue to work.

Known-good models

ROUGH requirements

ROUGH requirements (check the KoboldAI docs for better requirements): - nvidia card with CUDA and at least 12GB of Video RAM (VRAM) - A recent Debian-based distro - A GUI desktop session (this approach needs a browser)

NOTE: this is NOT the official KoboldAI version, but a development branch that supports 4bit quantized models. In future, it should be possible to use the official version instead, after this feature has been merged into it.

Debian/Ubuntu/Mint/Pop! OS Installation

This example is for the lightest model to run, on machines with limited resources. See Known-good Models below, for other options, and adjust accordingly to your needs.

sudo apt-get update && sudo apt-get install -y nvidia-cuda-toolkit git git-lfs
git clone https://github.com/0cc4m/KoboldAI -b latestgptq --recurse-submodules
cd KoboldAI
./install_requirements.sh
cd KoboldAI/models
git clone https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GPTQ TheBloke_WizardLM-7B-uncensored-GPTQ
cd TheBloke_WizardLM-7B-uncensored-GPTQ
ln -s WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors 4bit-128g.safetensors
cd ../..
./play.sh

Running

• The final step, running ./play.sh, should launch your web browser.
• In the browser, click AI
• Click Load a model from its directory
• Select the model that you cloned earlier, stable-vicuna-13B-GPTQ
• After selecting, some sliders appear at the bottom. Move the GPU 0 slider all the way to the right. NOTE: if this later fails to load, it's probably this slider that you need to change. Read the KoboldAI docs!
• Click Load.
• If this loads load successfully, the Loading message should disappear within a minute or two at most.
• Now, in a separate terminal, run kobold-assistant serve, per the docs above. stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors 4bit-128g.safetensors

Known-good Models

Any of these models will work. They're listed with the easiest model to run first, and the best (but more demanding) models last.

• TheBloke_WizardLM-7B-uncensored-GPTQ

  • Should run within 8GB
  • Obviously not as good as the more demanding models, but surprisingly similar to Alexa and other commercial offerings
  • Run ln -s WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors 4bit-128g.safetensors in the model directory before attempting to load it.

• TheBloke/stable-vicuna-13b

  • This should run in about 12GB
  • Seems about equivalent to Alexa
  • Run ln -s stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors 4bit-128g.safetensors in the model directory before attempting to load it.

• MetalX_GPT4-X-Alpasta-30b-4bit

  • This requires at least 24GB
  • It's a capable, general model, which seems better than Alexa
  • Run ln -s gpt4-x-alpasta-30b-128g-4bit.safetensors 4bit-128g.safetensors in the model directory before attempting to load it.

• TheBloke/WizardLM-30B-Uncensored-GPTQ

  • This requires at least 24GB
  • It's a capable, general model, which seems better than Alexa
  • Run ln -s WizardLM-30B-Uncensored-GPTQ-4bit.act-order.safetensors 4bit.safetensors in the model directory before attempting to load it.

• Any other 4bit, 128b safetensors llama-based model from huggingface should also work, using the above approaches.

Known-bad models

• `TheBl