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To build this Docker image you need to be in the root of the repository (i.e. the parent directory of this one).

Reginald model

The following command will build it the image for the (full) Reginald model which has the model + slack bot and tag it as reginald:latest:

docker build . -t reginald:latest -f docker/reginald/Dockerfile

The following environment variables can be used by this image:

  • REGINALD_MODEL: name of model to use
  • REGINALD_MODEL_NAME: name of sub-model to use with the one requested if not using hello model.
    • For llama-index-llama-cpp and `llama-index-hf`` models, this specifies the LLM (or path to that model) which we would like to use
    • For chat-completion-azure and llama-index-gpt-azure, this refers to the deployment name on Azure
    • For chat-completion-openai and llama-index-gpt-openai, this refers to the model/engine name on OpenAI
  • LLAMA_INDEX_MODE: mode to use ("query" or "chat") if using llama-index model
  • LLAMA_INDEX_DATA_DIR: data directory if using llama-index model
  • LLAMA_INDEX_WHICH_INDEX: index to use ("handbook", "wikis", "public", "reg" or "all_data") if using llama-index model
  • LLAMA_INDEX_FORCE_NEW_INDEX: whether to force a new index if using llama-index model
  • LLAMA_INDEX_MAX_INPUT_SIZE: max input size if using llama-index-llama-cpp or llama-index-hf model
  • LLAMA_INDEX_IS_PATH: whether to treat REGINALD_MODEL_NAME as a path if using llama-index-llama-cpp model
  • LLAMA_INDEX_N_GPU_LAYERS: number of GPU layers if using llama-index-llama-cpp model
  • LLAMA_INDEX_DEVICE: device to use if using llama-index-hf model
  • OPENAI_API_KEY: API key for OpenAI if using chat-completion-openai or llama-index-gpt-openai models
  • OPENAI_AZURE_API_BASE: API base for Azure OpenAI if using chat-completion-azure or llama-index-gpt-azure models
  • OPENAI_AZURE_API_KEY: API key for Azure OpenAI if using chat-completion-azure or llama-index-gpt-azure models
  • SLACK_APP_TOKEN: app token for Slack
  • SLACK_BOT_TOKEN: bot token for Slack

To run you can use the following command (to run the hello model):

docker run -e REGINALD_MODEL=hello -e SLACK_APP_TOKEN=<slack-app-token> -e SLACK_BOT_TOKEN=<slack-bot-token> reginald:latest

Slack bot only

The following command will build it the image for the Slack bot only and tag it as reginald-slack-bot:latest:

docker build . -t reginald-slack-bot:latest -f docker/slack_bot/Dockerfile

The following environment variables will be used by this image:

  • REGINALD_EMOJI: emoji to use for bot
  • SLACK_APP_TOKEN: app token for Slack
  • SLACK_BOT_TOKEN: bot token for Slack

To run you can use the following command:

docker run -e REGINALD_EMOJI=wave -e SLACK_APP_TOKEN=<slack-app-token> -e SLACK_BOT_TOKEN=<slack-bot-token> reginald-slack-bot:latest

Using an environment file

Rather than passing in the environment variables on the command line using the -e flag in docker run, you can use an environment file:

docker run --env-file .env reginald:latest

where .env is a file containing the environment variables, e.g. for running the llama-index-llama-cpp model using the handbook index:

REGINALD_MODEL=llama-index-llama-cpp
REGINALD_MODEL_NAME=https://huggingface.co/TheBloke/Llama-2-7B-chat-GGUF/resolve/main/llama-2-7b-chat.Q4_K_M.gguf
LLAMA_INDEX_MODE=chat
LLAMA_INDEX_DATA_DIR=data
LLAMA_INDEX_WHICH_INDEX=handbook
LLAMA_INDEX_MAX_INPUT_SIZE=2048
SLACK_APP_TOKEN=<slack-app-token>
SLACK_BOT_TOKEN=<slack-bot-token>