Slackbot that uses langchain under the hood

Local development:

1. Create your Slackbot first, by following this tutorial: https://slack.dev/bolt-python/tutorial/getting-started (We really need to create a bot template, and will do that in the future)

2. Then, copy .env.example to .env and fill in the values.

pip install -r requirements-dev.txt

#
# To run it locally (no need to use ngrok or anything)
./run_local.sh

# Now you can talk to the bot on Slack
@chatterbot Tell me a joke.

TODO:

• Deploy the bot to Railway
• Make the bot respond with markdown
• Use Redis for permanent memory
• Use OpenAI streaming to generate text
• Create a dev and staging bot that runs the bot with a different name in Slack
• Switch to use a different type of memory, like token buffer: https://langchain.readthedocs.io/en/latest/modules/memory/types/token_buffer.html
• Get rid of the error that happens when a system message happens and there isn't a "user" field.
• Welcome people to the channel via something creative
• On a regular basis (daily?), have Chatterbot say something interesting
• Notify the user if GPT is being slow...
• Usernames and Embed profile information about the people chatting with Chatterbot, if it hasn't already seen them before
• Use Slack-Machine as the framework
• Make Chatterbot not respond if it is not being spoken to directly
• Have a "Bot is typing..." message or some other indicator... (Also turns out this is impossible)
• Make the bot have a green dot if it's online or a grey dot if not (Turns out this is impossible in the new framework??)