SlackDocBot

Slack bot to chat with your code: Embed the code, chat with GPT, via LangChain

Setup

Create a env.py file:

BOT_TOKEN=""
SIGNING_SECRET=""
DEEPLAKE_USERNAME=""
DEEPLAKE_DB=""

pip install -r requirements.txt

Run

python SlackBot.py

Embed a repo

Embed.py allows you to generate embeddings for a repo using the EmbedRepo class and save them into a DeepLake database. Those embeddings can then be used by the GPT agent.

Example: python Embed.py -dir "../some_dir" -db "deeplake_db_name"

Arguments:

• -dir <dir>: This argument is required. Replace <dir> with the path to the repo you want to generate embeddings for.
• -username <username>: This argument is optional. Replace <username> with your DeepLake username. If you don't provide a username, the script will use the one provided in your env.py.
• -db <db>: This argument is optional. Replace <db> with the name of the DeepLake database where you want to save the embeddings. If you don't provide a database name, the script will use the one provided in your env.py.