This Python script enables a Slack app to summarize messages from specified channels using OpenAI's GPT-3.5 model. It also includes functionality to respond to real-time Slack commands and can operate in a scheduled mode to run summarizations periodically.

• Real-Time Interaction: Responds to /digest command in Slack to summarize channel messages based on user preferences.
• Batch Summarization: Can be scheduled to automatically summarize messages from specified channels at regular intervals using a cron job or similar scheduling mechanism.
• Customizable: User and channel preferences can be stored and retrieved using a shelve database, allowing for persistent and customizable configurations.

Before you can run this script, you'll need:

• Python 3.8+
• Slack App with a Bot token and permissions to read channel messages and post messages.
• An OpenAI API key with access to the GPT-3.5 model.

You need to set the following environment variables:

• OPENAI_API_KEY: Your OpenAI API key.
• SLACK_BOT_TOKEN: Your Slack Bot User OAuth Token (xoxb-).
• SLACK_TOKEN: Your Slack App-Level Token (xapp- for Socket Mode).
• SLACK_WEBHOOK_URL: Your Slack incoming webhook URL (if needed).

You can set these variables in your environment or use a .env file and load them with python-dotenv.

Install the required Python packages:

pip install openai slack_bolt slack_sdk shelve

1. Create a new Slack App in your workspace.
2. Add the Bot Token Scopes:
   • channels:history
   • chat:write
   • commands
3. Install the app to your workspace and invite it to the channels it needs access to.

• Interactive Mode (listening to Slack events):

  python slackgpt.py

• Batch Mode (Daily Summaries):

python slackgpt.py --summarize-only

/digest [channel_names]: Triggers the summarization of the specified channels and posts the summaries and stores it in the db for cron job.