AI Agent App Template (Bolt for Python)

This Bolt for Python template demonstrates how to build AI Apps in Slack.

Models from OpenAI are used and can be customized for prompts of all kinds.

Setup

Before getting started, make sure you have a development workspace where you have permissions to install apps. If you don’t have one setup, go ahead and create one.

Developer Program

Join the Slack Developer Program for exclusive access to sandbox environments for building and testing your apps, tooling, and resources created to help you build and grow.

Installation

Add this app to your workspace using either the Slack CLI or other development tooling, then read ahead to configuring LLM responses in the Providers section.

Using Slack CLI

Install the latest version of the Slack CLI for your operating system:

• Slack CLI for macOS & Linux
• Slack CLI for Windows

You'll also need to log in if this is your first time using the Slack CLI.

slack login

Initializing the project

slack create my-bolt-python-assistant --template slack-samples/bolt-python-assistant-template
cd my-bolt-python-assistant

Creating the Slack app

Use the following command to add your new Slack app to your development workspace. Choose a "local" app environment for upcoming development:

slack install

After the Slack app has been created you're all set to configure the LLM provider!

Using Terminal

1. Open https://api.slack.com/apps/new and choose "From an app manifest"
2. Choose the workspace you want to install the application to
3. Copy the contents of manifest.json into the text box that says *Paste your manifest code here* (within the JSON tab) and click Next
4. Review the configuration and click Create
5. Click Install to Workspace and Allow on the screen that follows. You'll then be redirected to the App Configuration dashboard.

Environment Variables

Before you can run the app, you'll need to store some environment variables.

1. Rename .env.sample to .env.
2. Open your apps setting page from this list, click OAuth & Permissions in the left hand menu, then copy the Bot User OAuth Token into your .env file under SLACK_BOT_TOKEN.

SLACK_BOT_TOKEN=YOUR_SLACK_BOT_TOKEN

3. Click Basic Information from the left hand menu and follow the steps in the App-Level Tokens section to create an app-level token with the connections:write scope. Copy that token into your .env as SLACK_APP_TOKEN.

SLACK_APP_TOKEN=YOUR_SLACK_APP_TOKEN

Initializing the project

git clone https://github.com/slack-samples/bolt-python-assistant-template.git my-bolt-python-assistant
cd my-bolt-python-assistant

Setup your python virtual environment

python3 -m venv .venv
source .venv/bin/activate  # for Windows OS, .\.venv\Scripts\Activate instead should work

Install dependencies

pip install -r requirements.txt

Providers

OpenAI Setup

Unlock the OpenAI models from your OpenAI account dashboard by clicking create a new secret key, then save your OpenAI key into the .env file as OPENAI_API_KEY like so:

OPENAI_API_KEY=YOUR_OPEN_API_KEY

Development

Starting the app

Slack CLI

slack run

Terminal

python3 app.py

Start talking to the bot! Start a new DM or thread and click the feedback button when it responds.

Linting

# Run ruff check from root directory for linting
ruff check

# Run ruff format from root directory for code formatting
ruff format

Project Structure

manifest.json

manifest.json is a configuration for Slack apps. With a manifest, you can create an app with a pre-defined configuration, or adjust the configuration of an existing app.

app.py

app.py is the entry point for the application and is the file you'll run to start the server. This project aims to keep this file as thin as possible, primarily using it as a way to route inbound requests.

/listeners

Every incoming request is routed to a "listener". This directory groups each listener based on the Slack Platform feature used, so /listeners/events handles incoming events, /listeners/shortcuts would handle incoming Shortcuts requests, and so on.

/listeners/assistant

Configures the new Slack Assistant features, providing a dedicated side panel UI for users to interact with the AI chatbot. This module includes:

• The assistant_thread_started.py file, which responds to new app threads with a list of suggested prompts.
• The message.py file, which responds to user messages sent to app threads or from the Chat and History tab with an LLM generated response.

/ai

The llm_caller.py file, which handles OpenAI API integration and message formatting. It includes the call_llm() function that sends conversation threads to OpenAI's models.

App Distribution / OAuth

Only implement OAuth if you plan to distribute your application across multiple workspaces. A separate app_oauth.py file can be found with relevant OAuth settings.

When using OAuth, Slack requires a public URL where it can send requests. In this template app, we've used ngrok. Checkout this guide for setting it up.

Start ngrok to access the app on an external network and create a redirect URL for OAuth.

ngrok http 3000

This output should include a forwarding address for http and https (we'll use https). It should look something like the following:

Forwarding   https://3cb89939.ngrok.io -> http://localhost:3000

Navigate to OAuth & Permissions in your app configuration and click Add a Redirect URL. The redirect URL should be set to your ngrok forwarding address with the slack/oauth_redirect path appended. For example:

https://3cb89939.ngrok.io/slack/oauth_redirect