This Slack chatbot app template offers a customizable solution for integrating AI-powered conversations into your Slack workspace. Here's what the app can do out of the box:
/ask-bolty
command to communicate with the bot in channels where it hasn't been addedInspired by ChatGPT-in-Slack
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.
*Paste your manifest code here*
(within the JSON tab) and click NextBefore you can run the app, you'll need to store some environment variables.
SLACK_BOT_TOKEN
.connections:write
scope. Copy this token. You will store this in your environment as SLACK_APP_TOKEN
.# Run these commands in the terminal. Replace with your app token, bot token, and the token for whichever API(s) you plan on using
export SLACK_BOT_TOKEN=<your-bot-token>
export SLACK_APP_TOKEN=<your-app-token>
export OPENAI_API_KEY=<your-api-key>
export ANTHROPIC_API_KEY=<your-api-key>
To use Google Cloud Vertex AI, follow this quick start to create a project for sending requests to the Gemini API, then gather Application Default Credentials with the strategy to match your development environment.
Once your project and credentials are configured, export environment variables to select from Gemini models:
export VERTEX_AI_PROJECT_ID=<your-project-id>
export VERTEX_AI_LOCATION=<location-to-deploy-model>
The project location can be located under the Region on the Vertex AI dashboard, as well as more details about available Gemini models.
# Clone this project onto your machine
git clone https://github.com/slack-samples/bolt-python-ai-chatbot.git
# Change into this project directory
cd bolt-python-ai-chatbot
# Setup your python virtual environment
python3 -m venv .venv
source .venv/bin/activate
# Install the dependencies
pip install -r requirements.txt
# Start your local server
python3 app.py
# Run flake8 from root directory for linting
flake8 *.py && flake8 listeners/
# Run black from root directory for code formatting
black .
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". Inside this directory, we group each listener based on the Slack Platform feature used, so /listeners/commands
handles incoming Slash Commands requests, /listeners/events
handles Events and so on.
/ai
ai_constants.py
: Defines constants used throughout the AI module.ai/providers
This module contains classes for communicating with different API providers, such as Anthropic, OpenAI, and Vertex AI. To add your own LLM, create a new class for it using the base_api.py
as an example, then update ai/providers/__init__.py
to include and utilize your new class for API communication.
__init__.py
:
This file contains utility functions for handling responses from the provider APIs and retrieving available providers./state_store
user_identity.py
: This file defines the UserIdentity class for creating user objects. Each object represents a user with the user_id, provider, and model attributes.
user_state_store.py
: This file defines the base class for FileStateStore.
file_state_store.py
: This file defines the FileStateStore class which handles the logic for creating and managing files for each user.
set_user_state.py
: This file creates a user object and uses a FileStateStore to save the user's selected provider to a JSON file.
get_user_state.py
: This file retrieves a users selected provider from the JSON file created with set_user_state.py
.
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