https://github.com/danishi/slack-url-summarize-gemini
Summarize URLs in Slack messages using Gemini
https://github.com/danishi/slack-url-summarize-gemini
gemini google-cloud python slack
Last synced: 6 months ago
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Summarize URLs in Slack messages using Gemini
- Host: GitHub
- URL: https://github.com/danishi/slack-url-summarize-gemini
- Owner: danishi
- License: mit
- Created: 2024-09-15T23:52:33.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-08T05:22:15.000Z (9 months ago)
- Last Synced: 2025-05-11T10:09:16.467Z (6 months ago)
- Topics: gemini, google-cloud, python, slack
- Language: Python
- Homepage:
- Size: 53.7 KB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Summarize URLs in Slack messages using Gemini
[](https://github.com/danishi/slack-url-summarize-gemini/blob/main/LICENSE)
[](https://makeapullrequest.com)
A Slack bot that summarizes URLs shared in Slack channels using Google Cloud Functions (Cloud Run function 1st gen) and Vertex AI Gemini model.
## Table of Contents
- [Features](#features)
- [Architecture](#architecture)
- [Prerequisites](#prerequisites)
- [Setup](#setup)
- [Configuration](#configuration)
- [Deployment](#deployment)
- [Slack App Setup](#slack-app-setup)
- [License](#license)
- [Acknowledgments](#acknowledgments)
## Features
- Automatically summarizes articles from shared URLs in Slack.
- Extracts important keywords and generates a summary.
- Integrates with Google Cloud Functions and Vertex AI.
## Architecture
- **Slack Bot**: Built using the `slack_bolt` framework.
- **Google Cloud Functions**: Hosts the bot's backend logic.
- **Vertex AI**: Uses the Gemini model for text summarization.
- **Dependencies**: Managed via `requirements.txt`.
## Prerequisites
- **Google Cloud Platform (Google Cloud) Account** with billing enabled.
- **Slack Workspace** where you have permission to install apps.
- **Python 3.12+** installed locally for development.
- **Google Cloud SDK** installed and configured with your account.
## Setup
### 1. Clone the Repository
```bash
git clone https://github.com/danishi/slack-url-summarize-gemini.git
cd slack-url-summarize-gemini
```
### 2. Install Dependencies
Create a virtual environment and install the required packages:
```bash
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
## Configuration
### 1. Environment Variables
Create a `.env` file in the root directory and add the following environment variables:
```dotenv
SLACK_BOT_TOKEN=your-slack-bot-token
SLACK_SIGNING_SECRET=your-slack-signing-secret
SLACK_REACTION_KEY=the-reaction-keyword
SLACK_PROCESSING_REACTION_KEY=the-processing-reaction-keyword
GOOGLE_CLOUD_PROJECT=your-gcp-project-id
GOOGLE_CLOUD_LOCATION=us-central1
GOOGLE_MODEL_NAME=gemini-2.0-flash-001
```
- **SLACK_BOT_TOKEN**: Obtain this from Slack after installing your app.
- **SLACK_SIGNING_SECRET**: Found in your Slack app's Basic Information page.
- **SLACK_REACTION_KEY**: The emoji name that triggers the bot (e.g., `summarize`).
- **SLACK_PROCESSING_REACTION_KEY**: The emoji name that processing the bot (e.g., `processing`).
- **GOOGLE_CLOUD_PROJECT**: Your Google Cloud project ID.
- **GOOGLE_CLOUD_LOCATION**: The location of your Google Cloud resources (e.g., `asia-northeast1`).
- **GOOGLE_MODEL_NAME**: The gen AI model name (e.g., `gemini-1.5-flash-001`).
### 2. Vertex AI Setup
Ensure that the Vertex AI API is enabled in your Google Cloud project and you have the necessary permissions.
## Deployment
### 1. Deploy to Google Cloud Functions
#### a. Zip the Application
```bash
zip -r function.zip .
```
#### b. Deploy via Google Cloud Console or CLI
**Using gcloud CLI:**
```bash
gcloud functions deploy slack_events_fn \
--runtime python312 \
--trigger-http \
--allow-unauthenticated \
--entry-point slack_events_fn \
--memory 512MB \
```
**Parameters:**
- **--runtime**: Python version.
- **--trigger-http**: Expose the function via HTTP.
- **--allow-unauthenticated**: Allow public access.
- **--entry-point**: The function to execute (`slack_events_fn`).
- **--memory**: Allocate enough memory (recommended 512MB or higher).
#### c. Note the Function URL
After deployment, note the URL provided. This will be used in Slack app configuration.
## Slack App Setup
### 1. Create a Slack App
- Navigate to [Slack API](https://api.slack.com/apps) and click **"Create New App"**.
- Choose **"From scratch"** and provide an app name and select your workspace.
### 2. Configure OAuth & Permissions
- In your app settings, go to **OAuth & Permissions**.
- Under **Scopes**, add the following **Bot Token Scopes**:
- `app_mentions:read`
- `channels:history`
- `reactions:read`
- `chat:write`
- `groups:history`
- `reactions:read`
- `reactions:write`
- `users:read`
- `im:history`
### 3. Configure Event Subscriptions
- Go to **Event Subscriptions** and toggle **Enable Events** to **On**.
- **Request URL**: Enter your Google Cloud Function URL.
- Under **Subscribe to Bot Events**, add:
- `message.channels`
- `reaction_added`
### 4. Configure Interactivity & Shortcuts
- Go to **Interactivity & Shortcuts** and toggle **Interactivity** to **On**.
- **Request URL**: Enter your Google Cloud Function URL.
### 5. Install the App to Your Workspace
- Go to **Install App** and click **"Install App to Workspace"**.
- Authorize the app to your workspace.
- Copy the **Bot User OAuth Token** and **Signing Secret** to your `.env` file or set them as environment variables in Google Cloud.
## License
This project is licensed under the [MIT License](LICENSE).
## Acknowledgments
- [Slack API](https://api.slack.com/)
- [Google Cloud Functions](https://cloud.google.com/functions)
- [Vertex AI](https://cloud.google.com/vertex-ai)
- [Slack Bolt for Python](https://slack.dev/bolt-python/)