Demonstrates pagination of Algolia results in Streamlit and on-demand Algolia index updates right from the Streamlit app.

Tech Stack:

• Streamlit for Python-based UI
• Algolia for search functionality
• Supabase for database operations (can be replaced with any database)

Implements a book search interface using Streamlit for the UI, Algolia for search, and Supabase for data persistence. Search includes:

• Typo tolerance and instant results
• Pagination of search results
• Caching to reduce API calls
• Real-time index synchronization on data changes
• Error handling and edge cases

Dataset: 27,000+ book records from Kaggle's Books dataset

Before you begin, ensure you have:

1. Python 3.10+ installed
2. An Algolia account (Sign up for free)
3. A Supabase project (Create one here)

# If you have git installed
git clone https://github.com/SiddhantSadangi/streamlit_algolia.git
cd algolia

# Or download and extract the project folder

Create a virtual environment (recommended):

# On Windows
python -m venv venv
venv\Scripts\activate

# On macOS/Linux
python3 -m venv venv
source venv/bin/activate

Install required packages:

pip install -r requirements.txt

1. Sign up for Supabase at https://supabase.com/dashboard

2. Create a new project

3. Navigate to the Table Editor in Supabase dashboard

4. Create the books table by uploading the books.csv file. Use ISBN as the primary key.

5. Get your Supabase credentials:

   • Navigate to Project Settings → API
   • Copy your Project URL
   • Copy your anon/public key

1. Sign up for Algolia at https://www.algolia.com/users/sign_up

2. Create a new application in your Algolia dashboard

3. Note your credentials:

   • Application ID
   • Write API Key (needed for updating the index)

1. In your Algolia dashboard, go to Data Sources
2. Click Add a data source → Select Supabase
3. Configure the connection:
   • Trigger: On demand (or set up automatic triggers)
   • Indexing strategy: Full record updates
   • Source table: books
   • Destination index: books_dataset
   • Map fields from your books table to Algolia index. Use ISBN as the ObjectID.
4. Run the initial sync to populate your Algolia index

Create a .streamlit folder in your project root if it doesn't exist:

mkdir .streamlit

Create a secrets.toml file in the .streamlit folder:

# .streamlit/secrets.toml

# Supabase Configuration
SUPABASE_URL = "https://your-project.supabase.co"
SUPABASE_KEY = "your-anon-key-here"

# Algolia Configuration
ALGOLIA_APP_ID = "your-app-id-here"
ALGOLIA_API_KEY = "your-write-api-key-here"

Replace the placeholders with your actual credentials from Steps 3 and 4.

streamlit run app.py

The app will open in your default browser at http://localhost:8501

1. Enter a search query in the main search box (e.g., "Harry Potter", "Mystery", "Crichton")
2. View results with pagination controls
3. Use the pagination buttons to navigate through multiple pages
4. Click "Raw results" to see the full API response

1. Add a Book:

   • Enter ISBN and title in the sidebar
   • Click "Add/Update Book"
   • The book will be added to both Supabase and Algolia in real-time

2. Update a Book:

   • Enter the ISBN of an existing book
   • Enter a new title or year of publication
   • Click "Add/Update Book" (uses upsert logic)
   • Only this one record is updated in Algolia, not the entire index

3. Delete a Book:

   • Enter the ISBN
   • Click "Delete Book"
   • The book will be removed from both systems immediately

4. View Current Books:

   • Check the dataframe at the bottom of the sidebar
   • Shows all books currently in the database

• Algolia Documentation
• Supabase Documentation
• Streamlit Documentation
• Books Dataset on Kaggle