https://github.com/sqliteai/sqlite-aisearch-action
Automatically processes your documentation files and creates an SQLite AI-powered searchable database on SQLite Cloud
https://github.com/sqliteai/sqlite-aisearch-action
ai sqlite
Last synced: 2 days ago
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Automatically processes your documentation files and creates an SQLite AI-powered searchable database on SQLite Cloud
- Host: GitHub
- URL: https://github.com/sqliteai/sqlite-aisearch-action
- Owner: sqliteai
- Created: 2025-09-02T19:20:11.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-10-08T08:51:24.000Z (4 months ago)
- Last Synced: 2025-10-08T10:25:33.654Z (4 months ago)
- Topics: ai, sqlite
- Language: JavaScript
- Homepage: https://sqlite.ai
- Size: 337 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
[
](https://sqlite.ai)
# SQLite AI Search Action
Index your documentation files with SQLite AI-powered embeddings for intelligent search capabilities.
[](https://github.com/sqliteai/sqlite-aisearch-action/actions/workflows/test.yaml)
[](https://github.com/sqliteai/sqlite-aisearch-action/releases/latest)
## Overview
The SQLite AI Search Action automatically processes your documentation files and creates an AI-powered searchable database on SQLite Cloud. This action uses both embeddings to understand document content semantically and traditional full-text search, enabling more intelligent and contextual search results.
This action uses [sqlite-rag](https://github.com/sqliteai/sqlite-rag).
## How it works
1. **Downloads AI Model**: Retrieves the specified Hugging Face model to generate embeddings for semantic search
2. **Processes Documents**: Recursively scans and parses all documentation files in your repository
3. **Creates Dual Index**: Generates both AI embeddings and traditional full-text search indices for comprehensive search capabilities
4. **Builds Database**: Creates a SQLite database containing documents, embeddings, and search indices
5. **Uploads to SQLite Cloud**: Transfers the complete database to your SQLite Cloud project
6. **Integrates with Edge Function**: Works out-of-the-box with the predefined SQLite Cloud Edge Function template ([aisearch-docs.js](search_edge_function_template/aisearch-docs.js)) for instant search functionality
> **Note**: the SQLite Cloud Search Edge Function supports only the default model. Do not change the model settings if you want to use our search edge function.
## Usage
### Setup your workflow
1. **Get your Connection String**: Ensure you have a project on [SQLite Cloud dashboard](https://dashboard.sqlitecloud.io). If not, sign up to [SQLite AI](https://sqlite.ai) to create one for free.
2. **Set GitHub Secret**: Add your connection string as `SQLITECLOUD_CONNECTION_STRING` in your repository secrets.
3. **Add to Workflow**: Create or update your GitHub workflow:
```yaml
name: AI Search Index
on:
push:
branches: [main]
workflow_dispatch:
jobs:
build-search:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build AI Search Database
uses: sqliteai/sqlite-aisearch-action@v1
with:
connection_string: ${{ secrets.SQLITECLOUD_CONNECTION_STRING }}
base_url: https://docs.yoursite.com
database_name: aidocs_search.db
source_files: ./path/to/documents
```
### Create the Search Edge Function
To enable search functionality on your indexed database, you need to create an Edge Function using the provided template:
1. Access your dashboard on https://dashboard.sqlitecloud.io
2. Enter the same project where the created database has been uploaded
3. Go to the **Edge Functions** section
4. Create a new `Javascript Function` and copy and paste the code from [aisearch-docs.js](search_edge_function_template/aisearch-docs.js) in the editor
5. Deploy and test
#### How to perform a search
1. Go in the **Detail** in the Edge Function panel and copy the **Function URL**
2. Execute a GET request and send a URL-econded query as `query` parameter.
Example: `GET
https://myproject.cloud/v2/functions/aisearch-docs?query=what%27s+Offsync%3F`
Response example:
```json
{
"data": {
"search": [
{
"id": "c41a6c2e-34e9-4e8e-92b9-41b8065047c7",
"uri": "docs/sqlite-cloud/sdks/php/methods.mdx",
"metadata": "{\"base_url\": \"https://docs.sqlitecloud.io/docs/\"}",
"snippet": "---\ntitle: OffSync\ndescription: Enable local-first applications with automatic data synchronization between edge devices and SQLite Cloud...",
"vec_rank": 1,
"fts_rank": null,
"combined_rank": 0.0163934426229508,
"vec_distance": 0.581515073776245,
"fts_score": null
},
...
]
}
}
```
## Support
- 📖 [SQLite Cloud Documentation](https://docs.sqlitecloud.io)
- 💬 [Community Support](https://github.com/orgs/sqlitecloud/discussions)