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--- |
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license: gfdl |
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language: |
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- it |
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- es |
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- sc |
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- en |
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- de |
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- zh |
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- ar |
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tags: |
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- sqlite |
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- wikipedia |
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- wikilite |
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- eja |
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pretty_name: wikilite |
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--- |
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# Processed Wikipedia SQLite Databases for Wikilite |
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This dataset provides pre-processed SQLite databases of Wikipedia articles for use with the [Wikilite](https://github.com/eja/wikilite) tool. These databases allow you to quickly and efficiently search and access Wikipedia content offline using Wikilite's lexical and semantic search capabilities. |
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## Supported Languages |
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Currently, the dataset includes databases for the following languages: |
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* **Sardinian (sc)** |
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* **Italian (it)** |
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* **Spanish (es)** |
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* **English (en)** |
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* **German (de)** |
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* **Chinese (zh)** |
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* **Arabic (ar)** |
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More languages may be added in the future. |
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## Dataset Structure |
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Each language is stored as a separate compressed file (`.db.gz`). There are two types of databases available: |
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1. **Lexical Only**: Located in the `lexical/` directory. These support standard FTS5 full-text search (exact word matching) and are lighter in size. |
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2. **Semantic & Lexical**: Located in the root or specific model directories. These databases contain **embedded GGUF models** directly within the file structure, enabling both keyword search and vector-based conceptual search without external dependencies. |
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## How to Use This Dataset |
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### 1. Command Line & Web Interface (Linux, macOS, Windows, Termux) |
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Wikilite runs primarily as a command-line tool that can also serve a local web interface. |
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1. **Install Wikilite** |
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Download the precompiled binary for your operating system from the [Wikilite Releases](https://github.com/eja/wikilite/releases/latest) page and extract it. |
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2. **Download a Database** |
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You can download the `.db.gz` files manually from this repository and extract them, or use Wikilite's built-in tools to handle it for you: |
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* **Interactive Wizard:** Run `./wikilite` without arguments to launch a wizard that guides you through selecting and downloading a database. |
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* **Setup Command:** Run `./wikilite --setup` to view and download available databases automatically. |
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3. **Run Wikilite** |
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Once you have a database file (e.g., `wikilite.db`), you can use it in three ways: |
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* **Interactive Mode:** |
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```bash |
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./wikilite |
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``` |
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(Follow the on-screen prompts) |
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* **Command Line Search:** |
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```bash |
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./wikilite --cli --db <file.db> |
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``` |
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* **Web Interface:** |
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```bash |
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./wikilite --web --db <file.db> |
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``` |
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Access the interface at `http://localhost:35248` in your browser. |
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### 2. Android Application |
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A native Android application is available that uses these exact databases. |
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1. Download the [Android App APK](https://github.com/eja/wikilite/releases/latest/download/wikilite-android.apk). |
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2. **External Storage:** If you manually download a `wikilite.db` file from this repository and place it on your external SD card, the app will detect and use it automatically. |
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3. **In-App Download:** If no database is found on launch, the app provides an option to download these pre-built databases directly. |
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## About Wikilite |
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[Wikilite](https://github.com/eja/wikilite) is a self-contained tool for creating and browsing local SQLite databases of Wikipedia articles. |
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### Features |
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* **Lexical Search:** Uses FTS5 for efficient, exact keyword matching. |
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* **Semantic Search:** Uses embedded GGUF models (via llama.cpp integration) contained within the database files to find content based on meaning, synonyms, and conceptual similarity. |
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* **Offline Operation:** Complete functionality without internet connectivity. |
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* **Cross-Platform:** Available for Linux, macOS, Windows, Termux, and Android. |
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### Semantic Search Capabilities |
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The semantic search functionality employs text embeddings to handle: |
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* Query misspellings and typographical errors. |
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* Conceptual similarity despite different terminology. |
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* Synonym and related term matching. |
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* Morphological variations (plurals, verb tenses). |
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*Note: The semantic databases in this repository are fully self-contained. No external model files or API keys are required.* |
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## Contributing |
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If you would like to contribute databases for additional languages, please feel free to submit a pull request. |
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## Acknowledgments |
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* [Wikipedia](https://www.wikipedia.org/): For providing the valuable data. |
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* [SQLite](https://www.sqlite.org/): For the robust database engine. |
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* [LLaMA.cpp](https://github.com/ggml-org/llama.cpp): For enabling the internal generation of embeddings. |
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* [Wikilite](https://github.com/eja/wikilite): For the software powering these datasets. |
