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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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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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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`) within the dataset. For example: |
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* `it.db.gz` - Italian Wikipedia database (lexical only) |
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* `sc.all-mini.db.gz` - Sardinian Wikipedia database (lexical and semantic) |
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## How to Use this Dataset |
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1. **Download the Desired Database:** Choose the database for the language you want to use and download the corresponding `.db.gz` file. |
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2. **Decompress the Database:** Use a tool like `gunzip` to decompress the downloaded file. For example, on Linux or macOS, you can run the following command in your terminal: |
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```bash |
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gunzip it.db.gz |
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``` |
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This will create the decompressed database file (`it.db` in the example above). |
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3. **Install Wikilite**: Follow the instructions on the [Wikilite github repo](https://github.com/eja/wikilite) to clone the repository and build the binary, or download a precompiled binary for your OS from [Wikilite Releases](https://github.com/eja/wikilite/releases/latest). |
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4. **Run Wikilite:** Navigate to the directory where you extracted the database and where you have the compiled `wikilite` binary. Use the `wikilite` command with the appropriate options. For example, to start the web interface for the Italian database, use: |
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```bash |
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./wikilite --db it.db --web |
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``` |
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This will start a local web server allowing you to browse and search the Wikipedia content. |
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**Command-line Usage:** Alternatively, you can search the database directly from the command line: |
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```bash |
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./wikilite --db it.db --cli |
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``` |
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5. **Access the Web Interface:** If you started the web server, open a web browser and navigate to `http://localhost:35248` to access the web interface. |
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## About Wikilite |
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[Wikilite](https://github.com/eja/wikilite) is a tool that provides offline access to Wikipedia content, featuring: |
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* **Fast and Flexible Lexical Searching:** Uses FTS5 (Full-Text Search 5) for efficient keyword-based searching. |
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* **Enhanced Semantic Search:** Integrates semantic search capabilities, allowing you to find information based on meaning rather than just keywords. |
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* **Offline Access:** Enables access to Wikipedia articles without an internet connection. |
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* **Command-Line Interface (CLI):** Allows direct searching from the terminal. |
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* **Web Interface (Optional):** Provides a user-friendly way to browse and search content. |
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### Semantic Search Details |
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Wikilite leverages text embeddings for its optional semantic search. This allows you to find results even if your query does not match keywords directly, handling cases like: |
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* Typos in your search query. |
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* Different wordings to express the same concept. |
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* The article uses synonyms or related terms. |
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**Note:** To enable semantic search, you'll need a local GGUF model or an OpenAI-compatible remote server and configure Wikilite accordingly. See the Wikilite GitHub repository for more details. |
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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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* [Ollama](https://ollama.ai) For enabling the internal generation of embeddings. |
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* [Wikilite](https://github.com/eja/wikilite): For making this project possible. |
