Update README.md

README.md

@@ -35,62 +35,72 @@ More languages may be added in the future.
 
 ## Dataset Structure
 
-Each language is stored as a separate compressed file (`.db.gz`) within the dataset. For example:
-
-*   `it.db.gz` - Italian Wikipedia database (lexical only)
-*   `sc.all-mini.db.gz` - Sardinian Wikipedia database (lexical and semantic)
+Each language is stored as a separate compressed file (`.db.gz`). There are two types of databases available:
 
+1.  **Lexical Only**: Located in the `lexical/` directory. These support standard FTS5 full-text search (exact word matching) and are lighter in size.
+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.
 
 ## How to Use This Dataset
 
-1. **Install Wikilite**  
-   Download a precompiled binary for your operating system from the [Wikilite Releases](https://github.com/eja/wikilite/releases/latest) page. Once downloaded, uncompress the binary.
+### 1. Command Line & Web Interface (Linux, macOS, Windows, Termux)
 
-2. **Run the `--setup` Command**  
-   Execute the binary with the `--setup` option to install a pre-built database. This command will display a list of available databases, allowing you to select and download the one you need, along with the corresponding GGUF model. For example:  
+Wikilite runs primarily as a command-line tool that can also serve a local web interface.
 
-   ```bash
-   ./wikilite --setup
-   ```
+1.  **Install Wikilite**  
+    Download the precompiled binary for your operating system from the [Wikilite Releases](https://github.com/eja/wikilite/releases/latest) page and extract it.
 
-   Note: Databases in the "lexical" folder are for full-text search only and do not support semantic search.
+2.  **Download a Database**  
+    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:
+    
+    *   **Interactive Wizard:** Run `./wikilite` without arguments to launch a wizard that guides you through selecting and downloading a database.
+    *   **Setup Command:** Run `./wikilite --setup` to view and download available databases automatically.
 
-3. **Run Wikilite with the Installed Database**  
-   After completing the setup, navigate to the directory containing the `wikilite` binary. Use the following commands to run Wikilite:  
+3.  **Run Wikilite**  
+    Once you have a database file (e.g., `wikilite.db`), you can use it in three ways:
 
-   - **To start the web interface** for browsing and searching:  
-     ```bash
-     ./wikilite --web
-     ```  
+    *   **Interactive Mode:**  
+        ```bash
+        ./wikilite
+        ```
+        (Follow the on-screen prompts)
 
-   - **To search via the command line**:  
-     ```bash
-     ./wikilite --cli
-     ```  
+    *   **Command Line Search:**  
+        ```bash
+        ./wikilite --cli --db <file.db>
+        ```
 
-4. **Access the Web Interface**  
-   If you started the web server using the `--web` option, open your browser and go to `http://localhost:35248` to access the web interface for browsing and searching the Wikipedia content.
+    *   **Web Interface:**  
+        ```bash
+        ./wikilite --web --db <file.db>
+        ```
+        Access the interface at `http://localhost:35248` in your browser.
 
+### 2. Android Application
 
-## About Wikilite
+A native Android application is available that uses these exact databases.
 
-[Wikilite](https://github.com/eja/wikilite) is a tool that provides offline access to Wikipedia content, featuring:
+1.  Download the [Android App APK](https://github.com/eja/wikilite/releases/latest/download/wikilite-android.apk).
+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.
+3.  **In-App Download:** If no database is found on launch, the app provides an option to download these pre-built databases directly.
 
-*   **Fast and Flexible Lexical Searching:** Uses FTS5 (Full-Text Search 5) for efficient keyword-based searching.
-*   **Enhanced Semantic Search:** Integrates semantic search capabilities, allowing you to find information based on meaning rather than just keywords.
-*   **Offline Access:** Enables access to Wikipedia articles without an internet connection.
-*   **Command-Line Interface (CLI):** Allows direct searching from the terminal.
-*   **Web Interface (Optional):** Provides a user-friendly way to browse and search content.
+## About Wikilite
 
-### Semantic Search Details
+[Wikilite](https://github.com/eja/wikilite) is a self-contained tool for creating and browsing local SQLite databases of Wikipedia articles.
 
-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:
+### Features
+*   **Lexical Search:** Uses FTS5 for efficient, exact keyword matching.
+*   **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.
+*   **Offline Operation:** Complete functionality without internet connectivity.
+*   **Cross-Platform:** Available for Linux, macOS, Windows, Termux, and Android.
 
-*   Typos in your search query.
-*   Different wordings to express the same concept.
-*   The article uses synonyms or related terms.
+### Semantic Search Capabilities
+The semantic search functionality employs text embeddings to handle:
+*   Query misspellings and typographical errors.
+*   Conceptual similarity despite different terminology.
+*   Synonym and related term matching.
+*   Morphological variations (plurals, verb tenses).
 
-**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.
+*Note: The semantic databases in this repository are fully self-contained. No external model files or API keys are required.*
 
 ## Contributing
 
@@ -100,5 +110,5 @@ If you would like to contribute databases for additional languages, please feel
 
 *   [Wikipedia](https://www.wikipedia.org/): For providing the valuable data.
 *   [SQLite](https://www.sqlite.org/): For the robust database engine.
-*   [LLaMA.cpp](https://github.com/ggml-org/llama.cpp) For enabling the internal generation of embeddings.
-*   [Wikilite](https://github.com/eja/wikilite): For making this project possible.
+*   [LLaMA.cpp](https://github.com/ggml-org/llama.cpp): For enabling the internal generation of embeddings.
+*   [Wikilite](https://github.com/eja/wikilite): For the software powering these datasets.