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----
-title: Arabic Book Analysis AI
-emoji: 📚
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 5.27.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-# Arabic Book Analysis AI
-
-This Huggingface Space hosts an AI system that analyzes Arabic books and answers questions based solely on their content. The system supports uploading books in .docx and .pdf formats, fine-tunes an AraBERT model on the extracted text, and provides answers in Arabic.
-
-## Features
-- Upload multiple books (.docx, .pdf).
-- Visual training progress with detailed logs: "Loading book", "Extracting ideas", "Training in progress", "Training completed".
-- Question-answering interface in Arabic, restricted to book content.
-- Separate tab for question-answering only, shareable with friends.
-- Formal answer style, suitable for scholarly texts.
-
-## Configuration
-To ensure proper deployment on Huggingface Spaces, configure the Space with the following settings:
-- **SDK**: Gradio (specified in the YAML front matter above)
-- **SDK Version**: 4.31.0 (matches `requirements.txt`)
-- **App File**: `app.py` (entry point for the Gradio app)
-- **Visibility**: Public (required for sharing the question-answering link)
-- **Hardware**: CPU (default free tier is sufficient; upgrade to GPU for faster training if needed)
-- **File Structure**:
-  - Place `app.py`, `requirements.txt`, and `README.md` in the root directory (`/`).
-  - No additional folders are required; the app expects all files at the root level.
-- **Environment Variables**: None required; all dependencies are listed in `requirements.txt`.
-- **Persistence**: The fine-tuned model is saved to `./fine_tuned_model` within the Space’s storage for reuse.
-- **Huggingface Space Name**: Use `arabic-book-analysis` for consistency with the provided links.
-
-## How to Use
-### Training and Question Interface
-1. **Upload Books**:
-   - Access the main interface at `/` and select the "التدريب والسؤال" tab.
-   - Click the "رفع الكتب" field to select .docx or .pdf files.
-   - Press "رفع وتدريب" to start processing and training.
-   - View uploaded files, training logs, and status.
-   - After training, see the message: "Training process finished: Enter your question".
-
-2. **Ask Questions**:
-   - In the same tab, enter an Arabic question in the "أدخل سؤالك بالعربية" field.
-   - Click "طرح السؤال" to get an answer based on the book’s content.
-
-### Question-Answering Only Interface
-- Share the main link with friends: `https://huggingface.co/spaces/your_huggingface_username/arabic-book-analysis`
-- Users can:
-  - Select the "طرح الأسئلة فقط" tab.
-  - Enter an Arabic question in the provided field.
-  - Receive answers based on the trained model’s knowledge.
-  - No training required.
-
-3. **Example**:
-   - Question: "ما هو قانون الإيمان وفقًا للكتاب؟"
-   - Answer: "قانون الإيمان هو أساس العقيدة المسيحية، ويؤمن به كل الكنائس المسيحية في العالم..."
-
-## Requirements
-- Python 3.8+
-- Dependencies listed in `requirements.txt`
-
-## Deployment
-1. **Create/Update Huggingface Space**:
-   - Log in to Huggingface with your username (replace `your_huggingface_username`).
-   - Create a new Space named "arabic-book-analysis" or update an existing one.
-   - Select "Gradio" as the SDK and set visibility to "Public".
-
-2. **Upload Zipped Folder**:
-   - Run the provided `create_zip.py` script to generate `arabic_book_analysis.zip`.
-   - In the Huggingface Space, go to the "Files" tab.
-   - Upload `arabic_book_analysis.zip` and extract it.
-   - Move `app.py`, `requirements.txt`, and `README.md` from `/arabic_book_analysis/` to the root directory (`/`).
-   - Ensure these files are in the root.
-
-3. **Build and Launch**:
-   - Huggingface Spaces will automatically install dependencies from `requirements.txt` and launch the app.
-   - Monitor build logs for errors.
-
-4. **Access Links**:
-   - Main interface (both tabs): `https://huggingface.co/spaces/your_huggingface_username/arabic-book-analysis`
-
-## Troubleshooting Configuration and Runtime Errors
-- **Error: "Invalid SDK"**:
-  - Ensure the Space is configured to use the Gradio SDK in the Space settings and the YAML front matter specifies `sdk: gradio`.
-- **Error: "Files not found"**:
-  - Verify that `app.py`, `requirements.txt`, and `README.md` are in the root directory (`/`), not in subfolders.
-  - Re-upload `arabic_book_analysis.zip`, extract it, and move files to the root using the Huggingface UI.
-- **Error: "Dependency installation failed"**:
-  - Check `requirements.txt` for correct package versions.
-  - Review build logs in the Space’s "Settings" tab for specific errors.
-- **Error: "Private Space access denied"**:
-  - Set the Space visibility to "Public" to enable the question-answering tab for friends.
-- **Error: "Model not found"**:
-  - Ensure training is completed at least once to save the fine-tuned model to `./fine_tuned_model`.
-- **Error: "FileNotFoundError: No such file or directory: 'java'"**:
-  - The `arabert` library’s Farasa dependency requires Java, which is not installed by default. This project uses a custom `preprocess_arabic_text` function in `app.py` to avoid Farasa and Java requirements. If this error occurs, ensure `app.py` uses `preprocess_arabic_text` instead of `ArabertPreprocessor`.
-- **Error: "TypeError: ArabertPreprocessor.__init__() got an unexpected keyword argument 'use_farasapy'"**:
-  - This occurred because `arabert==1.0.1` does not support the `use_farasapy` parameter. The current `app.py` avoids `ArabertPreprocessor` entirely, using a custom preprocessing function.
-- **Error: "FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0"**:
-  - This warning from `huggingface_hub` (used by `transformers`) may cause the container to exit if warnings are treated as errors. The current `app.py` suppresses this warning using a `warnings.filterwarnings` directive. If the error persists, check build logs for additional issues during model/tokenizer loading.
-- **Error: "TypeError: App.create_app() missing 1 required positional argument: 'blocks'"**:
-  - This occurred due to incorrect Gradio app setup in `app.py`. The current `app.py` uses a single `gr.Blocks` app with tabs, launched directly with `demo.launch()`, avoiding manual app mounting.
-- **Warning: "Some weights of BertForQuestionAnswering were not initialized"**:
-  - This warning appears when loading `aubmindlab/bert-base-arabertv2` for question-answering, as the model is not pre-fine-tuned for this task. It is expected and harmless, as the model will be fine-tuned during training. Ensure training is completed to initialize these weights.
-
-## Notes
-- Ensure books are in Arabic for accurate processing.
-- The system is optimized for Huggingface Spaces’ free tier; training may take a few minutes.
-- Replace `your_huggingface_username` with your actual Huggingface username.
-- Training logs are displayed in the interface for transparency.
-- The zipped folder simplifies uploads; ensure files are moved to the root directory after extraction.
-- The `arabert` library’s Farasa dependency is bypassed using a custom `preprocess_arabic_text` function to avoid Java requirements. This may slightly reduce preprocessing capabilities but ensures compatibility with Huggingface Spaces.
-- The `huggingface_hub` warning is suppressed in `app.py`. Future updates to `transformers` may resolve this when `huggingface_hub>=1.0.0` is released.
-- The model weights warning is normal and does not affect functionality after training.
-
-## License
-MIT License