Update README.md

README.md

@@ -25,14 +25,14 @@ configs:
 ---
 # HVU_QA
 
-**HVU_QA** is an open-source Vietnamese Question–Context–Answer (QCA) corpus, accompanied by supporting tools, created to facilitate the development of FAQ-style question generation and question answering systems, particularly for low-resource language settings. The dataset is developed by a research team at Hung Vuong University, Phu Tho, Vietnam, led by Dr. Ha Nguyen, Deputy Head of the Department of Engineering Technology. HVU_QA was constructed using a fully automated data-building pipeline that combines web crawling from reliable sources, semantic tag-based extraction, and AI-assisted filtering, helping ensure high factual accuracy, consistent structure, and practical usability for real-world applications.
+**HVU_QA** is an open-source Vietnamese Question-Context-Answer (QCA) corpus, accompanied by supporting tools, created to facilitate the development of FAQ-style question generation and question answering systems, particularly for low-resource language settings. The dataset was developed by a research team at Hung Vuong University, Phu Tho, Vietnam, led by Dr. Ha Nguyen, Deputy Head of the Department of Engineering Technology. HVU_QA was constructed using a fully automated data-building pipeline that combines web crawling from reliable sources, semantic tag-based extraction, and AI-assisted filtering, helping ensure high factual accuracy, consistent structure, and practical usability for real-world applications.
 
 ## 📋 Dataset Description
 
 - **Language:** Vietnamese
 - **Format:** SQuAD-style JSON
 - **Total samples:** 40,000 QCA triples (full corpus released)
-- **Domains covered:** Social services, labor law, administrative processes, and other public service topics.
+- **Domains covered:** Social services, labor law, administrative processes, and other public service topics
 - **Structure of each sample:**
   - **Question:** Generated or extracted question
   - **Context:** Supporting text passage from which the answer is derived
@@ -41,56 +41,131 @@ configs:
 ## ⚙️ Creation Pipeline
 
 The dataset was built using a 4-stage automated process:
+
 1. **Selecting relevant QA websites** from trusted sources.
 2. **Automated data crawling** to collect raw QA webpages.
-3. **Extraction via semantic tags** to obtain clean Question–Context–Answer triples.
+3. **Extraction via semantic tags** to obtain clean Question-Context-Answer triples.
 4. **AI-assisted filtering** to remove noisy or factually inconsistent samples.
 
 ## 📊 Quality Evaluation
-A fine-tuned `vit5-base` model trained on HVU_QA achieved:
 
-| Metric                 | Score           |
-|-------------------------|----------------|
-| BLEU                    | 89.1           |
-| Semantic similarity     | 91.5% (cos ≥ 0.8) |
-| Human grammar score     | 4.58 / 5         |
-| Human usefulness score  | 4.29 / 5         |
+A fine-tuned `VietAI/vit5-base` model trained on HVU_QA achieved:
+
+| Metric                 | Score            |
+|------------------------|------------------|
+| BLEU                   | 89.1             |
+| Semantic similarity    | 91.5% (cos >= 0.8) |
+| Human grammar score    | 4.58 / 5         |
+| Human usefulness score | 4.29 / 5         |
 
 These results confirm that HVU_QA is a high-quality resource for developing robust FAQ-style question generation models.
 
-## 📁 Dataset Structure
-```
-.HVU_QA
-├── t5-viet-qg-finetuned/
-├── fine_tune_qg.py
-├── generate_question.py
-├── 40k_train.json
+## 📁 Project Structure
+
+```text
+HVU_QA/
+├── backend/
+│   ├── __init__.py               # Flask app factory
+│   └── app.py                    # Backend API and frontend serving
+├── frontend/
+│   ├── index.html                # Web interface
+│   ├── app.js                    # Frontend logic
+│   └── style.css                 # Frontend styles
+├── t5-viet-qg-finetuned/         # Fine-tuned model folder
+├── 40k_train.json                # Training dataset in SQuAD-style JSON
+├── fine_tune_qg.py               # Model fine-tuning script
+├── generate_question.py          # CLI question generation script
+├── HVU_QA_tool.py                # Standalone launcher and model downloader
+├── main.py                       # Start the local web application
+├── requirements.txt              # Python dependencies
+├── HVU_QA_end_to_end_guide.ipynb # End-to-end usage notebook
 └── README.md
 ```
+
 ## 📁 Vietnamese Question Generation Tool
 
-## 🛠️ Requirements
+## 🛠️ Installation and Setup
+
+This repository supports two common workflows:
+
+1. **Full project mode:** use the complete source code, web interface, backend API, training script, and local model folder.
+2. **Standalone launcher mode:** use only `HVU_QA_tool.py` to automatically prepare a lightweight runtime, install missing dependencies, download the model, and run the app.
+
+### Requirements
+
+* Python 3.10+
+* `pip`
+* Optional: NVIDIA GPU with CUDA for faster inference or training
+
+### Option A. Install and run the full project
+
+Create and activate a virtual environment:
+
+```bash
+python -m venv venv
+```
+
+```bash
+# Windows
+venv\Scripts\activate
+
+# macOS / Linux
+source venv/bin/activate
+```
+
+Install dependencies:
+
+```bash
+python -m pip install --upgrade pip
+python -m pip install -r requirements.txt
+```
+
+`requirements.txt` already includes the main runtime packages such as Flask, Torch, Transformers, Datasets, Accelerate, SentencePiece, Safetensors, NumPy, and Hugging Face Hub.
+
+If you need a CUDA-specific PyTorch build, install the matching version from [pytorch.org](https://pytorch.org) first, then install the remaining dependencies from `requirements.txt`.
+
+Prepare the local model:
+
+```bash
+python HVU_QA_tool.py --skip-run
+```
+
+If `t5-viet-qg-finetuned/` already exists and contains a valid exported model, you can skip this step.
+
+Run the web app:
 
-* Python 3.8+
-* PyTorch >= 1.9
-* Transformers >= 4.30
-* scikit-learn
+```bash
+python main.py
+```
 
-### 📦 Install Required Libraries
+Then open `http://127.0.0.1:5000` in your browser.
+
+### Option B. Use the standalone launcher only
+
+If you only have `HVU_QA_tool.py` in an empty folder, run:
 
 ```bash
-pip install datasets transformers sentencepiece safetensors accelerate evaluate sacrebleu rouge-score nltk scikit-learn
+python HVU_QA_tool.py
 ```
 
-*(Install PyTorch separately from [pytorch.org](https://pytorch.org) if not installed yet.)*
+The launcher will:
+
+1. Detect whether the full project already exists.
+2. Create a standalone runtime if needed.
+3. Create a dedicated virtual environment when necessary.
+4. Install missing runtime dependencies.
+5. Download the model from Hugging Face.
+6. Start the local web app automatically.
+
+### Optional: Load only the dataset from Hugging Face Hub
 
-### 📥 Load Dataset from Hugging Face Hub
 ```python
 from datasets import load_dataset
 
 ds = load_dataset("DANGDOCAO/GeneratingQuestions", split="train")
 print(ds[0])
 ```
+
 ## 📚 Usage
 
 * Train and evaluate a question generation model.
@@ -100,48 +175,50 @@ print(ds[0])
 ### 🔹 Fine-tuning
 
 ```bash
-python fine_tune_qg.py
+python fine_tune_qg.py --train_file 40k_train.json --output_dir t5-viet-qg-finetuned
 ```
 
 This will:
 
-1. Load the dataset from `40k_train.json`.  
-2. Fine-tune `VietAI/vit5-base`.  
-3. Save the trained model into `t5-viet-qg-finetuned/`.  
-
-*(Or download the pre-trained model: [t5-viet-qg-finetuned](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions/tree/main).)*
+1. Load the dataset from `40k_train.json`.
+2. Fine-tune `VietAI/vit5-base`.
+3. Save the trained model into `t5-viet-qg-finetuned/`.
+4. Export the best or final model to a folder such as `best-model/` or `final-model/`.
 
 ### 🔹 Generating Questions
+
 ```bash
-python generate_question.py
+python generate_question.py --text "Cà phê sữa đá là một loại đồ uống nổi tiếng ở Việt Nam." --num_questions 5
+
+**Example output:**
+
+```text
+1. Loại cà phê nào nổi tiếng ở Việt Nam?
+   (Which type of coffee is famous in Vietnam?)
+2. Cà phê sữa đá là loại đồ uống nổi tiếng ở đâu?
+   (Where is iced milk coffee a famous drink?)
+3. Vì sao cà phê sữa đá được nhiều người biết đến?
+   (Why is iced milk coffee well known?)
+4. Đồ uống nào là đặc trưng nổi tiếng ở Việt Nam?
+   (Which beverage is a famous specialty in Vietnam?)
+5. Cà phê sữa đá thường được nhắc đến như thế nào?
+   (How is iced milk coffee commonly described?)
 ```
 
-**Example:**
-```
-Input passage:
-Cà phê sữa đá là một loại đồ uống nổi tiếng ở Việt Nam
-(Iced milk coffee is a famous drink in Vietnam)
+**Common CLI options in `generate_question.py`:**
 
-Number of questions: 5
-```
-**Output:**
-```
-1. Loại cà phê nào nổi tiếng ở Việt Nam?  
-   (What type of coffee is famous in Vietnam?)  
-2. Tại sao cà phê sữa đá lại phổ biến?  
-   (Why is iced milk coffee popular?)  
-3. Cà phê sữa đá bao gồm những nguyên liệu gì?  
-   (What ingredients are included in iced milk coffee?)  
-4. Cà phê sữa đá có nguồn gốc từ đâu?  
-   (Where does iced milk coffee originate from?)  
-5. Cà phê sữa đá Việt Nam được pha chế như thế nào?  
-   (How is Vietnamese iced milk coffee prepared?)  
-```
-**You can adjust** in `generate_question.py`:
-
-- `top_k`, `top_p`, `temperature`, `no_repeat_ngram_size`, `repetition_penalty`
+- `--model_dir`
+- `--task_prefix`
+- `--num_questions`
+- `--device auto|cpu|cuda`
+- `--cpu_threads`
+- `--gpu_dtype auto|float16|bfloat16|float32`
+- `--max_source_length`
+- `--max_new_tokens`
+- `--output_format text|json`
 
 ## 📌 Citation
+
 If you use **HVU_QA** in your research, please cite:
 
 ```bibtex
@@ -156,12 +233,14 @@ If you use **HVU_QA** in your research, please cite:
   note      = {To appear}
 }
 ```
+
 ## ❤️ Support / Funding
 
 If you find **HVU_QA** useful, please consider supporting our work.  
 Your contributions help us maintain the dataset, improve quality, and release new versions (cleaning, expansion, benchmarks, and tools).
 
 ### 🇻🇳 Donate via VietQR (scan to support)
+
 This **VietQR / NAPAS 247** code can be scanned by Vietnamese banking apps and some international payment apps that support QR bank transfers.
 
 <img src="QRtk.jpg" alt="VietQR Support" width="320"/>
@@ -172,21 +251,28 @@ This **VietQR / NAPAS 247** code can be scanned by Vietnamese banking apps and s
 **Branch:** VietinBank CN PHU THO - HOI SO  
 
 ### 🌍 International Support (Quick card payment)
+
 If you are outside Vietnam, you can support this project via **Buy Me a Coffee**  
-(no PayPal account needed — pay directly with a credit/debit card):
+(no PayPal account needed; pay directly with a credit/debit card):
+
 - BuyMeACoffee: https://buymeacoffee.com/hanguyen0408
 
 ### 🌍 International Support (PayPal)
+
 If you prefer PayPal, you can also support us here:
+
 - PayPal.me: https://paypal.me/HaNguyen0408
 
 ### ✨ Other ways to support
-- ⭐ Star this repository / dataset on Hugging Face  
-- 📌 Cite our paper if you use it in your research  
-- 🐛 Open issues / pull requests to improve the dataset and tools
-- 
-📬 Contact / Maintainers
+
+- Star this repository / dataset on Hugging Face
+- Cite our paper if you use it in your research
+- Open issues / pull requests to improve the dataset and tools
+
+## 📬 Contact / Maintainers
+
 For questions, feedback, collaborations, or issue reports related to HVU_QA, please contact:
-Dr. Ha Nguyen (Project Lead)
-Hung Vuong University, Phu Tho, Vietnam
-Email: nguyentienha@hvu.edu.vn
+
+Dr. Ha Nguyen (Project Lead)  
+Hung Vuong University, Phu Tho, Vietnam  
+Email: nguyentienha@hvu.edu.vn