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# ChatbotRAG - Complete Summary
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## Tổng Quan Hệ Thống
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Hệ thống ChatbotRAG hiện đã được nâng cấp toàn diện với các tính năng advanced:
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### ✨ Tính Năng Chính
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1. **Multiple Inputs Support** (/index)
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- Index tối đa 10 texts + 10 images cùng lúc
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- Average embeddings tự động
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2. **Advanced RAG Pipeline** (/chat)
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- Query Expansion
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- Multi-Query Retrieval
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- Reranking with semantic similarity
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- Contextual Compression
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- Better Prompt Engineering
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3. **PDF Support** (/upload-pdf)
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- Parse PDF thành chunks
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- Auto chunking với overlap
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- Index vào RAG system
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4. **Multimodal PDF** (/upload-pdf-multimodal) ⭐ NEW
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- Extract text + image URLs từ PDF
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- Link images với text chunks
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- Return images cùng text trong chat
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- Perfect cho user guides với screenshots
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---
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## Kiến Trúc Hệ Thống
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```
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┌─────────────────────────────────────────────────────────────┐
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│ FastAPI Application │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ Indexing │ │ Search │ │ Chat │ │
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│ │ Endpoints │ │ Endpoints │ │ Endpoint │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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│ │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────────────────────────────────────────────┐ │
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│ │ Advanced RAG Pipeline │ │
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│ │ • Query Expansion │ │
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│ │ • Multi-Query Retrieval │ │
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│ │ • Reranking │ │
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│ │ • Contextual Compression │ │
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│ └──────────────────────────────────────────────────────┘ │
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│ │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ Jina CLIP │ │ Qdrant │ │ MongoDB │ │
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│ │ v2 │ │ Vector DB │ │ Documents │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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│ │
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│ ┌──────────────┐ ┌──────────────┐ │
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│ │ PDF │ │ Multimodal │ │
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│ │ Parser │ │ PDF Parser │ │
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│ └──────────────┘ └──────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────┘
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```
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---
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## Files Quan Trọng
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### Core System
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- **main.py** - FastAPI application với tất cả endpoints
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- **embedding_service.py** - Jina CLIP v2 embedding
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- **qdrant_service.py** - Qdrant vector DB operations
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- **advanced_rag.py** - Advanced RAG pipeline
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### PDF Processing
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- **pdf_parser.py** - Basic PDF parser (text only)
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- **multimodal_pdf_parser.py** - Multimodal PDF parser (text + images)
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- **batch_index_pdfs.py** - Batch indexing script
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### Documentation
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- **ADVANCED_RAG_GUIDE.md** - Advanced RAG features guide
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- **PDF_RAG_GUIDE.md** - PDF usage guide
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- **MULTIMODAL_PDF_GUIDE.md** - Multimodal PDF guide ⭐
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- **QUICK_START_PDF.md** - Quick start for PDF
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- **chatbot_guide_template.md** - Template for user guide PDF
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### Testing
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- **test_advanced_features.py** - Test advanced features
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- **test_pdf_chatbot.py** - Test PDF chatbot (example in docs)
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---
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## API Endpoints
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### 1. Indexing
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| Endpoint | Method | Description |
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|----------|--------|-------------|
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| `/index` | POST | Index texts + images (max 10 each) |
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| `/documents` | POST | Add text document |
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| `/upload-pdf` | POST | Upload PDF (text only) |
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| `/upload-pdf-multimodal` | POST | Upload PDF with images ⭐ |
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### 2. Search
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| Endpoint | Method | Description |
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|----------|--------|-------------|
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| `/search` | POST | Hybrid search (text + image) |
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| `/search/text` | POST | Text-only search |
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| `/search/image` | POST | Image-only search |
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| `/rag/search` | POST | RAG knowledge base search |
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### 3. Chat
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| Endpoint | Method | Description |
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|----------|--------|-------------|
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| `/chat` | POST | Chat with Advanced RAG |
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### 4. Management
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| Endpoint | Method | Description |
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|----------|--------|-------------|
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| `/documents/pdf` | GET | List all PDFs |
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| `/documents/pdf/{id}` | DELETE | Delete PDF document |
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| `/delete/{doc_id}` | DELETE | Delete document |
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| `/document/{doc_id}` | GET | Get document by ID |
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| `/history` | GET | Get chat history |
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| `/stats` | GET | Collection statistics |
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| `/` | GET | Health check + API docs |
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---
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## Use Cases & Recommendations
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### Case 1: PDF Hướng Dẫn Chỉ Có Text
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**Scenario:** FAQ, policy document, text guide
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**Solution:** `/upload-pdf`
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```bash
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curl -X POST "http://localhost:8000/upload-pdf" \
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-F "file=@faq.pdf" \
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-F "title=FAQ"
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```
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### Case 2: PDF Hướng Dẫn Có Hình Ảnh ⭐ (Your Case)
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**Scenario:** User guide với screenshots, tutorial với diagrams
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**Solution:** `/upload-pdf-multimodal`
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```bash
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curl -X POST "http://localhost:8000/upload-pdf-multimodal" \
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-F "file=@user_guide_with_images.pdf" \
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-F "title=User Guide" \
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-F "category=guide"
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```
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**Benefits:**
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- ✓ Extract text + image URLs
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- ✓ Link images với text chunks
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- ✓ Chatbot return images in response
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- ✓ Visual context for users
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### Case 3: Multiple Social Media Posts
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**Scenario:** Index nhiều posts với texts và images
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**Solution:** `/index` with multiple inputs
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```python
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data = {
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'id': 'post123',
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'texts': ['Post text 1', 'Post text 2', ...], # Max 10
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}
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files = [
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('images', open('img1.jpg', 'rb')),
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('images', open('img2.jpg', 'rb')), # Max 10
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]
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requests.post('http://localhost:8000/index', data=data, files=files)
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```
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### Case 4: Complex Queries
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**Scenario:** Câu hỏi phức tạp, cần độ chính xác cao
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**Solution:** Advanced RAG with full options
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```python
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{
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'message': 'Complex question',
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'use_rag': True,
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'use_advanced_rag': True,
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'use_reranking': True,
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'use_compression': True,
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'score_threshold': 0.5,
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'top_k': 5
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}
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```
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---
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## Workflow Đề Xuất Cho Bạn
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### Setup Ban Đầu
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1. **Tạo PDF hướng dẫn sử dụng**
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- Dùng template: `chatbot_guide_template.md`
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- Customize nội dung cho hệ thống của bạn
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- Thêm image URLs (screenshots, diagrams)
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- Convert to PDF: `pandoc template.md -o guide.pdf`
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2. **Upload PDF**
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```bash
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curl -X POST "http://localhost:8000/upload-pdf-multimodal" \
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-F "file=@chatbot_user_guide.pdf" \
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-F "title=Hướng dẫn sử dụng ChatbotRAG" \
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-F "category=user_guide"
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```
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3. **Verify**
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```bash
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curl http://localhost:8000/documents/pdf
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# Check "type": "multimodal_pdf" và "total_images"
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```
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### Sử Dụng Hàng Ngày
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1. **Chat với user**
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```python
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response = requests.post('http://localhost:8000/chat', json={
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'message': user_question,
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'use_rag': True,
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'use_advanced_rag': True,
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'hf_token': 'your_token'
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})
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```
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2. **Display response + images**
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```python
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# Text answer
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print(response.json()['response'])
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# Images (if any)
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for ctx in response.json()['context_used']:
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if ctx['metadata'].get('has_images'):
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for url in ctx['metadata']['image_urls']:
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# Display image in your UI
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print(f"Image: {url}")
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```
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### Cập Nhật Content
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1. **Update PDF** - Edit và re-export
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2. **Xóa PDF cũ**
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```bash
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curl -X DELETE http://localhost:8000/documents/pdf/old_doc_id
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```
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3. **Upload PDF mới**
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```bash
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curl -X POST http://localhost:8000/upload-pdf-multimodal -F "file=@new_guide.pdf"
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```
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---
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## Performance Tips
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### 1. Chunking
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**Default:**
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- chunk_size: 500 words
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- chunk_overlap: 50 words
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**Tối ưu:**
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```python
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# In multimodal_pdf_parser.py
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parser = MultimodalPDFParser(
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chunk_size=400, # Shorter for faster retrieval
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chunk_overlap=40,
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min_chunk_size=50
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)
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```
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### 2. Retrieval
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**Settings tốt:**
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```python
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{
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'top_k': 5, # 3-7 is optimal
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'score_threshold': 0.5, # 0.4-0.6 is good
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'use_reranking': True, # Always enable
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'use_compression': True # Keeps context relevant
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}
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```
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### 3. LLM
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**For factual answers:**
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```python
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{
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'temperature': 0.3, # Low for accuracy
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'max_tokens': 512, # Concise answers
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'top_p': 0.9
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}
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```
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---
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## Troubleshooting
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### Issue 1: Images không được detect
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**Solution:**
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- Verify PDF có image URLs (http://, https://)
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- Check format: markdown `` hoặc HTML `<img src>`
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- Test regex:
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```python
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from multimodal_pdf_parser import MultimodalPDFParser
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parser = MultimodalPDFParser()
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urls = parser.extract_image_urls("")
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print(urls) # Should return ['https://example.com/img.png']
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```
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### Issue 2: Chatbot không tìm thấy thông tin
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**Solution:**
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- Lower score_threshold: `0.3-0.5`
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- Increase top_k: `5-10`
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- Enable Advanced RAG
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- Rephrase question
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### Issue 3: Response quá chậm
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**Solution:**
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- Giảm top_k
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- Disable compression nếu không cần
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- Use basic RAG thay vì advanced for simple queries
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---
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## Next Steps
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### Immediate (Bây Giờ)
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1. ✓ System đã ready!
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2. Tạo PDF hướng dẫn của bạn
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3. Upload qua `/upload-pdf-multimodal`
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4. Test với câu hỏi thực tế
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### Short Term (1-2 tuần)
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1. Collect user feedback
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2. Fine-tune parameters (top_k, threshold)
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3. Add more PDFs (FAQ, tutorials, etc.)
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4. Monitor chat history để improve content
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### Long Term (Sau này)
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1. **Hybrid Search với BM25**
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- Combine dense + sparse retrieval
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- Better for keyword queries
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2. **Cross-Encoder Reranking**
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- Replace embedding similarity
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- More accurate ranking
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3. **Image Processing**
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- Download và process actual images
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- Use Jina CLIP for image embeddings
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- True multimodal embeddings (text + image vectors)
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4. **RAG-Anything Integration** (Nếu cần)
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- For complex PDFs with tables, charts
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- Vision encoder for embedded images
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- Advanced document understanding
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---
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## Comparison Matrix
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| Approach | Text | Images | URLs | Complexity | Your Case |
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|----------|------|--------|------|------------|-----------|
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| Basic RAG | ✓ | ✗ | ✗ | Low | ✗ |
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| PDF Parser | ✓ | ✗ | ✗ | Low | ✗ |
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| **Multimodal PDF** | ✓ | ✗ | ✓ | **Medium** | **✓** |
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| RAG-Anything | ✓ | ✓ | ✓ | High | Overkill |
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**Recommendation:** **Multimodal PDF** là perfect cho case của bạn!
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---
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## Kết Luận
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### Bạn Có Gì?
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✅ **Multiple Inputs**: Index 10 texts + 10 images
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✅ **Advanced RAG**: Query expansion, reranking, compression
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✅ **PDF Support**: Parse và index PDFs
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✅ **Multimodal PDF**: Extract text + image URLs, link together
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✅ **Complete Documentation**: Guides, examples, troubleshooting
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### Làm Gì Tiếp?
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1. **Tạo PDF** hướng dẫn với nội dung của bạn (có image URLs)
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2. **Upload** qua `/upload-pdf-multimodal`
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3. **Test** với câu hỏi thực tế
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4. **Iterate** - fine-tune based on feedback
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### Files Cần Đọc
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**Cho PDF với hình ảnh (Your case):**
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- [MULTIMODAL_PDF_GUIDE.md](MULTIMODAL_PDF_GUIDE.md) ⭐⭐⭐
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- [PDF_RAG_GUIDE.md](PDF_RAG_GUIDE.md)
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**Cho Advanced RAG:**
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- [ADVANCED_RAG_GUIDE.md](ADVANCED_RAG_GUIDE.md)
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**Quick Start:**
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- [QUICK_START_PDF.md](QUICK_START_PDF.md)
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---
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**Hệ thống của bạn bây giờ rất mạnh! Chỉ cần upload PDF và chat thôi! 🚀📄🤖**
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