# Presentation Process

This is the simple version you can use when presenting the project.

## One-Sentence Summary

Our system helps Hong Kong elderly users check suspicious messages or screenshots by comparing them with real scraped fraud-news cases and giving clear safety advice.

The app supports Traditional Chinese, Simplified Chinese, and English. In the web app, the answer language follows the selected interface/output language. If an API client omits the language or sends `auto`, the backend detects the suspicious message language; Traditional Chinese remains the default for Hong Kong Cantonese-style messages.

## The Process

### 1. Collect Fraud News

We scrape Hong Kong fraud-related news articles and store the case details.

Think of this as building a small local fraud case library.

### 2. Convert Cases Into Searchable Vectors

Each case is converted into a numerical representation called an embedding.

For presentation, you can say:

> We turn each news case into a searchable fingerprint, so similar scam patterns can be found quickly.

### 3. User Enters A Suspicious Message

The user can:

- paste a suspicious SMS, WhatsApp message, or email
- upload a screenshot

If the user uploads a screenshot, Qwen OCR first reads the text from the image.

### 4. Search Similar Cases

The user message is also converted into an embedding.

The system searches the Chroma vector database and retrieves the most similar fraud cases.

Example:

- user message says parcel delivery fee
- system retrieves similar parcel-delivery scam cases
- user message says investment return
- system retrieves similar investment scam cases

### 5. Qwen Explains The Risk

Qwen receives:

- the user message
- the retrieved similar cases
- strict elderly-friendly safety rules

It then gives:

- a fraud score from 0-10
- What Happened
- Red Flags
- What To Do
- the answer in Traditional Chinese, Simplified Chinese, or English based on the selected output language, with auto detection only when no language is selected

### 6. Safety Advice For Hong Kong

The answer always reminds users that if they feel suspicious, they should call:

**ADCC Anti-Deception Coordination Centre: 18222**

## Why This Is Useful For Elderly Users

- They do not need to understand technical terms.
- They can upload screenshots instead of typing everything.
- The answer is short and clear.
- It gives immediate actions, not just a warning.
- It uses Hong Kong-specific fraud cases and Hong Kong help resources.

## Presentation Demonstration Script

1. Open the app.
2. Paste a suspicious message, for example a fake parcel fee message.
3. Click **檢查風險**.
4. Show the score.
5. Show the similar cases retrieved from the vector database.
6. Explain the three safety sections:
   - What Happened
   - Red Flags
   - What To Do
7. Point out the ADCC 18222 reminder.

## Technical Architecture

```mermaid
flowchart LR
    A["User message or screenshot"] --> B["Frontend"]
    B --> C["FastAPI backend"]
    C --> D["Qwen OCR if screenshot"]
    C --> E["Embedding model"]
    E --> F["Chroma vector database"]
    F --> G["Similar fraud cases"]
    G --> H["Qwen risk explanation"]
    H --> I["Elderly-friendly result"]
```

## Key Point To Say

The AI does not answer from memory only. It first retrieves similar cases from our embedded fraud-news database, then uses those cases to explain the risk safely and simply.