# 🎯 New Features Added to Active Reading Demo

## 📂 **Category Selection Feature**

### What It Does
Users can now manually select or override the document category detection:

**Available Categories:**
- **Auto-Detect** (default) - AI detects domain automatically
- **Finance** - Financial reports, earnings, budgets
- **Legal** - Contracts, agreements, policies  
- **Technical** - API docs, manuals, specifications
- **Medical** - Clinical trials, research, treatments
- **General** - Any other document type

### Category-Specific Extraction Patterns

#### 📊 Finance Category
- **Revenue**: `$150 million revenue`, `sales of $2.5B`
- **Profit**: `profit margin 25%`, `net profit $50M`
- **Growth**: `15% growth`, `increased by 20%`
- **Dates**: `Q3 2024`, `fiscal year 2023`
- **Employees**: `hire 200 engineers`, `workforce of 5000`
- **Market Cap**: `market cap $10B`

#### ⚖️ Legal Category  
- **Parties**: `between Company A and Company B`
- **Terms**: `term of 36 months`, `duration 3 years`
- **Liability**: `liability not to exceed $1M`
- **Termination**: `90 days written notice`
- **Governing Law**: `governed by laws of Delaware`
- **Effective Date**: `effective January 1, 2024`

#### 🔧 Technical Category
- **API Endpoints**: `GET /api/users`, `POST /auth/login`
- **Versions**: `version 2.1.0`, `v3.5`
- **Response Time**: `response time 150ms`
- **Rate Limits**: `1000 requests per minute`
- **Authentication**: `OAuth 2.0`, `JWT tokens`
- **Status Codes**: `HTTP 200`, `status code 404`

#### 🏥 Medical Category
- **Dosage**: `50mg daily`, `100ml twice daily`
- **Duration**: `treatment for 12 weeks`
- **Efficacy**: `85% efficacy rate`
- **Side Effects**: `side effects in 12% of patients`
- **Patient Count**: `500 patients enrolled`
- **P-Values**: `p<0.001`, `p=0.025`

## 🔑 **Custom Keys Feature**

### What It Does
Users can specify their own extraction terms as comma-separated values:

**Example Inputs:**
```
CEO, budget, deadline, timeline
risk assessment, compliance, audit
performance, scalability, security
treatment, dosage, clinical trial
```

### How It Works
- **Smart Extraction**: Finds sentences containing the custom terms
- **Context Preservation**: Returns full sentences, not just keywords
- **Confidence Scoring**: Shows extraction confidence levels
- **JSON Output**: Structured data for easy integration

## 🎯 **New Strategy: Category-Specific Extraction**

### What's New
Added a specialized strategy that combines:
1. **Category-specific patterns** for targeted extraction
2. **Custom key extraction** for user-defined terms
3. **Structured output** with confidence scores
4. **Domain expertise** for each business category

### Example Output
```json
{
  "category": "Finance",
  "extracted_data": {
    "revenue": ["$150 million", "$2.5 billion sales"],
    "growth": ["15% increase", "20% growth rate"],
    "date": ["Q3 2024", "fiscal year 2023"]
  },
  "custom_extractions": {
    "CEO": ["CEO announced plans to expand", "CEO John Smith reported"],
    "investment": ["$50M investment in AI", "investment in new markets"]
  },
  "confidence_scores": {
    "revenue": 8.5,
    "custom_CEO": 6.2
  }
}
```

## 🎨 **Enhanced UI Elements**

### New Input Controls
- **📂 Category Dropdown**: Manual category selection
- **🔑 Custom Keys Input**: Text field for custom extraction terms
- **📊 Enhanced Strategy Selection**: Added "Category-Specific Extraction"

### New Output Tabs
- **🎯 Category Analysis**: Dedicated tab for category-specific results
- **Enhanced JSON**: Structured category extraction data
- **Confidence Scores**: Shows extraction reliability

### Improved User Experience
- **Dynamic Help Text**: Context-aware guidance
- **Example Suggestions**: Sample custom keys for each category
- **Better Visual Organization**: Clearer result presentation

## 🚀 **Usage Examples**

### Finance Document Analysis
```
Document Category: Finance
Custom Keys: CEO, quarterly results, investment
Strategy: Category-Specific Extraction
```

**Result**: Extracts revenue figures, profit margins, growth rates PLUS CEO mentions, quarterly data, and investment information.

### Legal Contract Review
```
Document Category: Legal  
Custom Keys: liability, termination, governing law
Strategy: Category-Specific Extraction
```

**Result**: Finds contract parties, terms, dates PLUS specific liability clauses, termination conditions, and jurisdiction details.

### Technical Documentation
```
Document Category: Technical
Custom Keys: security, performance, scalability  
Strategy: Category-Specific Extraction
```

**Result**: Extracts API endpoints, versions, rate limits PLUS security features, performance metrics, and scalability considerations.

## 🎯 **Why This Makes Active Reading Better**

### 1. **Adaptive Intelligence**
- AI now adapts not just to document type, but to user-specific needs
- Combines automated domain detection with custom requirements

### 2. **Enterprise Flexibility**  
- Users can extract exactly what they need for their business case
- Supports diverse enterprise document analysis workflows

### 3. **Structured Output**
- Category-specific patterns ensure consistent extraction
- Custom keys add user-defined flexibility
- JSON format enables easy integration

### 4. **Demonstrable Value**
- Shows how Active Reading adapts to different business domains
- Proves the framework can handle real enterprise requirements
- Highlights the superiority over one-size-fits-all approaches

## 🎨 **Implementation Impact**

### What Changed in Code
- **Added**: `extract_category_specific_info()` method
- **Enhanced**: `process_document()` function with category/custom key parameters  
- **New**: Category-specific regex patterns for each domain
- **Improved**: UI with additional input controls and output tabs

### Backward Compatibility
- ✅ All existing strategies still work
- ✅ Auto-detection remains the default
- ✅ Original demo functionality preserved
- ✅ Enhanced with new capabilities

This makes your Active Reading demo much more interactive and showcases the adaptive intelligence that makes it superior to traditional document processing approaches! 🚀