app.py

import gradio as gr
import torch
from gliner import GLiNER
import pandas as pd
import warnings
import random
import re
warnings.filterwarnings('ignore')

# Standard NER entity types
STANDARD_ENTITIES = [
    'DATE', 'EVENT', 'FAC', 'GPE', 'LANG', 'LOC',
    'MISC', 'NORP', 'ORG', 'PER', 'PRODUCT', 'WORK_OF_ART'
]

# Color schemes
STANDARD_COLORS = {
    'DATE': '#FF6B6B',      # Red
    'EVENT': '#4ECDC4',     # Teal
    'FAC': '#45B7D1',       # Blue
    'GPE': '#F9CA24',       # Yellow
    'LANG': '#6C5CE7',      # Purple
    'LOC': '#A0E7E5',       # Light Cyan
    'MISC': '#FD79A8',      # Pink
    'NORP': '#8E8E93',      # Grey
    'ORG': '#55A3FF',       # Light Blue
    'PER': '#00B894',       # Green
    'PRODUCT': '#E17055',   # Orange-Red
    'WORK_OF_ART': '#DDA0DD'  # Plum
}

# Additional colors for custom entities
CUSTOM_COLOR_PALETTE = [
    '#FF9F43', '#10AC84', '#EE5A24', '#0FBC89', '#5F27CD',
    '#FF3838', '#2F3640', '#3742FA', '#2ED573', '#FFA502',
    '#FF6348', '#1E90FF', '#FF1493', '#32CD32', '#FFD700',
    '#FF4500', '#DA70D6', '#00CED1', '#FF69B4', '#7B68EE'
]

class HybridNERManager:
    def __init__(self):
        self.gliner_model = None
        self.spacy_model = None
        self.all_entity_colors = {}

    def load_gliner_model(self):
        """Load GLiNER model for custom entities"""
        if self.gliner_model is None:
            try:
                # Use a more stable model for HF Spaces
                self.gliner_model = GLiNER.from_pretrained("urchade/gliner_medium-v2.1")
                print("✓ GLiNER model loaded successfully")
            except Exception as e:
                print(f"Error loading GLiNER model: {str(e)}")
                return None
        return self.gliner_model

    def load_spacy_model(self):
        """Load spaCy model for standard NER"""
        if self.spacy_model is None:
            try:
                import spacy
                # Try to load the transformer model first, fallback to smaller model
                try:
                    self.spacy_model = spacy.load("en_core_web_sm")
                    print("✓ spaCy model loaded successfully")
                except OSError:
                    print("spaCy model not found. Using GLiNER for all entity types.")
                    return None
            except Exception as e:
                print(f"Error loading spaCy model: {str(e)}")
                return None
        return self.spacy_model

    def assign_colors(self, standard_entities, custom_entities):
        """Assign colors to all entity types"""
        self.all_entity_colors = {}

        # Assign standard colors
        for entity in standard_entities:
            self.all_entity_colors[entity.upper()] = STANDARD_COLORS.get(entity, '#CCCCCC')

        # Assign custom colors
        for i, entity in enumerate(custom_entities):
            if i < len(CUSTOM_COLOR_PALETTE):
                self.all_entity_colors[entity.upper()] = CUSTOM_COLOR_PALETTE[i]
            else:
                # Generate random color if we run out
                self.all_entity_colors[entity.upper()] = f"#{random.randint(0, 0xFFFFFF):06x}"

        return self.all_entity_colors

    def extract_spacy_entities(self, text, entity_types):
        """Extract entities using spaCy"""
        model = self.load_spacy_model()
        if model is None:
            return []

        try:
            doc = model(text)
            entities = []
            for ent in doc.ents:
                if ent.label_ in entity_types:
                    entities.append({
                        'text': ent.text,
                        'label': ent.label_,
                        'start': ent.start_char,
                        'end': ent.end_char,
                        'confidence': 1.0,  # spaCy doesn't provide confidence scores
                        'source': 'spaCy'
                    })
            return entities
        except Exception as e:
            print(f"Error with spaCy extraction: {str(e)}")
            return []

    def extract_gliner_entities(self, text, entity_types, threshold=0.3, is_custom=True):
        """Extract entities using GLiNER"""
        model = self.load_gliner_model()
        if model is None:
            return []

        try:
            entities = model.predict_entities(text, entity_types, threshold=threshold)
            result = []
            for entity in entities:
                result.append({
                    'text': entity['text'],
                    'label': entity['label'].upper(),
                    'start': entity['start'],
                    'end': entity['end'],
                    'confidence': entity.get('score', 0.0),
                    'source': 'GLiNER-Custom' if is_custom else 'GLiNER-Standard'
                })
            return result
        except Exception as e:
            print(f"Error with GLiNER extraction: {str(e)}")
            return []

def find_overlapping_entities(entities):
    """Find and merge overlapping entities"""
    if not entities:
        return []

    # Sort entities by start position
    sorted_entities = sorted(entities, key=lambda x: x['start'])
    merged_entities = []

    i = 0
    while i < len(sorted_entities):
        current_entity = sorted_entities[i]
        overlapping_entities = [current_entity]

        # Find all entities that overlap with current entity
        j = i + 1
        while j < len(sorted_entities):
            next_entity = sorted_entities[j]

            # Check if entities overlap
            if (current_entity['start'] <= next_entity['start'] < current_entity['end'] or
                next_entity['start'] <= current_entity['start'] < next_entity['end'] or
                current_entity['text'].lower() == next_entity['text'].lower()):
                overlapping_entities.append(next_entity)
                sorted_entities.pop(j)
            else:
                j += 1

        # Create merged entity
        if len(overlapping_entities) == 1:
            merged_entities.append(overlapping_entities[0])
        else:
            merged_entity = merge_entities(overlapping_entities)
            merged_entities.append(merged_entity)

        i += 1

    return merged_entities

def merge_entities(entity_list):
    """Merge multiple overlapping entities into one"""
    if len(entity_list) == 1:
        return entity_list[0]

    # Use the entity with the longest text span as the base
    base_entity = max(entity_list, key=lambda x: len(x['text']))

    # Collect all labels and sources
    labels = [entity['label'] for entity in entity_list]
    sources = [entity['source'] for entity in entity_list]
    confidences = [entity['confidence'] for entity in entity_list]

    return {
        'text': base_entity['text'],
        'start': base_entity['start'],
        'end': base_entity['end'],
        'labels': labels,
        'sources': sources,
        'confidences': confidences,
        'is_merged': True,
        'entity_count': len(entity_list)
    }

def create_highlighted_html(text, entities, entity_colors):
    """Create HTML with highlighted entities"""
    if not entities:
        return f"<div style='padding: 15px; border: 1px solid #ddd; border-radius: 5px; background-color: #fafafa;'><p>{text}</p></div>"

    # Find and merge overlapping entities
    merged_entities = find_overlapping_entities(entities)

    # Sort by start position
    sorted_entities = sorted(merged_entities, key=lambda x: x['start'])

    # Create HTML with highlighting
    html_parts = []
    last_end = 0

    for entity in sorted_entities:
        # Add text before entity
        html_parts.append(text[last_end:entity['start']])

        if entity.get('is_merged', False):
            # Handle merged entity with multiple colors
            html_parts.append(create_merged_entity_html(entity, entity_colors))
        else:
            # Handle single entity
            html_parts.append(create_single_entity_html(entity, entity_colors))

        last_end = entity['end']

    # Add remaining text
    html_parts.append(text[last_end:])

    highlighted_text = ''.join(html_parts)

    return f"""
    <div style='padding: 15px; border: 2px solid #ddd; border-radius: 8px; background-color: #fafafa; margin: 10px 0;'>
        <h4 style='margin: 0 0 15px 0; color: #333;'>📝 Text with Highlighted Entities</h4>
        <div style='line-height: 1.8; font-size: 16px; background-color: white; padding: 15px; border-radius: 5px;'>{highlighted_text}</div>
    </div>
    """

def create_single_entity_html(entity, entity_colors):
    """Create HTML for a single entity"""
    label = entity['label']
    color = entity_colors.get(label.upper(), '#CCCCCC')
    confidence = entity.get('confidence', 0.0)
    source = entity.get('source', 'Unknown')

    return (f'<span style="background-color: {color}; padding: 2px 4px; '
            f'border-radius: 3px; margin: 0 1px; '
            f'border: 1px solid {color}; color: white; font-weight: bold;" '
            f'title="{label} ({source}) - confidence: {confidence:.2f}">'
            f'{entity["text"]}</span>')

def create_merged_entity_html(entity, entity_colors):
    """Create HTML for a merged entity with multiple colors"""
    labels = entity['labels']
    sources = entity['sources']
    confidences = entity['confidences']

    # Get colors for each label
    colors = []
    for label in labels:
        color = entity_colors.get(label.upper(), '#CCCCCC')
        colors.append(color)

    # Create gradient background
    if len(colors) == 2:
        gradient = f"linear-gradient(to right, {colors[0]} 50%, {colors[1]} 50%)"
    else:
        # For more colors, create equal segments
        segment_size = 100 / len(colors)
        gradient_parts = []
        for i, color in enumerate(colors):
            start = i * segment_size
            end = (i + 1) * segment_size
            gradient_parts.append(f"{color} {start}%, {color} {end}%")
        gradient = f"linear-gradient(to right, {', '.join(gradient_parts)})"

    # Create tooltip
    tooltip_parts = []
    for i, label in enumerate(labels):
        tooltip_parts.append(f"{label} ({sources[i]}) - {confidences[i]:.2f}")
    tooltip = " | ".join(tooltip_parts)

    return (f'<span style="background: {gradient}; padding: 2px 4px; '
            f'border-radius: 3px; margin: 0 1px; '
            f'border: 2px solid #333; color: white; font-weight: bold;" '
            f'title="MERGED: {tooltip}">'
            f'{entity["text"]} 🔗</span>')

def create_entity_table_html(entities, entity_colors):
    """Create HTML table of entities"""
    if not entities:
        return "<p>No entities found.</p>"

    # Merge overlapping entities
    merged_entities = find_overlapping_entities(entities)

    # Group entities by type
    entity_groups = {}
    for entity in merged_entities:
        if entity.get('is_merged', False):
            key = 'MERGED_ENTITIES'
        else:
            key = entity['label']
        
        if key not in entity_groups:
            entity_groups[key] = []
        entity_groups[key].append(entity)

    # Create HTML table
    html = "<div style='margin: 15px 0;'>"
    
    for entity_type, entities_of_type in entity_groups.items():
        if entity_type == 'MERGED_ENTITIES':
            color = '#666666'
            header = f"🔗 Merged Entities ({len(entities_of_type)})"
        else:
            color = entity_colors.get(entity_type.upper(), '#CCCCCC')
            header = f"{entity_type} ({len(entities_of_type)})"

        html += f"""
        <h4 style="color: {color}; margin: 15px 0 10px 0;">{header}</h4>
        <table style="width: 100%; border-collapse: collapse; margin-bottom: 20px; border: 1px solid #ddd;">
            <thead>
                <tr style="background-color: {color}; color: white;">
                    <th style="padding: 10px; text-align: left; border: 1px solid #ddd;">Entity Text</th>
                    <th style="padding: 10px; text-align: left; border: 1px solid #ddd;">Label(s)</th>
                    <th style="padding: 10px; text-align: left; border: 1px solid #ddd;">Source(s)</th>
                    <th style="padding: 10px; text-align: left; border: 1px solid #ddd;">Confidence</th>
                </tr>
            </thead>
            <tbody>
        """

        for entity in entities_of_type:
            if entity.get('is_merged', False):
                labels_text = " | ".join(entity['labels'])
                sources_text = " | ".join(entity['sources'])
                conf_text = " | ".join([f"{c:.2f}" for c in entity['confidences']])
            else:
                labels_text = entity['label']
                sources_text = entity['source']
                conf_text = f"{entity['confidence']:.2f}"

            html += f"""
                <tr style="background-color: #fff;">
                    <td style="padding: 8px; border: 1px solid #ddd; font-weight: bold;">{entity['text']}</td>
                    <td style="padding: 8px; border: 1px solid #ddd;">{labels_text}</td>
                    <td style="padding: 8px; border: 1px solid #ddd;">{sources_text}</td>
                    <td style="padding: 8px; border: 1px solid #ddd;">{conf_text}</td>
                </tr>
            """

        html += "</tbody></table>"

    html += "</div>"
    return html

def create_legend_html(entity_colors, standard_entities, custom_entities):
    """Create a legend showing entity colors"""
    if not entity_colors:
        return ""

    html = "<div style='margin: 15px 0; padding: 15px; background-color: #f8f9fa; border-radius: 8px;'>"
    html += "<h4 style='margin: 0 0 15px 0;'>🎨 Entity Type Legend</h4>"

    if standard_entities:
        html += "<div style='margin-bottom: 15px;'>"
        html += "<h5 style='margin: 0 0 8px 0;'>🎯 Standard Entities:</h5>"
        html += "<div style='display: flex; flex-wrap: wrap; gap: 8px;'>"
        for entity_type in standard_entities:
            color = entity_colors.get(entity_type.upper(), '#ccc')
            html += f"<span style='background-color: {color}; padding: 4px 8px; border-radius: 15px; color: white; font-weight: bold; font-size: 12px;'>{entity_type}</span>"
        html += "</div></div>"

    if custom_entities:
        html += "<div>"
        html += "<h5 style='margin: 0 0 8px 0;'>✨ Custom Entities:</h5>"
        html += "<div style='display: flex; flex-wrap: wrap; gap: 8px;'>"
        for entity_type in custom_entities:
            color = entity_colors.get(entity_type.upper(), '#ccc')
            html += f"<span style='background-color: {color}; padding: 4px 8px; border-radius: 15px; color: white; font-weight: bold; font-size: 12px;'>{entity_type}</span>"
        html += "</div></div>"

    html += "</div>"
    return html

# Initialize the NER manager
ner_manager = HybridNERManager()

def process_text(text, standard_entities, custom_entities_str, confidence_threshold, use_spacy, use_gliner_standard):
    """Main processing function for Gradio interface"""
    if not text.strip():
        return "❌ Please enter some text to analyze", "", ""

    # Parse custom entities
    custom_entities = []
    if custom_entities_str.strip():
        custom_entities = [entity.strip() for entity in custom_entities_str.split(',') if entity.strip()]

    # Parse standard entities
    selected_standard = [entity for entity in standard_entities if entity]

    if not selected_standard and not custom_entities:
        return "❌ Please select at least one standard entity type OR enter custom entity types", "", ""

    all_entities = []

    # Extract standard entities
    if selected_standard:
        if use_spacy:
            spacy_entities = ner_manager.extract_spacy_entities(text, selected_standard)
            all_entities.extend(spacy_entities)
        
        if use_gliner_standard:
            gliner_standard_entities = ner_manager.extract_gliner_entities(text, selected_standard, confidence_threshold, is_custom=False)
            all_entities.extend(gliner_standard_entities)

    # Extract custom entities
    if custom_entities:
        custom_entity_results = ner_manager.extract_gliner_entities(text, custom_entities, confidence_threshold, is_custom=True)
        all_entities.extend(custom_entity_results)

    if not all_entities:
        return "❌ No entities found. Try lowering the confidence threshold or using different entity types.", "", ""

    # Assign colors
    entity_colors = ner_manager.assign_colors(selected_standard, custom_entities)

    # Create outputs
    legend_html = create_legend_html(entity_colors, selected_standard, custom_entities)
    highlighted_html = create_highlighted_html(text, all_entities, entity_colors)
    table_html = create_entity_table_html(all_entities, entity_colors)

    # Create summary
    total_entities = len(all_entities)
    merged_entities = find_overlapping_entities(all_entities)
    final_count = len(merged_entities)
    merged_count = sum(1 for e in merged_entities if e.get('is_merged', False))

    summary = f"""
    ## 📊 Analysis Summary
    - **Total entities found:** {total_entities}
    - **Final entities displayed:** {final_count}
    - **Merged entities:** {merged_count}
    - **Average confidence:** {sum(e.get('confidence', 0) for e in all_entities) / total_entities:.3f}
    """

    return summary, legend_html + highlighted_html, table_html

# Create Gradio interface
def create_interface():
    with gr.Blocks(title="Hybrid NER + GLiNER Tool", theme=gr.themes.Soft()) as demo:
        gr.Markdown("""
        # 🎯 Hybrid NER + Custom GLiNER Entity Recognition Tool
        
        Combine standard NER categories with your own custom entity types! This tool uses both traditional NER models and GLiNER for comprehensive entity extraction.
        
        ## 🔗 NEW: Overlapping entities are automatically merged with split-color highlighting!
        
        ### How to use:
        1. **📝 Enter your text** in the text area below
        2. **🎯 Select standard entities** you want to find (PER, ORG, LOC, etc.)
        3. **✨ Add custom entities** (comma-separated) like "relationships, occupations, skills"
        4. **⚙️ Choose models** and adjust confidence threshold
        5. **🔍 Click "Analyze Text"** to see results
        """)
        
        with gr.Row():
            with gr.Column(scale=2):
                text_input = gr.Textbox(
                    label="📝 Text to Analyze",
                    placeholder="Enter your text here...",
                    lines=6,
                    max_lines=10
                )
            
            with gr.Column(scale=1):
                confidence_threshold = gr.Slider(
                    minimum=0.1,
                    maximum=0.9,
                    value=0.3,
                    step=0.1,
                    label="🎚️ Confidence Threshold"
                )
        
        with gr.Row():
            with gr.Column():
                gr.Markdown("### 🎯 Standard Entity Types")
                standard_entities = gr.CheckboxGroup(
                    choices=STANDARD_ENTITIES,
                    value=['PER', 'ORG', 'LOC', 'MISC'],  # Default selection
                    label="Select Standard Entities"
                )
                
                with gr.Row():
                    use_spacy = gr.Checkbox(label="Use spaCy", value=True)
                    use_gliner_standard = gr.Checkbox(label="Use GLiNER for Standard", value=False)
            
            with gr.Column():
                gr.Markdown("### ✨ Custom Entity Types")
                custom_entities = gr.Textbox(
                    label="Custom Entities (comma-separated)",
                    placeholder="e.g. relationships, occupations, skills, emotions",
                    lines=3
                )
                gr.Markdown("""
                **Examples:**
                - relationships, occupations, skills
                - emotions, actions, objects
                - medical conditions, treatments
                """)
        
        analyze_btn = gr.Button("🔍 Analyze Text", variant="primary", size="lg")
        
        # Output sections
        with gr.Row():
            summary_output = gr.Markdown(label="Summary")
        
        with gr.Row():
            highlighted_output = gr.HTML(label="Highlighted Text")
        
        with gr.Row():
            table_output = gr.HTML(label="Detailed Results")
        
        # Connect the button to the processing function
        analyze_btn.click(
            fn=process_text,
            inputs=[
                text_input,
                standard_entities,
                custom_entities,
                confidence_threshold,
                use_spacy,
                use_gliner_standard
            ],
            outputs=[summary_output, highlighted_output, table_output]
        )
        
        # Add examples
        gr.Examples(
            examples=[
                [
                    "John Smith works at Google in New York. He graduated from Stanford University in 2015 and specializes in artificial intelligence research. His wife Sarah is a doctor at Mount Sinai Hospital.",
                    ["PER", "ORG", "LOC", "DATE"],
                    "relationships, occupations, educational background",
                    0.3,
                    True,
                    False
                ],
                [
                    "The meeting between CEO Jane Doe and the board of directors at Microsoft headquarters in Seattle discussed the Q4 financial results and the new AI strategy for 2024.",
                    ["PER", "ORG", "LOC", "DATE"],
                    "corporate roles, business events, financial terms",
                    0.4,
                    True,
                    True
                ]
            ],
            inputs=[
                text_input,
                standard_entities,
                custom_entities,
                confidence_threshold,
                use_spacy,
                use_gliner_standard
            ]
        )

    return demo

if __name__ == "__main__":
    demo = create_interface()
    demo.launch()