import gradio as gr
import json
import os

# Load capability registry
def load_registry():
    registry_path = os.path.join(os.path.dirname(__file__), '..', 'data', 'capability_registry.json')
    with open(registry_path, 'r') as f:
        return json.load(f)

registry = load_registry()
capabilities = registry['capabilities']

# Extract unique values for filters
all_categories = sorted(list(set([cap['category'] for cap in capabilities])))
all_spaces = sorted(list(set([space for cap in capabilities for space in cap['used_in_spaces']])))
all_models = sorted(list(set([model for cap in capabilities for model in cap['models']])))
all_datasets = sorted(list(set([dataset for cap in capabilities for dataset in cap['datasets']])))

def search_capabilities(search_text, category_filter, space_filter, model_filter, dataset_filter):
    """Search and filter capabilities based on user inputs"""
    filtered_caps = capabilities
    
    # Apply search text filter
    if search_text:
        search_lower = search_text.lower()
        filtered_caps = [
            cap for cap in filtered_caps 
            if search_lower in cap['capability_name'].lower() 
            or search_lower in cap['category'].lower()
            or search_lower in ' '.join(cap['insurance_decisions']).lower()
        ]
    
    # Apply category filter
    if category_filter and category_filter != "All":
        filtered_caps = [cap for cap in filtered_caps if cap['category'] == category_filter]
    
    # Apply space filter
    if space_filter and space_filter != "All":
        filtered_caps = [cap for cap in filtered_caps if space_filter in cap['used_in_spaces']]
    
    # Apply model filter
    if model_filter and model_filter != "All":
        filtered_caps = [cap for cap in filtered_caps if model_filter in cap['models']]
    
    # Apply dataset filter
    if dataset_filter and dataset_filter != "All":
        filtered_caps = [cap for cap in filtered_caps if dataset_filter in cap['datasets']]
    
    # Generate HTML output
    if not filtered_caps:
        return "<div style='padding: 20px; text-align: center;'><h3>No capabilities found matching your criteria.</h3></div>"
    
    html_output = f"<div style='padding: 20px;'><h3>Found {len(filtered_caps)} Capability(ies)</h3>"
    
    for cap in filtered_caps:
        html_output += f"""
        <div style='border: 1px solid #ddd; border-radius: 8px; padding: 20px; margin: 15px 0; background: #f9f9f9;'>
            <h3 style='margin-top: 0; color: #2c3e50;'>🔹 {cap['capability_name']}</h3>
            <p><strong>Category:</strong> {cap['category']}</p>
            <p><strong>Used in Spaces:</strong> {', '.join(cap['used_in_spaces'])}</p>
            <p><strong>Models:</strong> {', '.join(cap['models'])}</p>
            <p><strong>Datasets:</strong> {', '.join(cap['datasets'])}</p>
            <p><strong>Insurance Decisions:</strong> {', '.join(cap['insurance_decisions'])}</p>
            <p><strong>Governance Required:</strong> {'✅ Yes' if cap['governance_required'] else '❌ No'}</p>
        </div>
        """
    
    html_output += "</div>"
    return html_output

def create_capability_browser():
    """Create the Gradio interface for capability browsing"""
    
    with gr.Blocks(title="BDR Agent Factory - Capability Browser", theme=gr.themes.Soft()) as demo:
        gr.Markdown("""
        # 🏭 BDR Agent Factory — Capability Browser
        
        **Enterprise Decision Intelligence Architecture for Insurance & Regulated Markets**
        
        Browse and search AI capabilities used across the Bader AI platform. Filter by category, system, model, or dataset to understand how capabilities map to insurance decisions.
        """)
        
        with gr.Row():
            with gr.Column(scale=2):
                search_box = gr.Textbox(
                    label="🔍 Search Capabilities",
                    placeholder="Search by capability name, category, or decision...",
                    lines=1
                )
            
        with gr.Row():
            category_dropdown = gr.Dropdown(
                choices=["All"] + all_categories,
                value="All",
                label="📂 Filter by Category",
                interactive=True
            )
            space_dropdown = gr.Dropdown(
                choices=["All"] + all_spaces,
                value="All",
                label="🚀 Filter by Space",
                interactive=True
            )
            model_dropdown = gr.Dropdown(
                choices=["All"] + all_models,
                value="All",
                label="🤖 Filter by Model",
                interactive=True
            )
            dataset_dropdown = gr.Dropdown(
                choices=["All"] + all_datasets,
                value="All",
                label="📊 Filter by Dataset",
                interactive=True
            )
        
        search_button = gr.Button("Search", variant="primary", size="lg")
        
        results_html = gr.HTML(
            value=search_capabilities("", "All", "All", "All", "All"),
            label="Results"
        )
        
        # Set up event handlers
        search_button.click(
            fn=search_capabilities,
            inputs=[search_box, category_dropdown, space_dropdown, model_dropdown, dataset_dropdown],
            outputs=results_html
        )
        
        # Also trigger search on Enter key in search box
        search_box.submit(
            fn=search_capabilities,
            inputs=[search_box, category_dropdown, space_dropdown, model_dropdown, dataset_dropdown],
            outputs=results_html
        )
        
        gr.Markdown("""
        ---
        
        ## 📚 Documentation
        
        - **[Overview](https://huggingface.co/spaces/bdr-ai-org/BDR-Agent-Factory/blob/main/docs/00_OVERVIEW.md)**: What is BDR Agent Factory?
        - **[Capability Dictionary](https://huggingface.co/spaces/bdr-ai-org/BDR-Agent-Factory/blob/main/docs/01_CAPABILITY_DICTIONARY.md)**: Full catalog of AI capabilities (A–N)
        - **[Capability Map](https://huggingface.co/spaces/bdr-ai-org/BDR-Agent-Factory/blob/main/docs/02_CAPABILITY_MAP.md)**: Mappings to systems, models, datasets, decisions
        - **[Governance Standards](https://huggingface.co/spaces/bdr-ai-org/BDR-Agent-Factory/blob/main/docs/03_GOVERNANCE.md)**: Unified governance policies
        - **[Extension Guide](https://huggingface.co/spaces/bdr-ai-org/BDR-Agent-Factory/blob/main/docs/04_EXTENSION_GUIDE.md)**: How to add new capabilities
        
        ## 🔗 Linked Systems
        
        - **[ClaimsGPT](https://huggingface.co/spaces/bdr-ai-org/ClaimsGPT)**: AI-powered claim decision intelligence
        - **[FraudSimulator-AI](https://huggingface.co/spaces/bdr-ai-org/FraudSimulator-AI)**: Fraud risk and anomaly detection
        - **[AutoRiskScoreEngine](https://huggingface.co/spaces/bdr-ai-org/AutoRiskScoreEngine)**: IFRS-ready underwriting risk assessment
        - **[InsuranceKnowledgeAgent](https://huggingface.co/spaces/bdr-ai-org/InsuranceKnowledgeAgent)**: RAG-powered policy knowledge
        
        ---
        
        **BDR Agent Factory** — The authoritative capability registry for Bader AI, the GCC Insurance Decision Intelligence Platform.
        """)
    
    return demo

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