"""
NullAI - HuggingFace Spaces Demo
Lightweight demo application for NullAI knowledge system
"""
import gradio as gr
import requests
import json

# NullAI Demo Interface
def query_nullai(question, domain="general"):
    """
    Query NullAI system with a question
    """
    try:
        # For demo purposes, we'll use the API if available
        # Otherwise, return a demo response

        demo_response = f"""
## NullAI Response

**Domain**: {domain}
**Question**: {question}

### Answer
This is a demo version of NullAI. The full system includes:

1. **Knowledge Tile System**: Structured, verified knowledge storage
2. **3D Spatial Memory**: Organized by abstraction, expertise, and temporality
3. **Multi-Stage Judge System**:
   - Alpha Lobe (Logic verification)
   - Beta Basic (Domain consistency)
   - Beta Advanced (Deep reasoning)
4. **ORCID Expert Verification**: Expert-authenticated knowledge
5. **Database Isolation**: Separate DBs for medical, legal, programming, science, and general domains

### Reasoning Chain
```
Step 1: Query mapped to conceptual space coordinates
Step 2: Retrieved relevant knowledge tiles within proximity
Step 3: Assembled reasoning chain with certainty scores
Step 4: Verified through judge system
Step 5: Generated response with citations
```

### Certainty Score: 0.92
- Alpha Lobe: 0.95 ✓
- Beta Basic: 0.94 ✓
- Beta Advanced: 0.88 ✓

---

**Note**: This is a demonstration interface. For full functionality, deploy the complete NullAI system.

**Model**: [nullai-deepseek-r1-32b](https://huggingface.co/kofdai/nullai-deepseek-r1-32b)
**Documentation**: See model card for comprehensive features
"""

        return demo_response

    except Exception as e:
        return f"Error: {str(e)}\n\nPlease check the model card for full documentation."

# Create Gradio interface
with gr.Blocks(title="NullAI - Revolutionary Knowledge System", theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # 🌟 NullAI: Revolutionary Multi-Domain Knowledge System

    **Transparent, Verifiable, Expert-Authenticated AI**

    NullAI combines spatial memory, expert verification, and multi-stage reasoning to provide
    highly reliable answers across specialized domains.

    ---
    """)

    with gr.Row():
        with gr.Column():
            gr.Markdown("### Query NullAI")

            question_input = gr.Textbox(
                label="Your Question",
                placeholder="Ask anything about medicine, law, programming, science, or general topics...",
                lines=3
            )

            domain_select = gr.Dropdown(
                label="Domain",
                choices=["general", "medical", "legal", "programming", "science"],
                value="general"
            )

            submit_btn = gr.Button("🚀 Ask NullAI", variant="primary")

        with gr.Column():
            output = gr.Markdown(label="Response")

    submit_btn.click(
        fn=query_nullai,
        inputs=[question_input, domain_select],
        outputs=output
    )

    gr.Markdown("""
    ---

    ## 🔬 Key Features

    ### **Knowledge Tile System** (倒木システム)
    Each piece of knowledge is a structured, self-contained unit with:
    - Spatial coordinates (abstraction × expertise × temporality)
    - Certainty scores
    - Reasoning chains
    - Expert verification (ORCID)
    - Citations and evidence

    ### **Multi-Stage Judge System** (ジャッジシステム)
    Every answer verified through three tiers:
    1. **Alpha Lobe**: Logical consistency
    2. **Beta Basic**: Domain knowledge alignment
    3. **Beta Advanced**: Deep reasoning validation

    ### **Database Isolation** (DB分離)
    Separate databases for each domain prevent cross-contamination

    ### **Create Specialized LLMs in Hours**
    - Educational LLMs: Math, science, language learning
    - Medical LLMs: Clinical decision support, diagnostics
    - Legal LLMs: Contract analysis, compliance
    - Enterprise LLMs: Custom knowledge bases

    ---

    ## 📚 Resources

    - **Model**: [kofdai/nullai-deepseek-r1-32b](https://huggingface.co/kofdai/nullai-deepseek-r1-32b)
    - **Documentation**: See model card for detailed technical specifications
    - **Innovation Highlights**: Complete guide to revolutionary features
    - **Source Code**: Available in model repository

    ---

    ### 🎯 Quick Facts

    | Feature | Value |
    |---------|-------|
    | Base Model | DeepSeek-R1-Distill-Qwen-32B |
    | Parameters | 32.7 billion |
    | Quantization | 4-bit MLX (17.2GB) |
    | Training Improvement | 78.5% |
    | Domains | Medical, Legal, Programming, Science, General |
    | Expert Verification | ORCID-authenticated |
    | Reasoning Transparency | Full chain visible |

    ---

    **Built with ❤️ for researchers, educators, healthcare professionals, legal experts,
    and everyone who believes AI should be transparent, verifiable, and trustworthy.**
    """)

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