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README.md

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+# Lovdata Chat Interface
+
+A web-based chat interface that allows users to interact with Large Language Models (LLMs) equipped with Norwegian legal research tools from the Lovdata MCP server.
+
+## Overview
+
+This project creates a chat interface where users can:
+- Choose from multiple LLM providers (OpenAI, Anthropic, Google Gemini)
+- Have conversations enhanced with Norwegian legal document search capabilities
+- Access laws, regulations, and legal provisions through AI-powered semantic search
+- Receive properly cited legal information with cross-references
+
+## Architecture
+
+### Backend (FastAPI)
+- **LLM Provider Layer**: Abstract interface supporting multiple LLM providers with tool calling
+- **MCP Integration**: Client connection to lovdata-ai MCP server
+- **Skill System**: Norwegian legal research guidance and best practices
+- **Chat Management**: Conversation history, streaming responses, session management
+
+### Frontend (Next.js)
+- **Chat Interface**: Real-time messaging with streaming responses
+- **Model Selector**: Dropdown to choose LLM provider and model
+- **Tool Visualization**: Display when legal tools are being used
+- **Citation Rendering**: Properly formatted legal references and cross-references
+
+### External Dependencies
+- **Lovdata MCP Server**: Provides 15+ tools for Norwegian legal research
+- **PostgreSQL Database**: Vector embeddings for semantic search
+- **LLM APIs**: OpenAI, Anthropic, Google Gemini (with API keys)
+
+## Supported LLM Providers
+
+| Provider | Models | Tool Support | Notes |
+|----------|--------|--------------|-------|
+| OpenAI | GPT-4, GPT-4o | ✅ Native | Requires API key |
+| Anthropic | Claude-3.5-Sonnet | ✅ Native | Requires API key |
+| Google | Gemini-1.5-Pro | ✅ Function calling | Requires API key |
+| Local | Ollama models | ⚠️ Limited | Self-hosted option |
+
+## MCP Tools Available
+
+The interface integrates all tools from the lovdata-ai MCP server:
+
+### Law Document Tools
+- `get_law`: Retrieve specific laws by ID or title
+- `list_laws`: Browse laws with filtering and pagination
+- `get_law_content`: Get HTML content of laws
+- `get_law_text`: Get plain text content
+
+### Search Tools
+- `search_laws_fulltext`: Full-text search in laws
+- `search_laws_semantic`: Semantic search using vector embeddings
+- `search_provisions_fulltext`: Full-text search in provisions
+- `search_provisions_semantic`: Semantic search in provisions
+
+### Provision Tools
+- `get_provision`: Get individual legal provisions
+- `list_provisions`: List all provisions in a law
+- `get_provisions_batch`: Bulk retrieval for RAG applications
+
+### Reference Tools
+- `get_cross_references`: Find references from/to provisions
+- `resolve_reference`: Parse legal reference strings (e.g., "lov/2014-06-20-42/§8")
+
+## Skills Integration
+
+The system loads Norwegian legal research skills that ensure:
+- Proper citation standards (Lovdata URL formatting)
+- Appropriate legal terminology usage
+- Clear distinction between information and legal advice
+- Systematic amendment tracking
+- Cross-reference analysis
+
+## Implementation Plan
+
+### Phase 1: Core Infrastructure
+1. **Project Structure Setup**
+   - Create backend (FastAPI) and frontend (Next.js) directories
+   - Set up Python virtual environment and Node.js dependencies
+   - Configure development tooling (linting, testing, formatting)
+
+2. **LLM Provider Abstraction**
+   - Create abstract base class for LLM providers
+   - Implement OpenAI, Anthropic, and Google Gemini clients
+   - Add tool calling support and response streaming
+   - Implement provider switching logic
+
+3. **MCP Server Integration**
+   - Build MCP client to connect to lovdata-ai server
+   - Create tool registry and execution pipeline
+   - Add error handling and retry logic
+   - Implement tool result formatting for LLM consumption
+
+### Phase 2: Chat Functionality
+4. **Backend API Development**
+   - Create chat session management endpoints
+   - Implement conversation history storage
+   - Add streaming response support
+   - Build health check and monitoring endpoints
+
+5. **Skill System Implementation**
+   - Create skill loading and parsing system
+   - Implement skill application to LLM prompts
+   - Add skill validation and error handling
+   - Create skill management API endpoints
+
+### Phase 3: Frontend Development
+6. **Chat Interface**
+   - Build responsive chat UI with message history
+   - Implement real-time message streaming
+   - Add message formatting for legal citations
+   - Create conversation management (new chat, clear history)
+
+7. **Model Selection UI**
+   - Create LLM provider and model selector
+   - Add API key management (secure storage)
+   - Implement model switching during conversations
+   - Add model capability indicators
+
+8. **Tool Usage Visualization**
+   - Display when MCP tools are being used
+   - Show tool execution results in chat
+   - Add legal citation formatting
+   - Create expandable tool result views
+
+### Phase 4: Deployment & Production
+9. **Containerization**
+   - Create Dockerfiles for backend and frontend
+   - Set up Docker Compose for development
+   - Configure production Docker Compose
+   - Add environment variable management
+
+10. **Deployment Configuration**
+    - Set up CI/CD pipeline (GitHub Actions)
+    - Configure cloud deployment (Railway/Render)
+    - Add reverse proxy configuration
+    - Implement SSL certificate management
+
+11. **Monitoring & Error Handling**
+    - Add comprehensive logging
+    - Implement error tracking and reporting
+    - Create health check endpoints
+    - Add rate limiting and abuse protection
+
+12. **Documentation**
+    - Create setup and deployment guides
+    - Document API endpoints
+    - Add user documentation
+    - Create troubleshooting guides
+
+## Development Setup
+
+### Prerequisites
+- Python 3.12+
+- Node.js 18+
+- Docker and Docker Compose
+- API keys for desired LLM providers
+
+### Local Development
+```bash
+# Clone and setup
+git clone <repository>
+cd lovdata-chat
+
+# Backend setup
+cd backend
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+pip install -r requirements.txt
+
+# Frontend setup
+cd ../frontend
+npm install
+
+# Start development servers
+docker-compose -f docker-compose.dev.yml up
+```
+
+### Environment Variables
+```bash
+# Backend
+LOVDATA_MCP_URL=http://localhost:8001
+OPENAI_API_KEY=your_key_here
+ANTHROPIC_API_KEY=your_key_here
+GOOGLE_API_KEY=your_key_here
+
+# Frontend
+NEXT_PUBLIC_API_URL=http://localhost:8000
+```
+
+## Deployment Options
+
+### Cloud Deployment (Recommended)
+- **Frontend**: Vercel or Netlify
+- **Backend**: Railway, Render, or Fly.io
+- **Database**: Use existing lovdata-ai PostgreSQL instance
+
+### Self-Hosted Deployment
+- **Docker Compose**: Full stack containerization
+- **Reverse Proxy**: Nginx or Caddy
+- **SSL**: Let's Encrypt automatic certificates
+
+## Security Considerations
+
+- API keys stored securely (environment variables, secret management)
+- Rate limiting on chat endpoints
+- Input validation and sanitization
+- CORS configuration for frontend-backend communication
+- Audit logging for legal tool usage
+
+## Performance Optimization
+
+- Response streaming for real-time chat experience
+- MCP tool result caching
+- Conversation history pagination
+- Lazy loading of legal document content
+- CDN for static frontend assets
+
+## Future Enhancements
+
+- User authentication and conversation persistence
+- Advanced citation management and export
+- Integration with legal research workflows
+- Multi-language support beyond Norwegian
+- Advanced analytics and usage tracking
+
+## Contributing
+
+1. Follow the implementation plan phases
+2. Ensure comprehensive testing for LLM integrations
+3. Document API changes and new features
+4. Maintain security best practices for API key handling
+
+---
+
+**Status**: Planning phase complete. Ready for implementation.
+
+**Next Steps**: Begin with Phase 1 - Project Structure Setup