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89 lines
2.5 KiB
Markdown
89 lines
2.5 KiB
Markdown
# Frontend Application
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This directory contains the Next.js frontend application for the txt2kg project.
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## Structure
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- **app/**: Next.js 15 app directory with pages and API routes
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- API routes for LLM providers (Ollama, vLLM, NVIDIA API)
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- Triple extraction and graph query endpoints
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- Settings and health check endpoints
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- **components/**: React 19 components
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- Graph visualization (Three.js WebGPU)
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- PyGraphistry integration for GPU-accelerated rendering
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- RAG query interface
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- Document upload and processing
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- **contexts/**: React context providers for state management
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- **hooks/**: Custom React hooks
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- **lib/**: Utility functions and shared logic
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- LLM service (Ollama, vLLM, NVIDIA API integration)
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- Graph database services (ArangoDB, Neo4j)
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- Qdrant vector database integration
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- RAG service for knowledge graph querying
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- **public/**: Static assets
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- **types/**: TypeScript type definitions for graph data structures
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## Technology Stack
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- **Next.js 15**: React framework with App Router
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- **React 19**: Latest React with improved concurrent features
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- **TypeScript**: Type-safe development
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- **Tailwind CSS**: Utility-first styling
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- **Three.js**: WebGL/WebGPU 3D graph visualization
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- **D3.js**: Data-driven visualizations
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- **LangChain**: LLM orchestration and chaining
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## Development
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To start the development server:
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```bash
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cd frontend
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npm install
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npm run dev
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```
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Or use the start script from project root:
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```bash
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./start.sh --dev-frontend
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```
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The development server will run on http://localhost:3000
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## Building for Production
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```bash
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cd frontend
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npm run build
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npm start
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```
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Or use Docker (recommended):
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```bash
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# From project root
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./start.sh
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```
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The production app will run on http://localhost:3001
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## Environment Variables
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Required environment variables are configured in docker-compose files:
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- `ARANGODB_URL`: ArangoDB connection URL
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- `OLLAMA_BASE_URL`: Ollama API endpoint
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- `VLLM_BASE_URL`: vLLM API endpoint (optional)
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- `NVIDIA_API_KEY`: NVIDIA API key (optional)
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- `QDRANT_URL`: Qdrant vector database URL (optional)
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- `SENTENCE_TRANSFORMER_URL`: Embeddings service URL (optional)
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## Features
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- **Knowledge Graph Extraction**: Extract triples from text using LLMs
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- **Graph Visualization**: Interactive 3D visualization with Three.js WebGPU
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- **RAG Queries**: Query knowledge graphs with retrieval-augmented generation
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- **Multiple LLM Providers**: Support for Ollama, vLLM, and NVIDIA API
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- **GPU-Accelerated Rendering**: Optional PyGraphistry integration for large graphs
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- **Vector Search**: Qdrant integration for semantic search |