WeKnora Documentation
Comprehensive documentation for WeKnora, covering installation, configuration, usage, and advanced features.
Table of Contents
Installation & Setup
WeKnora can be installed using Docker Compose for the easiest setup experience.
System Requirements
- Docker 20.10+ and Docker Compose 2.0+
- 4GB+ RAM (8GB recommended)
- 10GB+ free disk space
- Linux, macOS, or Windows with WSL2
Quick Installation
For detailed installation instructions, see our Getting Started Guide.
Configuration
WeKnora can be configured through the Web UI or configuration files.
Web UI Configuration
The recommended way to configure WeKnora is through the Web UI:
- Access the Web UI at
http://localhost - Create or select a knowledge base
- Navigate to the configuration page
- Configure models, prompts, and retrieval settings
Model Configuration
You can configure different models for various tasks:
- Embedding Models: For generating vector embeddings (e.g., OpenAI, local models)
- LLM Models: For generating answers (OpenAI, Ollama, etc.)
- Reranking Models: For improving retrieval precision
Environment Variables
Key environment variables can be set in .env file:
Document Parsing
WeKnora supports parsing documents in various formats and extracting structured information.
Supported Formats
- PDF (.pdf)
- Microsoft Word (.docx)
- Markdown (.md)
- Plain Text (.txt)
- HTML (.html)
- Web URLs
Parsing Features
- Automatic structure detection (headings, sections, lists)
- Text extraction with formatting preservation
- Table extraction and parsing
- Image and metadata extraction
- Intelligent chunking strategies
Upload Methods
- Drag and Drop: Drag files directly into the upload area
- Folder Import: Import entire folders of documents
- URL Import: Import documents from web URLs
- API Upload: Use the API to programmatically upload documents
Related Documentation
Retrieval Configuration
Configure how WeKnora retrieves relevant information from your knowledge bases.
Retrieval Strategies
- Semantic Search: Vector-based similarity search
- Keyword Search: Traditional keyword matching
- Hybrid Search: Combination of semantic and keyword search
Retrieval Parameters
- Top K: Number of documents/chunks to retrieve
- Similarity Threshold: Minimum similarity score for retrieval
- Reranking: Enable/disable reranking for improved precision
- Cross-KB Search: Search across multiple knowledge bases
Reranking
Reranking improves retrieval precision by reordering results based on relevance:
- Configure reranking models in knowledge base settings
- Adjust reranking parameters for optimal performance
- Balance between speed and accuracy
Agent Mode Configuration
Agent mode enables ReACT (Reasoning and Acting) agents that can use tools and reason through problems.
Enabling Agent Mode
- Navigate to conversation settings
- Select "Agent Mode" in the conversation interface
- Configure agent model and tools
- Enable/disable web search as needed
Agent Tools
- Knowledge Base Retrieval: Built-in tool for searching knowledge bases
- MCP Tools: External tools via Model Context Protocol
- Web Search: Real-time web search capabilities
Agent Behavior
- Multi-iteration reasoning and reflection
- Tool call visualization
- Comprehensive summary reports
- Cross-knowledge base retrieval
Learn More
Knowledge Graph Configuration
Enable knowledge graph generation to visualize relationships between document sections.
Enabling Knowledge Graphs
- Navigate to knowledge base settings
- Enable "Knowledge Graph" feature
- Configure relationship extraction parameters
- Process documents to generate graph
Graph Features
- Automatic relationship extraction
- Semantic association network construction
- Interactive graph visualization
- Enhanced retrieval using graph structure
Graph Visualization
The knowledge graph provides:
- Visual representation of document relationships
- Interactive exploration of connections
- Contextual understanding of document structure
MCP Server Configuration
Configure WeKnora to work as an MCP (Model Context Protocol) server.
Installation
Configuration
Set environment variables:
Running the Server
Client Configuration
Configure your MCP client to connect to WeKnora:
Related Resources
Development Environment
Set up a development environment for contributing to WeKnora or customizing it for your needs.
Fast Development Mode
Use development mode to avoid rebuilding Docker images:
Development Advantages
- Frontend hot-reload (no restart needed)
- Backend quick restart (5-10 seconds)
- No Docker image rebuilds
- IDE breakpoint debugging support
Project Structure
Building from Source
Production Deployment
Deploy WeKnora to production environments using Docker or Kubernetes.
Docker Compose Deployment
For single-server deployments:
Kubernetes Deployment
WeKnora includes Helm charts for Kubernetes:
Production Considerations
- Use production-grade databases (PostgreSQL)
- Configure proper backup strategies
- Set up monitoring and logging
- Use reverse proxy (nginx, traefik) for SSL
- Configure resource limits and scaling
Troubleshooting
Common issues and their solutions.
Services Won't Start
- Check Docker and Docker Compose are running
- Verify ports 80, 8080, 16686 are not in use
- Check Docker logs:
docker-compose logs - Ensure sufficient disk space and memory
Document Processing Fails
- Verify document format is supported
- Check document is not corrupted
- Review document reader service logs
- Ensure sufficient storage space
Retrieval Issues
- Verify embeddings are generated correctly
- Check vector database connection
- Adjust retrieval thresholds
- Review similarity scores
API Errors
- Verify API key is correct
- Check API endpoint URL
- Review API request format
- Check rate limits