Roadmap
This document outlines the development roadmap for OpenViking.
Completed Features
Core Infrastructure
- Three-layer information model (L0/L1/L2)
- Viking URI addressing system
- Dual-layer storage (AGFS + Vector Index)
- Async/Sync client support
- QueueFS with SQLite backend
Resource Management
- Text resource management (Markdown, HTML, PDF)
- Automatic L0/L1 generation
- Semantic search with vector indexing
- Resource relations and linking
- Content write API
- Agent namespace management
Multi-modal Parsing
- Image OCR and parsing
- Audio transcription (Whisper ASR)
- Video parsing
- PDF with bookmark extraction
- Word, PowerPoint, Excel, EPub, ZIP parsers
- Code file parsing
- Feishu/Lark document parser
Retrieval
- Basic semantic search (
find) - Context-aware search with intent analysis (
search) - Session-based query expansion
- Reranking pipeline with multiple providers (OpenAI, LiteLLM, Cohere, Volcengine)
Session & Memory
- Conversation state tracking
- Context and skill usage tracking
- Automatic memory extraction
- Memory deduplication with LLM
- Session archiving and compression
- Working Memory V2 with cold-storage archival
Skills
- Skill definition and storage
- MCP tool auto-conversion
- Skill search and retrieval
Multi-tenant & Security
- Multi-tenant support with account isolation
- File and document encryption
- User-level privacy configs API
- API Key authentication
Configuration & Providers
- Pluggable embedding providers (OpenAI, Gemini, Volcengine, MiniMax, LiteLLM, Jina, Cohere, DashScope, Voyage, local)
- Pluggable LLM providers
- Pluggable rerank providers
- YAML-based configuration
- Setup wizard (
openviking-server init)
Server & Client Architecture
- HTTP Server (FastAPI)
- Native MCP endpoint built into openviking-server
- Python HTTP Client
- Client abstraction layer (LocalClient / HTTPClient)
- Web Console
CLI
- Rust CLI (
ovcommand) - TUI filesystem navigator
- Privacy, search, session, resource, and admin commands
Bot Integration
- VikingBot framework
- Feishu/Lark channel
- Telegram channel
Ecosystem & Plugins
- OpenClaw plugin (context engine for coding agents)
- Claude Code memory plugin
- Codex memory plugin
Observability
- Prometheus metrics
- OpenTelemetry tracing
- HTTP observability middleware
Deployment
- Docker image and Docker Compose
- Helm Chart for Kubernetes
- Cloud VikingDB support
Future Plans
Context Management
- Propagation updates when context is modified
- Version management and rollback for context (git-like)
Distributed Storage
- Distributed storage backend
Ecosystem
- Additional Agent framework adapters
We welcome suggestions and feedback in issues.
Contributing
We welcome contributions to help achieve these goals. See Contributing for guidelines.
