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 (ov command)
• 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

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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.

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Contributing

We welcome contributions to help achieve these goals. See Contributing for guidelines.