OpenViking abandons traditional RAG vector storage and uses a filesystem paradigm instead. It organizes agent context (memories, resources, skills) under viking:// URIs with a three-tier structure:
- L0 (Abstract): One-sentence summary for quick retrieval
- L1 (Overview): Core information and usage scenarios
- L2 (Details): Full original data, loaded on demand
This enables directory recursive retrieval that locks high-score directories first, then refines content exploration. The retrieval trajectory is fully observable, letting users see exactly how context is being accessed.
Key features:
- Unified context management via virtual filesystem
- Tiered context loading reduces token consumption
- Automatic session management extracts long-term memory
- Visualized retrieval trajectories for debugging
OpenViking is built with Python, Go (AGFS), and C++. It supports Volcengine Doubao, OpenAI, and LiteLLM providers.