openviking

name

openviking

description

Context database reference for OpenViking — an open-source context database for AI Agents that unifies memory, resources, and skills through a filesystem paradigm with hierarchical context delivery (L0/L1/L2) and semantic retrieval. Use this skill when the user asks about OpenViking, needs help writing code that uses the openviking Python package, wants to configure or troubleshoot OpenViking, or needs to understand its architecture, APIs, or concepts (Viking URI, context types, retrieval mechanisms, session management, etc.). Trigger on mentions of: "openviking", "viking://", "OpenViking", "context database", "AGFS", "VikingFS", "ovpack", or related API methods like find/search/add_resource/add_skill/session.

OpenViking Context Database

OpenViking is an open-source context database for AI Agents. It unifies memory, resources, and skills via a virtual filesystem (viking:// URIs), provides 3-layer progressive content loading (L0 Abstract / L1 Overview / L2 Detail), and supports directory-recursive semantic retrieval with intent analysis.

Quick Reference

import openviking as ov

client = ov.OpenViking(path="./data")   # embedded mode
client.initialize()

# Add resources
client.add_resource("./docs/", reason="Project docs")
client.wait_processed()

# Search
results = client.find("authentication", target_uri="viking://resources/")
results = client.search("help with auth", session=session)  # with intent analysis

# Filesystem ops
client.ls("viking://resources/")
client.abstract("viking://resources/docs/")   # L0 ~100 tokens
client.overview("viking://resources/docs/")   # L1 ~2k tokens
client.read("viking://resources/docs/api.md") # L2 full content

# Sessions & memory
session = client.session()
session.add_message("user", [TextPart(text="...")])
session.commit()  # archives + extracts memories

client.close()

Reference Files

Load the appropriate reference file based on what the user needs:

• Getting started: Read references/quickstart.md — installation, configuration examples, first script
• Client API: Read references/api-client.md — OpenViking(), initialize, close, modes
• Resources API: Read references/api-resources.md — add_resource, formats, ovpack, managing resources
• Skills API: Read references/api-skills.md — add_skill, SKILL.md format, MCP conversion
• Sessions API: Read references/api-sessions.md — session lifecycle, messages, commit, memory extraction
• Retrieval API: Read references/api-retrieval.md — find vs search, FindResult, hierarchical retrieval
• Filesystem API: Read references/api-filesystem.md — abstract, overview, read, ls, tree, rm, mv, grep, glob, link
• Concepts: Read references/concepts.md — architecture, context types, Viking URI, L0/L1/L2, storage, retrieval mechanism, extraction, session management
• Configuration: Read references/configuration.md — ov.conf schema, model providers, env vars, troubleshooting

Key Concepts Summary

Concept	Description
Viking URI	viking://{scope}/{path} — scopes: resources, user, agent, session
Context Types	Resource (knowledge), Memory (cognition), Skill (capabilities)
L0/L1/L2	Abstract (~100 tok) / Overview (~2k tok) / Full content (unlimited)
find()	Simple vector search, low latency
search()	Intent analysis + session context, higher quality
Session commit	Archives messages, extracts 6 memory categories
Memory categories	profile, preferences, entities, events (user); cases, patterns (agent)

Docs Source

Full documentation: https://openviking.ai/docs