agentseek 0.0.2

A database-native Agent Harness for runtime data workflows, powered by Bub

AgentSeek

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A database-native Agent Harness, by the OceanBase OSS Team.

What AgentSeek is

AgentSeek is a database-native Agent Harness for teams that want agent runtime data to become a first-class database workload. It is open to any Agent Framework — the current version ships with built-in Bub and is LangChain-friendly out of the box.

It treats the database as the natural place to keep agent context, execution history, tool calls, tasks, feedback, and observability together. The same runtime data can then serve debugging, replay, trajectory comparison, evaluation, analysis, and training workflows without being copied into separate systems or re-ingested later.

AgentSeek is a suite of components that work independently or together:

Component	What it does	Repo
agentseek-cli	Scaffold projects, manage lifecycle (create / run / build / deploy)	ob-labs/agentseek
agentseek-api	Agent Protocol server — ship your LangGraph to production, zero code change	ob-labs/agentseek-api
ContextSeek	Semantic context layer — memory, retrieval, evolution, progressive disclosure. Ships with LangChain middleware and LangSmith @traceable support	ob-labs/contextseek
langchain-oceanbase	Data substrate — checkpoint + store + vector + hybrid search on OceanBase / seekdb / MySQL	oceanbase/langchain-oceanbase

Each component has its own repo and docs. This repo documents the suite-level workflow; for component-specific API details, follow the links above.

Quick Start — for LangChain developers

Which template should I pick?

• Starting fresh / learning? → langchain/markdown-messages (minimal, 5 min)
• Already have a graph, need to deliver a product? → langchain/default (frontend + Feishu IM + full runtime)
• Need deep research with sub-agents? → deepagents/research (Tavily + report generation)
• Graph runs on a remote server? → langchain/cli-remote

# Pick one and run:
uvx --from agentseek-cli agentseek create langchain --template markdown-messages
# or: langchain --template default
# or: deepagents --template research

Then: cd <project> && uv sync && uv run langgraph dev (minimal) or uv run agentseek run (full delivery).

LangSmith tracing is pre-configured. Every template ships a .env.example with LANGSMITH_TRACING=true and LANGSMITH_API_KEY ready to fill in.

Next steps after your agent runs:

• Add persistent memory → ContextSeek docs
• Ship to production as a service → agentseek-api docs
• Switch to a durable database → langchain-oceanbase docs
• Install dev skills for guided help → see Development skills below
• Study DeepAgents systematically → see Open-source course below

For OceanBase / seekdb / MySQL developers

Already running OceanBase, seekdb, or MySQL? AgentSeek uses your database as the data substrate for AI agents.

pip install langchain-oceanbase[pyseekdb]   # OceanBase / seekdb
pip install langchain-oceanbase             # MySQL (checkpoint + store)

MySQL users get checkpoint and store out of the box; vector search requires OceanBase or seekdb. Full docs: langchain-oceanbase.

Other paths

AgentSeek ships as two complementary PyPI packages split by job:

• agentseek-cli — the project lifecycle CLI (create, run, build, deploy, api, ctx, skills). Self-contained, installable with uv tool install agentseek-cli.
• agentseek — the harness itself. Provides the runtime CLI (chat, run, gateway, install, update, …) and the library you embed in your application. Install it with pip install agentseek, or use pip install 'agentseek[cli]' when you also want the lifecycle CLI in the same environment.

Already using Bub? AgentSeek is a distribution of Bub with opinionated defaults. Try agentseek create bub --template default. See How AgentSeek relates to Bub.

See Choosing an entry point for the full comparison.

Open-source course

"Deep Agents 实战" — a free course on building production-grade AI agents with LangChain / DeepAgents. All hands-on labs use AgentSeek.

Course site · Source repo

Topics covered: Agent Harness concepts, virtual filesystem, task planning, sub-agents, async delegation, long-term memory, Human-in-the-Loop, skills, sandboxes, streaming frontends, and production deployment.

Development skills

Installable guides that live inside your AI coding agent (Claude Code, Cursor, etc.):

Skill	What it does
langchain-dev-guide	LangChain / LangGraph engineering pitfalls and verified fixes. Covers DeepAgents, middleware, streaming, multi-agent orchestration.
langchain-cn-models	Step-by-step recipes for integrating Chinese LLM providers (DeepSeek, Qwen, GLM, Moonshot) into LangChain.

npx skills add ob-labs/agentseek --all

Full details: skills/

Connect your Agent Framework

AgentSeek is designed to be the harness underneath any Agent Framework. If you are building a new framework or maintaining one that needs a durable data layer and semantic context — we welcome you to connect it. Bub is a good example: it ships built-in as AgentSeek's native framework through exactly this pattern. AgentSeek brings the data substrate (OceanBase / seekdb / MySQL), the semantic context layer (ContextSeek), and production serving (agentseek-api) so you don't have to build those yourself.

The integration pattern follows agentseek-langchain — a contrib plugin that bridges your runnable into the harness. See Extension model and Author a contrib plugin. PRs to contrib/ welcome.

Templates

Templates are a growing collection — we are continuously adding new ones and polishing existing ones for both the LangChain and Bub families. PRs welcome.

Template	Description
langchain/markdown-messages	Pure LangChain chatbot, langgraph dev backend, markdown-rendered frontend.
langchain/default	LangChain + CopilotKit frontend + Feishu IM gateway + full agentseek runtime.
langchain/cli-remote	Remote LangGraph server bridged via LangGraphClientRunnable.
deepagents/research	DeepAgents research agent with Tavily search and streamed report UI.
deepagents/default	create_deep_agent bound to agentseek-langchain.
bub/default	Lightweight Bub agent with CopilotKit frontend, no LangChain.

See Templates reference for inputs, generated layout, and next steps.

Docker Compose

cp .env.example .env
make compose-up

See How to run with Docker Compose.

Documentation

• Home — suite overview, multi-persona quick starts
• Tutorials — quick demo, first app, skills and MCP
• How-to guides — task-focused recipes
• Explanation — LangChain relationship, Bub relationship, runtime data model
• Reference — env vars, CLI, packages, templates, Docker

More package docs:

• agentseek-langchain
• agentseek-tapestore-oceanbase
• agentseek-contextseek
• agentseek-schedule-sqlalchemy

How it works

• Suite of components — agentseek-cli, agentseek-api, ContextSeek, langchain-oceanbase. Use together or independently.
• Bub as the runtime kernel — Bub provides the hook-first turn pipeline, tape store, skills, plugins, and channel model. AgentSeek consumes Bub as a library dependency.
• LangChain bridge — the agentseek-langchain contrib plugin connects LangGraph runnables into the harness turn pipeline transparently.
• .agentseek runtime home — workspace-local config, plugin sandbox, and runtime state.
• Environment aliases — AGENTSEEK_* values act as fallbacks for matching BUB_* values.
• Open authoring model — AGENTS.md, project-local skills, and MCP config are first-class extension points.

For a good default experience from local development to larger deployments, we recommend OceanBase seekdb and OceanBase.

Development

make install
make check
make test
make docs-test

License

Apache-2.0