datawhalechina/deepagents-in-action resource
📚 《Deep Agents 实战》—— LangChain 官方大使出品，基于 LangChain / LangGraph 生态，从零构建生产级 AI Agent 的完整指南 observed · 2026-08-28
Health v2 · maintenance only
58/100
- Activity 99
- Release rhythm 35
- Longevity 8
Flags: no_releases young no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 120
- days_rel: n/a
- days_push: 8
- n_releases_24m: 0
Adoption not part of the score
1790 stars · 180 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
An open-source Chinese-language course ('Deep Agents 实战') that teaches building production-grade AI agents with the LangChain/LangGraph Deep Agents SDK. It includes 16 chapters with lectures, videos, and hands-on labs covering planning, subagents, memory, human-in-the-loop, sandboxing, MCP, and streaming.
Use cases
- learn to build production AI agents with LangGraph
- understand context engineering for agents
- build multi-agent systems with subagents
- add long-term memory to an AI agent
- run agent code safely in a sandbox
- extend agents with MCP tools
- debug LangChain apps with LangSmith traces
When to choose
- you want a structured, chapter-by-chapter guide to the Deep Agents SDK
- you prefer Chinese-language tutorials with video and labs
- you are moving from agent frameworks to production agent harnesses
When to avoid
- you need a ready-to-use agent application rather than a course
- you need English-only material
- you want content under a permissive code license (content is CC BY-NC-SA)
Facets
learning-resource · maturity active
agent-framework developer-tools mcp rag artificial-intelligence large-language-models tutorials developer-tools python cross-platform deepagents langchain langgraph context-engineering chinese course tutorial agentic-ai sandbox astro ai-agents
2 sources
- readme: https://github.com/datawhalechina/deepagents-in-action · fetched 2026-08-28 · 43808235d960
- homepage: https://datawhalechina.github.io/deepagents-in-action/ · fetched 2026-08-29 · fd747297fea3
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| datawhalechina/deepagents-in-action | main | 58 |
For agents
markdown · JSON · MCP: product_card(name="datawhalechina/deepagents-in-action")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem