deepagents/examples/README.md

Examples

Real agents and patterns built on Deep Agents.

Featured

Deep Agents Code A pre-built coding Deep Agent in your terminal — similar to Claude Code or Codex — powered by any LLM. Includes an interactive TUI, web search, remote sandboxes, persistent memory, custom skills, and human-in-the-loop approval. curl -LsSf https://langch.in/dcode | bash Source · Docs

Open SWE An open-source, async coding agent for your org's internal workflows. Runs each task in an isolated cloud sandbox, integrates with Slack, Linear, and GitHub, and ships PRs end-to-end. @open-swe fix this user-reported bug plz! Repository · Blog post

In the wild

Production agents powered by the LangChain stack:

Project	Description
LangSmith Fleet	No-code platform for building AI agents from templates; connect your accounts and let the agent handle routine work
Chat LangChain	Documentation assistant that answers questions about LangChain, LangGraph, and LangSmith (source)

All examples

Research

Example	Description
Deep Research	Multi-step web research with Tavily, parallel sub-agents, and strategic reflection
MCP Docs Agent	Docs research agent using MCP tools over LangChain documentation

Coding

Example	Description
Coding Agent	Autonomous coding agent in a LangSmith sandbox
Nemotron Research Agent	NVIDIA Nemotron Super for research + GPU-accelerated execution via RAPIDS

Content

Example	Description
Content Builder	Blog posts, LinkedIn posts, and tweets with memory (AGENTS.md), skills, and subagents
Text-to-SQL	Natural language to SQL with planning and skill-based workflows on the Chinook demo database
LLM Wiki	Script-first LLM wiki synced via langsmith hub init/pull/push

Deployable services

Example	Description
Content Writer	Content writer with per-user memory and Supabase auth
GTM Strategist	GTM strategy agent coordinating sync and async subagents
Async Subagent Server	Self-hosted Agent Protocol server exposing a researcher as an async subagent

Advanced patterns

Example	Description
Ralph Loop	Autonomous looping with fresh context each iteration, using the filesystem for persistence
Agents as Folders	Download a zip, unzip, and run
Better Harness	Eval-driven outer-loop optimization of a Deep Agents harness

Each example has its own README with setup instructions.

Contributing an example

See the Contributing Guide for general contribution guidelines.

When adding a new example:

• Use uv for dependency management with a pyproject.toml and uv.lock (commit the lock file)
• Pin to deepagents version — use a version range (e.g., >=0.3.5,<0.4.0) in dependencies
• Include a README with clear setup and usage instructions
• Add tests for reusable utilities or non-trivial helper logic
• Keep it focused — each example should demonstrate one use-case or workflow
• Follow the structure of existing examples (see deep_research/ or text-to-sql-agent/ as references)

Resources

• LangChain Academy — Comprehensive, free courses on LangChain libraries and products, made by the LangChain team.
• Code of Conduct — community guidelines and standards