[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-2370":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":31,"readmeContent":32,"aiSummary":33,"trendingCount":16,"starSnapshotCount":16,"syncStatus":34,"lastSyncTime":35,"discoverSource":36},2370,"deepagents","langchain-ai\u002Fdeepagents","langchain-ai","The batteries-included agent harness.","https:\u002F\u002Fdocs.langchain.com\u002Fdeepagents",null,"Python",24477,3467,118,85,0,96,597,1826,475,120,"MIT License",false,"main",[26,5,27,28,29,30],"ai","langchain","langgraph","python","typescript","2026-06-12 04:00:14","\u003Cdiv align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Fdeepagents\u002Foverview#deep-agents-overview\">\n    \u003Cpicture>\n      \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\".github\u002Fimages\u002Flogo-dark.svg\">\n      \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\".github\u002Fimages\u002Flogo-light.svg\">\n      \u003Cimg alt=\"Deep Agents Logo\" src=\".github\u002Fimages\u002Flogo-dark.svg\" width=\"50%\">\n    \u003C\u002Fpicture>\n  \u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ch3>The batteries-included agent harness.\u003C\u002Fh3>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fopensource.org\u002Flicenses\u002FMIT\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fl\u002Fdeepagents\" alt=\"PyPI - License\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fpypistats.org\u002Fpackages\u002Fdeepagents\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpepy\u002Fdt\u002Fdeepagents\" alt=\"PyPI - Downloads\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Fdeepagents\u002F#history\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fdeepagents?label=%20\" alt=\"Version\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fx.com\u002Flangchain_oss\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Furl\u002Fhttps\u002Ftwitter.com\u002Flangchain_oss.svg?style=social&label=Follow%20%40LangChain\" alt=\"Twitter \u002F X\">\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cbr>\n\nDeep Agents is an agent harness. An opinionated, ready-to-run agent out of the box. Instead of wiring up prompts, tools, and context management yourself, you get a working agent immediately and customize what you need.\n\n**What's included:**\n\n- **Planning** — `write_todos` for task breakdown and progress tracking\n- **Filesystem** — `read_file`, `write_file`, `edit_file`, `ls`, `glob`, `grep` for reading and writing context\n- **Shell access** — `execute` for running commands (with sandboxing)\n- **Sub-agents** — `task` for delegating work with isolated context windows\n- **Smart defaults** — Prompts that teach the model how to use these tools effectively\n- **Context management** — Auto-summarization when conversations get long, large outputs saved to files\n\n> [!NOTE]\n> Looking for the JS\u002FTS library? Check out [deepagents.js](https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Fdeepagentsjs).\n\n## Quickstart\n\n```bash\npip install deepagents\n# or\nuv add deepagents\n```\n\n```python\nfrom deepagents import create_deep_agent\n\nagent = create_deep_agent()\nresult = agent.invoke({\"messages\": [{\"role\": \"user\", \"content\": \"Research LangGraph and write a summary\"}]})\n```\n\nThe agent can plan, read\u002Fwrite files, and manage its own context. Add tools, customize prompts, or swap models as needed.\n\n> [!TIP]\n> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https:\u002F\u002Fdocs.langchain.com\u002Flangsmith\u002Fhome).\n\n## Customization\n\nAdd your own tools, swap models, customize prompts, configure sub-agents, and more. See the [documentation](https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Fdeepagents\u002Foverview) for full details.\n\n```python\nfrom langchain.chat_models import init_chat_model\n\nagent = create_deep_agent(\n    model=init_chat_model(\"openai:gpt-4o\"),\n    tools=[my_custom_tool],\n    system_prompt=\"You are a research assistant.\",\n)\n```\n\nMCP is supported via [`langchain-mcp-adapters`](https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Flangchain-mcp-adapters).\n\n## Deep Agents CLI\n\nA pre-built coding agent in your terminal — similar to Claude Code or Cursor — powered by any LLM. One install command and you're up and running.\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"libs\u002Fcli\u002Fimages\u002Fcli.png\" alt=\"Deep Agents CLI\" width=\"600\"\u002F>\n\u003C\u002Fp>\n\n```bash\ncurl -LsSf https:\u002F\u002Flangch.in\u002Fgh-da-cli | bash\n```\n\n**Highlights:**\n\n- **Interactive TUI** — rich terminal interface with streaming responses\n- **Web search** — ground responses in live information\n- **Headless mode** — run non-interactively for scripting and CI\n- Plus all SDK features out of the box — remote sandboxes, persistent memory, custom skills, and human-in-the-loop approval\n\nSee the [CLI documentation](https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Fdeepagents\u002Fcli\u002Foverview) for the full feature set.\n\n## LangGraph Native\n\n`create_deep_agent` returns a compiled [LangGraph](https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Flanggraph\u002Foverview) graph. Use it with streaming, Studio, checkpointers, or any LangGraph feature.\n\n## FAQ\n\n### Why should I use this?\n\n- **100% open source** — MIT licensed, fully extensible\n- **Provider agnostic** — Works with any Large Language Model that supports tool calling, including both frontier and open models\n- **Built on LangGraph** — Production-ready runtime with streaming, persistence, and checkpointing\n- **Batteries included** — Planning, file access, sub-agents, and context management work out of the box\n- **Get started in seconds** — `uv add deepagents` and you have a working agent\n- **Customize in minutes** — Add tools, swap models, tune prompts when you need to\n\n---\n\n## Documentation\n\n- [docs.langchain.com](https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Fdeepagents\u002Foverview) – Comprehensive documentation, including conceptual overviews and guides\n- [reference.langchain.com\u002Fpython](https:\u002F\u002Freference.langchain.com\u002Fpython\u002Fdeepagents\u002F) – API reference docs for Deep Agents packages\n- [Chat LangChain](https:\u002F\u002Fchat.langchain.com\u002F) – Chat with the LangChain documentation and get answers to your questions\n\n**Discussions**: Visit the [LangChain Forum](https:\u002F\u002Fforum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.\n\n## Additional resources\n\n- **[Examples](examples\u002F)** — Working agents and patterns\n- [Contributing Guide](https:\u002F\u002Fdocs.langchain.com\u002Foss\u002Fpython\u002Fcontributing\u002Foverview) – Learn how to contribute to LangChain projects and find good first issues.\n- [Code of Conduct](https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Flangchain\u002F?tab=coc-ov-file) – Our community guidelines and standards for participation.\n\n---\n\n## Acknowledgements\n\nThis project was primarily inspired by Claude Code, and initially was largely an attempt to see what made Claude Code general purpose, and make it even more so.\n\n## Security\n\nDeep Agents follows a \"trust the LLM\" model. The agent can do anything its tools allow. Enforce boundaries at the tool\u002Fsandbox level, not by expecting the model to self-police. See the [security policy](https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Fdeepagents?tab=security-ov-file) for more information.\n","Deep Agents 是一个基于 LangChain 和 LangGraph 构建的 Python & TypeScript 代理框架，旨在简化复杂代理任务的开发。该项目提供了一个开箱即用的代理解决方案，内置了规划工具、文件系统后端以及创建子代理的能力，能够自动处理任务分解、文件读写和上下文管理等操作。它特别适用于需要快速搭建并自定义 AI 代理的应用场景，如自动化研究助手或数据处理流水线。通过简单的 API 调用即可启动一个功能完备的代理，并支持进一步定制化配置以满足特定需求。",2,"2026-06-11 02:49:39","top_language"]