用 LangChain.js、TypeScript 和 Azure 快速搭建无服务器 RAG 聊天机器人，省去自己拼装检索与生成链路的麻烦。
一套面向 AI 工程师的学习路线与实战资料，覆盖数据结构、深度学习、LangChain/LangGraph 智能体、LLM 推理与评测等主题，帮你系统补齐从算法到落地的知识。
用 LangChain.js、LlamaIndex.TS 和微软 Agent Framework 编排多个 AI 智能体，通过 MCP 协作，演示可部署到 Azure 容器应用的企业级旅行应用。
基于 React 19 + FastAPI + LangChain/LangGraph 的 AI 修图智能体，用自然语言驱动 21 种编辑工具完成抠图、图层拆分、区域编辑和文生图，配套教程带你一周掌握 AI Agent 全栈开发。
- Preserve LangGraph Store key escaping, empty-index handling and backend write/list error handling ( 7038) - Preserve Unicode archive query constraints in text
Changes since langchain-typesafe==0.0.1 release(typesafe): 0.0.2 ( 41720) feat(typesafe): accept a classifier in experimental middleware ( 41657)
Changes since langchain-core==1.7.5 release(core): 1.7.6 ( 41698) perf(core): merge streamed AIMessageChunk s once when accumulating runnable streams ( 41697) perf(core):
Changes since langchain-openai==1.7.3 release(openai): 1.7.4 ( 41683) chore(deps): require langchain-core =1.7.5 for refusal handling ( 41682) feat(core): standardize mod
Initial release release(typesafe): 0.0.1 ( 41650) chore(infra): relax third-party dependency upper bounds ( 41407) chore(deps): bump certifi from 2026.7.22 to 2
…ding images by @dliubarskyi in https://github.com/langchain4j/langchain4j/pull/6659 Introduce Confidence Cascade agentic pattern by @mariofusco in https://github.com/lang