待翻譯:Building Production Agents with Jev and LangGraph
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how LangGraph orchestrates Jev, TypeSafe AI's decision model, to build faster, cheaper production agents.
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AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how LangGraph orchestrates Jev, TypeSafe AI's decision model, to build faster, cheaper production agents.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:LangChain announced new updates to LangSmith. Updates include Engine v2 with red teaming and automatic testing, a new version of Managed Deep Agents, trajectories and more.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:LangSmith Custom Apps lets you build the interface you want with your LangSmith data, publish it into your workspace, and skip the hosting, auth, and permissions work. Learn more.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:LangChain introduces LangSmith Fine-Tuning and SmithTune, a CLI built for post-training models. Train specialized models without building data pipelines by hand.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Trajectories in LangSmith provide a conversational view of an agent session. Trajectories make trace data easy to navigate and speed up debugging for long-running agents.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:LangSmith Engine now includes Red Teaming to proactively detect agent issues and automated agent testing. Learn more about the Engine v2 release.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Managed Deep Agents is the simplest way to build, deploy, and run agents in production. The 0.8 release adds support for user-owned credentials, user-level memory, HTTP channels, file transfer in Slack and a pre-built tool for web search.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how LangSmith helps healthcare AI teams turn clinical review into reusable evaluators, datasets, and release gates for safer AI in production.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Use Jev as a judge for LangSmith evals to evaluate agent traces with faster, cheaper structured feedback across production runs, datasets, and regression tests.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:We tested Jev against LLM judges on accuracy, repeatability, latency, and cost to see whether System One models could offer a new approach to agent evaluation.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Open Source Agent Architecture LangChain Building a Harness with Jev September 17, 2026 5 min Go back to blog Create agents Agents run in a loop: an LLM decides what to do, a tool executes, a model evaluates the results…
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Deep Life Sci is LangChain's open source agentic assistant for clinical and lab scientists. It pulls from 600K+ ClinicalTrials.gov studies, 29M PubMed abstracts, and 12M PubMed Central full-text articles, with sandboxed sub-agents for real data analysis.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how Included Health used Deep Agents, LangGraph, and LangSmith to build Dot, a federated healthcare navigation agent with human handoff and clinical oversight.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Agent programs in healthcare and life sciences are being built under a different set of constraints than those in most industries. There’s plenty of upside if the constraints can be resolved. Success can mean hours of manual review compressed into minutes, data spread across a dozen systems finally queryable in one place, and clinicians getting time back from documentation. At the same time, the cost of a wrong answer can be higher here than almost anywhere else, which changes how teams build.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:How LangChain built a paid media agent to analyze campaign performance, optimize ads, propose changes, and turn marketing data into action.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how Credit Genie uses OpenWiki to automate repo documentation, reduce tribal knowledge, and give engineers and coding agents searchable codebase context.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Learn how Connections in Managed Deep Agents securely manage credentials, support per-user OAuth, and let agents act with each caller’s identity.
deepagents 為子代理引入“上下文模式”(isolated / fork),讓主管代理既可以委派任務,又可以決定子代理繼承多少上下文。fork 模式繼承主管的會話歷史,可複用 prompt caching、減少重複工作;isolated 模式則讓子代理在全新上下文中獨立完成任務。文章還透過 worker、verifier、researcher、memory 四類子代理說明如何選擇。
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Managed Deep Agents and LLM Gateway hit public beta, plus Deep Agents v0.7, Tuned Evaluators, Bring Your Own Cloud on AWS, and LangSmith Engine upgrades.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Dive into LangSmith product usage patterns that show how the AI ecosystem and the way people are building LLM apps is evolving.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Reflections on how LangChain has evolved — including our products, ecosystem, and community — over the past two years, and where we're headed next.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:See how Podium tests across the lifecycle development of their AI employee agent, using LangSmith for dataset curation and finetuning. They improved agent F1 response quality to 98% and reduced the need for engineering intervention by 90%.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Our new infrastructure for running agents at scale, LangGraph Cloud, is available in beta. We also have a new stable release of LangGraph.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Build, deploy, and monitor production-grade AI agents at scale with LangChain's enterprise agentic AI platform integrated with NVIDIA.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Learn proven strategies to speed up your AI agent: reduce latency, optimize LLM calls, enable parallelism, and improve UX. Expert tips from LangChain.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:LangGraph Platform, our infrastructure for deploying and managing agents at scale, is now generally available. Learn how to deploy
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:We raised $125M at a $1.25B valuation to build the platform for agent engineering.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:We built WikiBench to test whether generated wikis help coding agents. Pairing a wiki with source code scored higher than source alone, at lower cost.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Why LangChain believes in open, customizable cognitive architectures over closed systems. Build reliable LLM agents with OpenGPTs and LangSmith.
AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Discover Connery: open-source plugin infrastructure for LLM apps. Secure integrations, personalization, and human-in-the-loop control for AI agents.