待翻译:Building Production Agents with Jev and LangGraph
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:See how LangGraph orchestrates Jev, TypeSafe AI's decision model, to build faster, cheaper production agents.
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AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:See how LangGraph orchestrates Jev, TypeSafe AI's decision model, to build faster, cheaper production agents.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:LangChain introduces LangSmith Fine-Tuning and SmithTune, a CLI built for post-training models. Train specialized models without building data pipelines by hand.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:LangSmith Engine now includes Red Teaming to proactively detect agent issues and automated agent testing. Learn more about the Engine v2 release.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:See how LangSmith helps healthcare AI teams turn clinical review into reusable evaluators, datasets, and release gates for safer AI in production.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:How LangChain built a paid media agent to analyze campaign performance, optimize ads, propose changes, and turn marketing data into action.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:See how Credit Genie uses OpenWiki to automate repo documentation, reduce tribal knowledge, and give engineers and coding agents searchable codebase context.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Learn how Connections in Managed Deep Agents securely manage credentials, support per-user OAuth, and let agents act with each caller’s identity.
deepagents 为子代理引入“上下文模式”(isolated / fork),让主管代理既可以委派任务,又可以决定子代理继承多少上下文。fork 模式继承主管的会话历史,可复用 prompt caching、减少重复工作;isolated 模式则让子代理在全新上下文中独立完成任务。文章还通过 worker、verifier、researcher、memory 四类子代理说明如何选择。
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Dive into LangSmith product usage patterns that show how the AI ecosystem and the way people are building LLM apps is evolving.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Reflections on how LangChain has evolved — including our products, ecosystem, and community — over the past two years, and where we're headed next.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Our new infrastructure for running agents at scale, LangGraph Cloud, is available in beta. We also have a new stable release of LangGraph.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Build, deploy, and monitor production-grade AI agents at scale with LangChain's enterprise agentic AI platform integrated with NVIDIA.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Learn proven strategies to speed up your AI agent: reduce latency, optimize LLM calls, enable parallelism, and improve UX. Expert tips from LangChain.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:LangGraph Platform, our infrastructure for deploying and managing agents at scale, is now generally available. Learn how to deploy
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:We raised $125M at a $1.25B valuation to build the platform for agent engineering.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译: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 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Why LangChain believes in open, customizable cognitive architectures over closed systems. Build reliable LLM agents with OpenGPTs and LangSmith.
AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Discover Connery: open-source plugin infrastructure for LLM apps. Secure integrations, personalization, and human-in-the-loop control for AI agents.