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健康状态 健康来源类型 研究原文权限 允许原文最近入库 2026-09-25ID langchain-blog运行状态 已启用

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最新公开文章

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.

LangChain Blog站内正文待翻译:Building Production Agents with Jev and LangGraph

待翻译:New in LangSmith: Engine v2, Managed Deep Agents, Fine-Tuning, 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: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.

LangChain Blog站内正文待翻译:New in LangSmith: Engine v2, Managed Deep Agents, Fine-Tuning, and more

待翻译:LangSmith Custom Apps: Build custom interfaces around your agent data

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.

LangChain Blog站内正文待翻译:LangSmith Custom Apps: Build custom interfaces around your agent data

待翻译:Introducing LangSmith Fine-Tuning

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.

LangChain Blog站内正文待翻译:Introducing LangSmith Fine-Tuning

待翻译:Trajectories now in LangSmith: A readable view of every agent session

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.

LangChain Blog站内正文待翻译:Trajectories now in LangSmith: A readable view of every agent session

待翻译:New in LangSmith Engine: red teaming and automated testing

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.

LangChain Blog站内正文待翻译:New in LangSmith Engine: red teaming and automated testing

待翻译:Managed Deep Agents delivers a better user experience for agents 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: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.

LangChain Blog站内正文待翻译:Managed Deep Agents delivers a better user experience for agents in production

待翻译:The Reliability Layer for Healthcare AI: Common LangSmith Use Cases

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.

LangChain Blog站内正文待翻译:The Reliability Layer for Healthcare AI: Common LangSmith Use Cases

待翻译:Jev-as-a-Judge Is Now Available in LangSmith

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.

LangChain Blog站内正文待翻译:Jev-as-a-Judge Is Now Available in LangSmith

待翻译:Can Jev Be a Better Agent Evaluator?

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.

LangChain Blog站内正文待翻译:Can Jev Be a Better Agent Evaluator?

待翻译:Building a Harness with Jev

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…

LangChain Blog站内正文待翻译:Building a Harness with Jev

待翻译:Building an Agent Harness for Life Sciences: Introducing Deep Life Sci

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.

LangChain Blog站内正文待翻译:Building an Agent Harness for Life Sciences: Introducing Deep Life Sci

待翻译:How Included Health Built Federated Healthcare Agents with LangGraph and Deep Agents

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.

LangChain Blog站内正文待翻译:How Included Health Built Federated Healthcare Agents with LangGraph and Deep Agents

待翻译:Scaling Agents in Healthcare & Life Sciences: Lessons from Madrigal Pharmaceuticals, Abridge, and Vizient

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.

LangChain Blog站内正文待翻译:Scaling Agents in Healthcare & Life Sciences: Lessons from Madrigal Pharmaceuticals, Abridge, and Vizient

待翻译:How We Built LangChain’s Paid Media Agent

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.

LangChain Blog站内正文待翻译:How We Built LangChain’s Paid Media Agent

待翻译:How Credit Genie keeps codebase docs fresh with OpenWiki

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.

LangChain Blog站内正文待翻译:How Credit Genie keeps codebase docs fresh with OpenWiki

待翻译:Connections: managed credentials and per-caller identity for Managed Deep Agents

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.

LangChain Blog站内正文待翻译:Connections: managed credentials and per-caller identity for Managed Deep Agents

多智能体框架中的上下文组织

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。

LangChain Blog站内正文多智能体框架中的上下文组织

待翻译:August 2026: LangChain Newsletter — Managed Deep Agents, LLM Gateway, 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: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.

LangChain Blog站内正文待翻译:August 2026: LangChain Newsletter — Managed Deep Agents, LLM Gateway, and More

待翻译:LangChain State of AI 2024 Report

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.

LangChain Blog站内正文待翻译:LangChain State of AI 2024 Report

待翻译:LangChain's Second Birthday

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.

LangChain Blog站内正文待翻译:LangChain's Second Birthday

待翻译:How Podium optimized agent behavior and reduced engineering intervention by 90% with LangSmith

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%.

LangChain Blog站内正文待翻译:How Podium optimized agent behavior and reduced engineering intervention by 90% with LangSmith

待翻译:Announcing LangGraph v0.1 & LangGraph Cloud: Running agents at scale, reliably

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.

LangChain Blog站内正文待翻译:Announcing LangGraph v0.1 & LangGraph Cloud: Running agents at scale, reliably

待翻译:LangChain Announces Enterprise Agentic AI Platform Built 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:Build, deploy, and monitor production-grade AI agents at scale with LangChain's enterprise agentic AI platform integrated with NVIDIA.

LangChain Blog站内正文待翻译:LangChain Announces Enterprise Agentic AI Platform Built with NVIDIA

待翻译:AI Agent Latency 101: How do I speed up my AI agent?

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.

LangChain Blog站内正文待翻译:AI Agent Latency 101: How do I speed up my AI agent?

待翻译:Evaluating OpenWiki with WikiBench

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.

LangChain Blog站内正文待翻译:Evaluating OpenWiki with WikiBench

待翻译:OpenAI's Bet on a Cognitive Architecture

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.

LangChain Blog站内正文待翻译:OpenAI's Bet on a Cognitive Architecture

待翻译:Meet Connery: An Open-Source Plugin Infrastructure for OpenGPTs and LLM apps

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.

LangChain Blog站内正文待翻译:Meet Connery: An Open-Source Plugin Infrastructure for OpenGPTs and LLM apps

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