landing page

pipeline/core/builder.py

@@ -685,6 +685,10 @@ def is_shared_file(self, file_path: Path) -> bool:
         if file_path.name == "docs.json":
             return True
 
+        # index.mdx at root should be shared
+        if file_path.name == "index.mdx" and len(relative_path.parts) == 1:
+            return True
+
         # Images directory should be shared
         if "images" in relative_path.parts:
             return True

src/docs.json

@@ -10,8 +10,7 @@
   },
   "logo": {
     "light": "/images/brand/langchain-docs-teal.svg",
-    "dark": "/images/brand/langchain-docs-lilac.svg",
-    "href": "https://docs.langchain.com/oss/python"
+    "dark": "/images/brand/langchain-docs-lilac.svg"
   },
   "favicon": {
     "light": "/images/brand/docs-favicon.svg",
@@ -131,6 +130,14 @@
       {
         "version": "Python",
         "dropdowns": [
+          {
+            "dropdown": "Home",
+            "icon": "house",
+            "description": "LangChain docs home",
+            "pages": [
+              "index"
+            ]
+          },
           {
             "dropdown": "OSS (v1-alpha)",
             "icon": "link",
@@ -1149,6 +1156,14 @@
       {
         "version": "JavaScript",
         "dropdowns": [
+          {
+            "dropdown": "Home",
+            "icon": "house",
+            "description": "LangChain docs home",
+            "pages": [
+              "index"
+            ]
+          },
           {
             "dropdown": "OSS (v1-alpha)",
             "icon": "link",

src/hide-version-picker.js

@@ -15,7 +15,9 @@
         body.classList.remove('hide-version-picker');
 
         // Add appropriate class based on URL
-        if (currentPath.includes('/langgraph-platform/') || currentPath.includes('/langgraph-platform')) {
+        if (currentPath === '/' || currentPath === '/index') {
+            body.classList.add('hide-version-picker');
+        } else if (currentPath.includes('/langgraph-platform/') || currentPath.includes('/langgraph-platform')) {
             body.classList.add('hide-version-picker');
         } else if (currentPath.match(/\/labs(?:\/|$)/)) {
             body.classList.add('hide-version-picker');

src/index.mdx

@@ -1,62 +1,115 @@
 ---
-title: LangChain docs home
-sidebarTitle: Home
-description: "The platform for reliable agents"
-mode: "wide"
+title:
+sidebarTitle: All docs
+mode: "center"
 ---
 
+# The agent engineering platform
 
-# Frameworks
+Tools for every step of the agent development lifecycle. Ship reliable agents fast with open source frameworks for building agents, and our commercial platform LangSmith for observing, evaluating, and deploying agents.
+
+## Get started
+
+<CardGroup cols={4}>
+<Card title="Send your first trace" icon="monitor-waveform" href="/langsmith/integrations" cta="Get started" />
+
+<Card title="Build your first agent" icon="gear" href="/oss/python/langchain/quickstart" cta="Get started" />
+
+<Card title="Build an advanced agent" icon="gears" href="/oss/python/langgraph/quickstart" cta="Get started"/>
+
+<Card title="Sign up for LangSmith" icon="screwdriver-wrench" href="https://smith.langchain.com/" cta="Try LangSmith" />
+
+</CardGroup>
+
+## Open source agent frameworks
+
+<Tabs>
+<Tab title="Python" icon="python">
 
 <CardGroup cols={2}>
     <Card
-        title="LangChain - Python"
-        href="https://python.langchain.com/docs/introduction/"
+        title="LangChain"
+        href="/oss/python/langchain/overview"
+        icon="link"
+        cta="Learn more"
+    >
+    Get started quickly with pre-built agent architectures and standard integrations for swapping model providers.
+    </Card>
+
+    <Card
+        title="LangGraph"
+        href="/oss/python/langgraph/overview"
+        icon="circle-nodes"
+        cta="Learn more"
     >
-  Open-source framework for developing applications powered by large language models (LLMs).
+    Control every step of your custom agent with low-level orchestration, memory, and human-in-the-loop support.
     </Card>
 
+</CardGroup>
+
+</Tab>
+<Tab title="JavaScript" icon="js">
+<CardGroup cols={2}>
     <Card
-        title="LangChain - JavaScript"
-        href="https://js.langchain.com/docs/introduction/"
+        title="LangChain"
+        href="/oss/javascript/langchain/overview"
+        icon="link"
+        cta="Learn more"
     >
-  Open-source framework for developing applications powered by large language models (LLMs).
+    Get started quickly with pre-built agent architectures and standard integrations for swapping model providers.
     </Card>
 
     <Card
         title="LangGraph"
-        href="/oss/python"
+        href="/oss/javascript/langgraph/overview"
+        icon="circle-nodes"
+        cta="Learn more"
     >
-  Low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
+    Control every step of your custom agent with low-level orchestration, memory, and human-in-the-loop support.
     </Card>
 
 </CardGroup>
+</Tab>
+</Tabs>
 
-# Platforms
+## LangSmith offerings
 
 <CardGroup cols={2}>
     <Card
-        title="LangGraph Platform"
-        href="/langgraph-platform/"
+        title="Observability"
+        href="/langsmith/observability"
+        icon="magnifying-glass"
+        cta="Learn more"
     >
-    Commercial platform for developing, deploying, and scaling long-running agents and worflows.
+    See exactly how your agent thinks and acts with detailed tracing and aggregate trend metrics.
     </Card>
 
     <Card
-        title="LangSmith"
-        href="https://docs.smith.langchain.com/"
+        title="Evaluation"
+        href="/langsmith/evaluation"
+        icon="chart-simple"
+        cta="Learn more"
     >
-    Observability and evals platform for debugging, testing, and monitoring any AI application.
+    Test and score agent behavior on production data or offline datasets to continuously improve performance.
     </Card>
-</CardGroup>
 
-# Experimental
+    <Card
+        title="Prompt Engineering"
+        href="/langsmith/prompt-engineering"
+        icon="terminal"
+        cta="Learn more"
+    >
+    Iterate on prompts with version control, auto-generated prompt improvement, and collaboration features.
+    </Card>
 
-<CardGroup cols={2}>
     <Card
-        title="LangChain Labs"
-        href="/labs"
+        title="Deployment"
+        href="/langgraph-platform"
+        icon="rocket-launch"
+        cta="Learn more"
     >
-    A collection of agents and experimental AI products.
+    Ship your agent in one click with infrastructure built for long-running tasks and human oversight.
     </Card>
+
 </CardGroup>
+

src/labs/swe/index.mdx

@@ -3,7 +3,7 @@ title: "Introduction"
 description: "An introduction to Open SWE"
 ---
 
-Open SWE is an open-source cloud-based coding agent built with [LangGraph](https://docs.langchain.com/oss/javascript/langgraph/overview). It's designed to autonomously understand, plan, and execute code changes across entire repositories.
+Open SWE is an open source cloud-based coding agent built with [LangGraph](https://docs.langchain.com/oss/javascript/langgraph/overview). It's designed to autonomously understand, plan, and execute code changes across entire repositories.
 
 ## How It Works
 

src/oss/langchain/overview.mdx

@@ -23,9 +23,11 @@ For the latest stable version, see the [v0 LangChain](https://js.langchain.com/d
 </Warning>
 :::
 
-LangChain is the easiest way to start building with LLMs, letting you get started on building agents with OpenAI, Anthropic, Google, and [more](/oss/integrations/providers) in under 10 lines of code.
+LangChain is the easiest way to start building agents and applications powered by LLMs. With under 10 lines of code, you can connect to OpenAI, Anthropic, Google, and [more](/oss/integrations/providers). LangChain provides pre-built agent architectures and model integrations to help you get started quickly and seamlessly incorporate LLMs into your agents and applications.
 
-LangChain [agents](/oss/langchain/agents) are built on top of [LangGraph](/oss/langgraph/overview) in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. You do not need to know LangGraph for basic LangChain agent usage.
+We recommend you use LangChain to build common agents that loop LLM and tool calls, like SQL agents, RAG and document analysis, and simple customer support chatbots. Use [LangGraph](/oss/langgraph/overview), our low-level agent orchestration framework and runtime, when you have more advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency.
+
+LangChain [agents](/oss/langchain/agents) are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. You do not need to know LangGraph for basic LangChain agent usage.
 
 ## <Icon icon="download" size={20} /> Install
 

src/oss/langgraph/overview.mdx

@@ -7,13 +7,13 @@ import AlphaCallout from '/snippets/alpha-lg-callout.mdx';
 
 <AlphaCallout />
 
-Trusted by companies shaping the future of agents - including Klarna, Replit, Elastic, and more - LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
+Trusted by companies shaping the future of agents-- including Klarna, Replit, Elastic, and more-- LangGraph is a low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents.
 
-LangGraph is very low-level, and focused entirely on agent **orchestration**. Before using LangGraph, it is recommended you familiarize yourself with some of the components used to build agents, starting with [models](/oss/langchain/models) and [tools](/oss/langchain/tools). We will commonly use [LangChain](/oss/langchain/overview) components throughout the documentation, but you don't need to use LangChain to use LangGraph.
+LangGraph is very low-level, and focused entirely on agent **orchestration**. Before using LangGraph, we recommend you familiarize yourself with some of the components used to build agents, starting with [models](/oss/langchain/models) and [tools](/oss/langchain/tools).
 
-If you are just getting started with agents, or want a higher level abstraction, it is recommended that you use LangChain's [agents](/oss/langchain/agents).
+We will commonly use [LangChain](/oss/langchain/overview) components throughout the documentation to integrate models and tools, but you don't need to use LangChain to use LangGraph. If you are just getting start with agents or want a higher level abstraction, we recommend you use LangChain's [agents](/oss/langchain/agents) that provide pre-built architectures for common LLM and tool calling loops.
 
-LangGraph is focused on the underlying capabilties important for agent orchestration: durable execution, streaming, human-in-the-loop, etc. We expose two different APIs for consuming these capabilities: a Graph API and a functional API. We largely use the Graph API throughout the documentation, but feel free to use the functional API if you'd prefer.
+LangGraph is focused on the underlying capabilities important for agent orchestration: durable execution, streaming, human-in-the-loop, and more.
 
 ## <Icon icon="download" size={20} /> Install