docs: Nav reorg (#5236)

* docs: Nav consolidation

* nav

* reorg

* fix links

* fix

* prebuilts

* fix spelling

* reorg

* reorg
This commit is contained in:
Lauren Hirata Singh
2025-06-27 14:06:26 -04:00
committed by GitHub
parent 70894af72c
commit 83bbe42eab
7 changed files with 131 additions and 221 deletions
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@@ -111,6 +111,7 @@ REDIRECT_MAP = {
"concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
"how-tos/index.md": "index.md",
"tutorials/introduction.ipynb": "concepts/why-langgraph.md",
"agents/deployment.md": "tutorials/langgraph-platform/local-server.md",
# deployment redirects
"how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
"concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
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@@ -1,92 +0,0 @@
---
search:
boost: 2
tags:
- agent
hide:
- tags
---
# Deployment
To deploy your LangGraph agent, create and configure a LangGraph app. This setup supports both local development and production deployments.
Features:
* 🖥️ Local server for development
* 🧩 Studio Web UI for visual debugging
* ☁️ Cloud and 🔧 self-hosted deployment options
* 📊 LangSmith integration for tracing and observability
!!! info "Requirements"
- ✅ You **must** have a [LangSmith account](https://www.langchain.com/langsmith). You can sign up for **free** and get started with the free tier.
## Create a LangGraph app
```bash
pip install -U "langgraph-cli[inmem]"
langgraph new path/to/your/app --template new-langgraph-project-python
```
This will create an empty LangGraph project. You can modify it by replacing the code in `src/agent/graph.py` with your agent code. For example:
```python
from langgraph.prebuilt import create_react_agent
def get_weather(city: str) -> str:
"""Get weather for a given city."""
return f"It's always sunny in {city}!"
graph = create_react_agent(
model="anthropic:claude-3-7-sonnet-latest",
tools=[get_weather],
prompt="You are a helpful assistant"
)
```
### Install dependencies
In the root of your new LangGraph app, install the dependencies in `edit` mode so your local changes are used by the server:
```shell
pip install -e .
```
### Create an `.env` file
You will find a `.env.example` in the root of your new LangGraph app. Create
a `.env` file in the root of your new LangGraph app and copy the contents of the `.env.example` file into it, filling in the necessary API keys:
```bash
LANGSMITH_API_KEY=lsv2...
ANTHROPIC_API_KEY=sk-
```
## Launch LangGraph server locally
```shell
langgraph dev
```
This will start up the LangGraph API server locally. If this runs successfully, you should see something like:
> Ready!
>
> - API: [http://localhost:2024](http://localhost:2024/)
>
> - Docs: http://localhost:2024/docs
>
> - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
See this [tutorial](https://langchain-ai.github.io/langgraph/tutorials/langgraph-platform/local-server/) to learn more about running LangGraph app locally.
## LangGraph Studio Web UI
LangGraph Studio Web is a specialized UI that you can connect to LangGraph API server to enable visualization, interaction, and debugging of your application locally. Test your graph in the LangGraph Studio Web UI by visiting the URL provided in the output of the `langgraph dev` command.
> - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
## Deployment
Once your LangGraph app is running locally, you can deploy it using LangGraph Platform. Refer to the [deployment options guide](../concepts/deployment_options.md) for detailed instructions on all supported deployment models.
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@@ -8,9 +8,9 @@ hide:
- tags
---
# Agent development with LangGraph
# Agent development using prebuilt components
**LangGraph** provides both low-level primitives and high-level prebuilt components for building agent-based applications. This section focuses on the **prebuilt**, **reusable** components designed to help you construct agentic systems quickly and reliably—without the need to implement orchestration, memory, or human feedback handling from scratch.
LangGraph provides both low-level primitives and high-level prebuilt components for building agent-based applications. This section focuses on the prebuilt, ready-to-use components designed to help you construct agentic systems quickly and reliably—without the need to implement orchestration, memory, or human feedback handling from scratch.
## What is an agent?
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@@ -1,10 +1,10 @@
# Use the functional API
The [**Functional API**](../../concepts/functional_api.md) allows you to add LangGraph's key features — [persistence](../concepts/persistence.md), [memory](../how-tos/memory/add-memory.md), [human-in-the-loop](../concepts/human_in_the_loop.md), and [streaming](../concepts/streaming.md) — to your applications with minimal changes to your existing code.
The [**Functional API**](../concepts/functional_api.md) allows you to add LangGraph's key features — [persistence](../concepts/persistence.md), [memory](../how-tos/memory/add-memory.md), [human-in-the-loop](../concepts/human_in_the_loop.md), and [streaming](../concepts/streaming.md) — to your applications with minimal changes to your existing code.
!!! tip
For conceptual information on the functional API, see [Functional API](../../concepts/functional_api.md).
For conceptual information on the functional API, see [Functional API](../concepts/functional_api.md).
## Creating a simple workflow
@@ -1,4 +1,4 @@
# LangGraph Platform quickstart
# Run a local server
This guide shows you how to run a LangGraph application locally.
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@@ -92,38 +92,75 @@ nav:
- Get started:
- index.md
- Quickstarts:
- Agent: agents/agents.md
- LangGraph basics:
- Start with a prebuilt agent: agents/agents.md
- Build a custom workflow:
- concepts/why-langgraph.md
- Build a basic chatbot: tutorials/get-started/1-build-basic-chatbot.md
- tutorials/get-started/2-add-tools.md
- tutorials/get-started/3-add-memory.md
- Add human-in-the-loop: tutorials/get-started/4-human-in-the-loop.md
- tutorials/get-started/5-customize-state.md
- tutorials/get-started/6-time-travel.md
- Local server: tutorials/langgraph-platform/local-server.md
- Deployment: cloud/quick_start.md
- General concepts:
- Common patterns:
- Agent architectures: concepts/agentic_concepts.md
- Workflows & agents: tutorials/workflows.md
- Agent development: agents/overview.md
- Workflow orchestration:
- Graph API: concepts/low_level.md
- Subgraphs: concepts/subgraphs.md
- Runtime: concepts/pregel.md
- Functional API: concepts/functional_api.md
- 1. Build a basic chatbot: tutorials/get-started/1-build-basic-chatbot.md
- 2. Add tools: tutorials/get-started/2-add-tools.md
- 3. Add memory: tutorials/get-started/3-add-memory.md
- 4. Add human-in-the-loop: tutorials/get-started/4-human-in-the-loop.md
- 5. Customize state: tutorials/get-started/5-customize-state.md
- 6. Time travel: tutorials/get-started/6-time-travel.md
- Run a local server: tutorials/langgraph-platform/local-server.md
- Agent development:
- Workflows & agents: tutorials/workflows.md
- Prebuilt components: agents/overview.md
- Run an agent: agents/run_agents.md
- Agent architectures: concepts/agentic_concepts.md
- Guides:
- LangGraph APIs:
- Graph API:
- Overview: concepts/low_level.md
- Use the Graph API: how-tos/graph-api.ipynb
- Functional API:
- Overview: concepts/functional_api.md
- Use the Functional API: how-tos/use-functional-api.md
- Runtime: concepts/pregel.md
- Core capabilities:
- Streaming: concepts/streaming.md
- Persistence: concepts/persistence.md
- Durable execution: concepts/durable_execution.md
- Memory: concepts/memory.md
- Tools: concepts/tools.md
- Human-in-the-loop: concepts/human_in_the_loop.md
- Breakpoints: concepts/breakpoints.md
- Time travel: concepts/time-travel.md
- Multi-agent: concepts/multi_agent.md
- Platform capabilities:
- Streaming:
- Overview: concepts/streaming.md
- Stream outputs: how-tos/streaming.md
- Use Server API: cloud/how-tos/streaming.md
- Persistence:
- Overview: concepts/persistence.md
- Durable execution:
- Overview: concepts/durable_execution.md
- Memory:
- Overview: concepts/memory.md
- Add memory: how-tos/memory/add-memory.md
- Context:
- Add context: agents/context.md
- Models:
- Configure model: agents/models.md
- Tools:
- Overview: concepts/tools.md
- Call tools: how-tos/tool-calling.md
- Human-in-the-loop:
- Overview: concepts/human_in_the_loop.md
- Add human intervention: how-tos/human_in_the_loop/add-human-in-the-loop.md
- Use Server API: cloud/how-tos/add-human-in-the-loop.md
- Breakpoints:
- Overview: concepts/breakpoints.md
- Set breakpoints: how-tos/human_in_the_loop/breakpoints.md
- Use Server API: cloud/how-tos/human_in_the_loop_breakpoint.md
- Time travel:
- Overview: concepts/time-travel.md
- Use time travel: how-tos/human_in_the_loop/time-travel.md
- Use Server API: cloud/how-tos/human_in_the_loop_time_travel.md
- Subgraphs:
- Overview: concepts/subgraphs.md
- Use subgraphs: how-tos/subgraph.ipynb
- Multi-agent:
- Overview: concepts/multi_agent.md
- Prebuilt implementation: agents/multi-agent.md
- Custom implementation: how-tos/multi_agent.ipynb
- MCP:
- Use MCP: agents/mcp.md
- Server API: concepts/server-mcp.md
- Evaluation:
- Basic implementation: agents/evals.md
- Platform-only capabilities:
- LangGraph Platform:
- Overview: concepts/langgraph_platform.md
- Components:
@@ -133,107 +170,72 @@ nav:
- Data plane: concepts/langgraph_data_plane.md
- Control plane: concepts/langgraph_control_plane.md
- LangGraph CLI: concepts/langgraph_cli.md
- LangGraph Studio: concepts/langgraph_studio.md
- LangGraph Studio:
- Overview: concepts/langgraph_studio.md
- Quickstart: cloud/how-tos/studio/quick_start.md
- cloud/how-tos/invoke_studio.md
- cloud/how-tos/studio/manage_assistants.md
- cloud/how-tos/threads_studio.md
- cloud/how-tos/iterate_graph_studio.md
- cloud/how-tos/studio/run_evals.md
- cloud/how-tos/clone_traces_studio.md
- cloud/how-tos/datasets_studio.md
- LangGraph SDK: concepts/sdk.md
- Plans & pricing: concepts/plans.md
- Application structure: concepts/application_structure.md
- Scalability & resilience: concepts/scalability_and_resilience.md
- Authentication & access control: concepts/auth.md
- Assistants: concepts/assistants.md
- Double-texting: concepts/double_texting.md
- Webhooks: cloud/concepts/webhooks.md
- Cron jobs: cloud/concepts/cron_jobs.md
- Deployment:
- Overview: concepts/deployment_options.md
- Deployment options:
- Cloud SaaS: concepts/langgraph_cloud.md
- Self-Hosted Data Plane: concepts/langgraph_self_hosted_data_plane.md
- Self-Hosted Control Plane: concepts/langgraph_self_hosted_control_plane.md
- Standalone Container: concepts/langgraph_standalone_container.md
- Guides:
- LangGraph APIs:
- Use the Graph API: how-tos/graph-api.ipynb
- Use the Functional API: how-tos/use-functional-api.md
- Models:
- Configure model: agents/models.md
- Streaming:
- Stream outputs: how-tos/streaming.md
- Use Server API: cloud/how-tos/streaming.md
- Context:
- Add context: agents/context.md
- Memory:
- Add memory: how-tos/memory/add-memory.md
- Human-in-the-loop:
- how-tos/human_in_the_loop/add-human-in-the-loop.md
- Use Server API: cloud/how-tos/add-human-in-the-loop.md
- Time travel:
- how-tos/human_in_the_loop/time-travel.md
- Use Server API: cloud/how-tos/human_in_the_loop_time_travel.md
- Breakpoints:
- Set breakpoints: how-tos/human_in_the_loop/breakpoints.md
- Use Server API: cloud/how-tos/human_in_the_loop_breakpoint.md
- Tools:
- Call tools: how-tos/tool-calling.md
- Subgraphs:
- Use subgraphs: how-tos/subgraph.ipynb
- Multi-agent:
- Prebuilt implementation: agents/multi-agent.md
- Custom implementation: how-tos/multi_agent.ipynb
- MCP:
- Use MCP: agents/mcp.md
- Server API: concepts/server-mcp.md
- Evaluation:
- Basic implementation: agents/evals.md
- Deployment:
- Basic deployment: agents/deployment.md
- Set up your application:
- Use requirements.txt: cloud/deployment/setup.md
- Use pyproject.toml: cloud/deployment/setup_pyproject.md
- Use JavaScript: cloud/deployment/setup_javascript.md
- Use custom Docker: cloud/deployment/custom_docker.md
- Rebuild graph at runtime: cloud/deployment/graph_rebuild.md
- Deploy to production:
- Cloud SaaS: cloud/deployment/cloud.md
- Self-Hosted Data Plane: cloud/deployment/self_hosted_data_plane.md
- Self-Hosted Control Plane: cloud/deployment/self_hosted_control_plane.md
- Standalone Container: cloud/deployment/standalone_container.md
- Platform capabilities:
- LangGraph Studio:
- Quickstart: cloud/how-tos/studio/quick_start.md
- cloud/how-tos/invoke_studio.md
- cloud/how-tos/studio/manage_assistants.md
- cloud/how-tos/threads_studio.md
- cloud/how-tos/iterate_graph_studio.md
- cloud/how-tos/studio/run_evals.md
- cloud/how-tos/clone_traces_studio.md
- cloud/how-tos/datasets_studio.md
- Authentication & access control:
- how-tos/auth/custom_auth.md
- how-tos/auth/openapi_security.md
- Overview: concepts/auth.md
- how-tos/auth/custom_auth.md
- how-tos/auth/openapi_security.md
- Assistants:
- cloud/how-tos/configuration_cloud.md
- Threads: cloud/how-tos/use_threads.md
- Runs:
- cloud/how-tos/background_run.md
- cloud/how-tos/same-thread.md
- Overview: concepts/assistants.md
- cloud/how-tos/configuration_cloud.md
- Threads: cloud/how-tos/use_threads.md
- Runs:
- cloud/how-tos/background_run.md
- cloud/how-tos/same-thread.md
- cloud/how-tos/cron_jobs.md
- cloud/how-tos/stateless_runs.md
- cloud/how-tos/configurable_headers.md
- Double-texting:
- Overview: concepts/double_texting.md
- cloud/how-tos/interrupt_concurrent.md
- cloud/how-tos/rollback_concurrent.md
- cloud/how-tos/reject_concurrent.md
- cloud/how-tos/enqueue_concurrent.md
- Webhooks:
- Overview: cloud/how-tos/webhooks.md
- cloud/how-tos/webhooks.md
- Cron jobs:
- Overview: cloud/how-tos/cron_jobs.md
- cloud/how-tos/cron_jobs.md
- cloud/how-tos/stateless_runs.md
- cloud/how-tos/configurable_headers.md
- Double-texting:
- cloud/how-tos/interrupt_concurrent.md
- cloud/how-tos/rollback_concurrent.md
- cloud/how-tos/reject_concurrent.md
- cloud/how-tos/enqueue_concurrent.md
- Webhooks: cloud/how-tos/webhooks.md
- Cron jobs: cloud/how-tos/cron_jobs.md
- Server customization:
- how-tos/http/custom_lifespan.md
- how-tos/http/custom_middleware.md
- how-tos/http/custom_routes.md
- how-tos/http/custom_lifespan.md
- how-tos/http/custom_middleware.md
- how-tos/http/custom_routes.md
- Data management:
- Add semantic search: cloud/deployment/semantic_search.md
- Add TTLs: how-tos/ttl/configure_ttl.md
- Deployment:
- Overview: concepts/deployment_options.md
- Quickstart: cloud/quick_start.md
- Set up your application:
- Use requirements.txt: cloud/deployment/setup.md
- Use pyproject.toml: cloud/deployment/setup_pyproject.md
- Use JavaScript: cloud/deployment/setup_javascript.md
- Use custom Docker: cloud/deployment/custom_docker.md
- Rebuild graph at runtime: cloud/deployment/graph_rebuild.md
- Deployment options:
- Cloud SaaS: concepts/langgraph_cloud.md
- Self-Hosted Data Plane: concepts/langgraph_self_hosted_data_plane.md
- Self-Hosted Control Plane: concepts/langgraph_self_hosted_control_plane.md
- Standalone Container: concepts/langgraph_standalone_container.md
- Deploy to production:
- Cloud SaaS: cloud/deployment/cloud.md
- Self-Hosted Data Plane: cloud/deployment/self_hosted_data_plane.md
- Self-Hosted Control Plane: cloud/deployment/self_hosted_control_plane.md
- Standalone Container: cloud/deployment/standalone_container.md
- Reference:
- reference/index.md
@@ -263,7 +265,6 @@ nav:
- Environment variables: cloud/reference/env_var.md
- Examples:
- agents/run_agents.md
- Template applications: concepts/template_applications.md # TODO: make tutorial
- Agentic RAG: tutorials/rag/langgraph_agentic_rag.ipynb
- Agent Supervisor: tutorials/multi_agent/agent_supervisor.ipynb
Generated
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@@ -2590,7 +2590,7 @@ wheels = [
[[package]]
name = "langgraph"
version = "0.5.0rc1"
version = "0.5.0"
source = { editable = "../libs/langgraph" }
dependencies = [
{ name = "langchain-core" },
@@ -2894,7 +2894,7 @@ test = [
[[package]]
name = "langgraph-prebuilt"
version = "0.5.0rc0"
version = "0.5.1"
source = { editable = "../libs/prebuilt" }
dependencies = [
{ name = "langchain-core" },
@@ -2925,7 +2925,7 @@ dev = [
[[package]]
name = "langgraph-sdk"
version = "0.1.70"
version = "0.1.72"
source = { editable = "../libs/sdk-py" }
dependencies = [
{ name = "httpx" },