LangSmith Deployment is a workflow orchestration runtime purpose-built for agent workloads. It provides the managed infrastructure agents need to run reliably in production at scale, supporting the full lifecycle from local development to deployment.Documentation Index
Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
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Deployable products
LangSmith Deployment is framework-agnostic which means you can deploy agents built with:Deep Agents
Use the Deep Agents CLI to deploy a deep agent to LangSmith Cloud.
LangGraph (and LangChain)
Use the LangGraph CLI and app templates to deploy a LangGraph application to LangSmith.
Other frameworks
Use the LangGraph Functional API to deploy Strands, CrewAI, and other agent frameworks.
Deployment environments
You can run the same Agent Server runtime in several hosting models. A standalone server is the lightest option: you run containers yourself without the LangSmith control plane. For managed deployments through the UI and APIs, use Cloud or Self-hosted (full platform in your infrastructure).Cloud
Fully managed by LangChain. Create deployments from GitHub in the LangSmith UI or with
langgraph deploy. Requires a Plus plan or above.Standalone server
Deploy Agent Server with Docker, Compose, or Kubernetes. Bring your own PostgreSQL, Redis, and LangSmith license; no control plane. Optional LangSmith tracing to Cloud or a self-hosted instance.
Self-hosted
Run the full LangSmith platform, including the control plane and data plane, in your cloud (for example on Kubernetes). Requires Enterprise plan. Integrates observability, evaluation, and agent deployment in one private stack.
Deployment capabilities
Once an agent is deployed, you work with Agent Server’s execution model: assistants for configuration, threads for state, and runs for workloads.Core capabilities
Stream to users, pause for human review, handle concurrent input, and connect via MCP and A2A.
Studio
Use an interactive environment for developing and debugging agents.
Advanced configuration
Authentication, encryption, custom routes, and short- and long-term memory stores.
Agent composition
RemoteGraph lets any agent call other deployed agents with MCP and A2A.
Reference & operations
Tutorials
- Collect user feedback for Agent Server runs: Attach end-user feedback to runs and traces
- Deploy other frameworks (e.g., Strands, CrewAI): Wrap existing agents with Functional API and deploy
- Implement generative user interfaces with LangGraph: Stream UI elements to a React client
- Implement a CI/CD pipeline: Automate tests, evaluations, and deployments with GitHub Actions
Securing and customizing your server
- Custom auth: Authentication and multi-tenant access control
- Server customization: Custom routes, middleware, lifespan hooks, encryption
Operations
- CI/CD pipelines
- TTL configuration for state and thread management
- Semantic search
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