LangGraph

LangGraph is LangChain's low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents. It lets you mix deterministic, hand-coded steps with LLM-driven agentic steps in a single graph, giving you fine-grained control over exactly where and how AI is applied. It's trusted by Klarna, Uber, J.P. Morgan, Replit, and Elastic.

Key Features

• Durable Execution: Agents persist through failures and can run for extended periods, automatically resuming from where they left off.
• Human-in-the-Loop: Inspect and modify agent state at any point during execution for oversight and steering.
• Comprehensive Memory: Short-term working memory for ongoing reasoning plus long-term persistent memory across sessions.
• Deterministic + Agentic Mixing: Combine hand-coded logic with LLM-driven decisions in one graph — predictable where you need it, flexible where you don't.
• Streaming & Persistence: First-class streaming and durable state via checkpoints.
• Production Deployment: Deploy and scale agents via LangSmith Deployment; visual prototyping in LangSmith Studio.
• Standalone or LangChain: Works without LangChain, but integrates seamlessly with the full LangChain stack.
• Deep Agents SDK: Planning, subagents, filesystem tools, and context management built on top of LangGraph.

Use Cases

Who Should Use This Tool?

• Production Agent Teams: Teams building agents that must survive failures and run for hours or days.
• Complex Workflow Builders: Applications needing deterministic control flows with LLM decisions at specific points.
• Enterprise AI Teams: Companies like Klarna, Uber, and J.P. Morgan shipping stateful multi-actor applications.

Problems It Solves

1. Agent reliability: Durable execution means long-running agents resume instead of restarting after crashes.
2. Oversight: Human-in-the-loop lets you approve or modify actions before they take effect.
3. State management: Memory and checkpoints handle both in-context and cross-session state.

Pricing

Advantages & Unique Selling Points

Compared to Competitors:

1. Low-level control: More expressive than black-box agent frameworks for bespoke architectures.
2. Durable execution: Automatic resume from failure points — not just retries.
3. Ecosystem depth: Integrates with LangChain, LangSmith, and Deep Agents SDK.

What Makes It Stand Out:

• 39,000+ GitHub stars and a mature, active community.
• Inspired by Pregel and Apache Beam; interface inspired by NetworkX.
• Mixes deterministic and agentic steps in the same graph.

Getting Started

Quick Start Guide

1. Install: pip install langgraph.
2. Define state: Create a StateGraph with your state schema.
3. Add nodes: Connect LLM calls and deterministic functions as graph nodes.
4. Compile and run: Compile the graph and invoke it; add checkpoints for durability.

Integration

Integrates with:

• LangChain, LangSmith, Deep Agents SDK
• Any model provider
• LangSmith Deployment for hosted scaling

Frequently Asked Questions

Do I need LangChain to use LangGraph?

No — LangGraph works standalone, though it integrates with LangChain products when you want them.

Is it free?

Yes — the core library is MIT-licensed open source.

What kind of agents can I build?

Single-agent, multi-agent, and hierarchical control flows — all with durable execution and human-in-the-loop.

Alternatives

If LangGraph isn't the right fit, consider these alternatives:

• CrewAI: Higher-level role-based multi-agent framework.
• OpenAI Agents SDK: OpenAI's production-focused agent framework.
• Google ADK: Google's multi-agent framework with A2A support.

Tips & Best Practices

1. Use checkpoints for durability: Persist state so long-running agents survive restarts.
2. Add human-in-the-loop gates: Approve risky actions before they execute.
3. Separate deterministic from agentic: Keep predictable logic in code and flexible decisions in LLM nodes.

Conclusion

LangGraph is the orchestration runtime behind the most reliable stateful agents in production — durable execution, human-in-the-loop, and comprehensive memory in one low-level framework. If you're building agents that must run long and never lose state, LangGraph is the industry standard.