ClevAgent provides a workspace for running and guiding AI agents with background efficiency and safety controls.
LangGraph
Gain control with LangGraph to design agents that reliably handle complex tasks.
About LangGraph
LangGraph is a low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful AI agents. It lets developers combine hand-coded, deterministic steps with LLM-driven agentic steps in the same graph, so the parts of a workflow that need predictability can be fixed while other parts stay flexible.
The framework focuses on agent orchestration rather than prompts or agent architecture. Its documented capabilities include durable execution, streaming, human-in-the-loop review of agent state, and persistence, with both short-term and long-term memory. LangGraph can be used on its own, and it can also be paired with LangChain for model and tool integrations. Users who are new to agents are advised to learn the basic components first, or to use LangChain's higher-level agent abstractions instead.
Key features
- Combines deterministic code steps and LLM-driven steps in one graph
- Durable execution with persistence that resumes after failures
- Streaming support for agent runs
- Human-in-the-loop inspection and modification of agent state
- Short-term working memory and long-term memory across sessions
- Tracing with LangSmith to inspect execution paths and state changes
Best for: Python developers who need fine-grained control over long-running, stateful agent workflows and are comfortable working with low-level components.
Good for
- Lets developers choose exactly where deterministic logic and model-driven decisions apply
- Supports human oversight by allowing inspection and modification of agent state at any point
- Can be used without LangChain
Watch out for
- Described as very low-level, so it is not aimed at users who want a higher-level abstraction
- Users are advised to learn models and tools before using it
- Tracing and debugging with LangSmith require setting tracing variables and an API key
LangGraph at a glance
- Category
- AI & Machine Learning › AI Agents & Automation
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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LangGraph FAQ
Do I need LangChain to use LangGraph?
No. LangGraph can be used standalone, though LangChain components are commonly used in its documentation to integrate models and tools.
What should someone new to agents use instead?
The documentation recommends LangChain's agents for a higher-level abstraction, since they provide prebuilt architectures for common LLM and tool-calling loops.
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