Deepagents
Deepagents is an open-source agent harness that provides an opinionated agent that runs out of the box. It is designed to be extensible, model-agnostic, and production-ready. The project is built on top of LangGraph and provides features such as sub-agents, filesystem, context management, shell access, persistent memory, human-in-the-loop, skills, and tools. Deepagents is available as a JavaScript/TypeScript library and can be used with any LLM that supports tool calling. The project has a comprehensive documentation and provides examples, guides, and API references for developers. Deepagents is designed to be used in production and provides a full harness for planning, context management, and delegation out of the box. The project is part of the LangChain ecosystem, which includes LangGraph, LangChain, and LangSmith. Deepagents can be used with LangChain's create_agent and LangGraph's CompiledStateGraph to provide a custom agent loop. The project has a strong focus on security and follows a 'trust the LLM' model, where the agent can do anything its tools allow, and boundaries are enforced at the tool/sandbox level.
- Category
- AI Agents
- Pricing
- Open Source
Problem solved
Deepagents solves the problem of creating a general-purpose agent that can be used in various applications, such as research, development, and production. It provides a flexible and extensible framework for building agents that can interact with their environment, manage context, and make decisions. Deepagents addresses the need for a production-ready agent harness that can be used with any LLM, providing a scalable and reliable solution for developers and organizations.
Use cases
- Research and development
- Production-ready agent deployments
- Custom agent loop creation
- Integration with LangChain and LangGraph
- Use with any LLM that supports tool calling
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
Pros
- Extensible and model-agnostic
- Production-ready and scalable
- Comprehensive documentation and examples
- Strong focus on security
- Part of the LangChain ecosystem
Cons
- Steep learning curve due to complexity
- Requires expertise in LLMs and agent development
- Limited support for certain LLMs or tools
Official website: https://github.com/langchain-ai/deepagents
Canonical LambdaBase page: https://www.lambdabase.com/tools/deepagents