framework-selection

To choose between LangChain, LangGraph, and Deep Agents, evaluate your task requirements against a structured decision table that details each framework's strengths and use cases. This selection process ensures the right tool matches your specific project needs.

You should use LangGraph instead of LangChain when your task requirements align with LangGraph's specific strengths outlined in its framework profile. Evaluating the decision table helps determine if LangGraph's capabilities are more suitable for your application than LangChain's.

Yes, you can combine LangChain and LangGraph in a single project by using a layered approach. This allows you to leverage the respective strengths of multiple frameworks, integrating their unique capabilities within the same application architecture.

Deep Agents use cases are defined by its detailed framework profile, which highlights its specific strengths for certain task requirements. Comparing this profile against LangChain's in the decision table reveals why Deep Agents might be the better choice for your project.

You evaluate task requirements to select the right AI framework by using a structured decision-making framework. This involves consulting a decision table that maps your project's specific needs directly to the detailed profiles and strengths of LangChain, LangGraph, and Deep Agents.