We have a discussion in our team whether to use clean architecture principles when building our agents.
A potential change of vector database sparked this discussion.
I personally think it’s a lot of abstraction around the code and I don’t like it but I see the other points.
Here are some pros and cons. I would really like to know what you think especially when you work with more than one agent.
Arguments for Combining LangGraph with Clean Architecture
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Separation of Concerns: Clean Architecture emphasizes clear separation between business logic, infrastructure, and interface layers. LangGraph’s graph-based orchestration of agents and workflows can be encapsulated within the domain and application layers, promoting modularity and maintainability.
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Testability: Clean Architecture facilitates unit testing by isolating core logic from external dependencies. LangGraph’s nodes and edges, which represent discrete logic units, can be designed as pure functions or classes that are easy to test independently.
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Scalability and Flexibility: LangGraph supports complex, stateful, and long-running workflows. Clean Architecture’s layered approach can help manage this complexity by organizing code into well-defined boundaries, making it easier to evolve and extend the system.
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Decoupling from Frameworks: Clean Architecture encourages minimizing direct dependencies on frameworks and infrastructure. LangGraph can be treated as an infrastructure or orchestration layer, allowing the core business rules to remain framework-agnostic.
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Better Collaboration: Clear architectural boundaries can help teams work in parallel on different layers (e.g., domain logic vs. orchestration), which is beneficial in complex LangGraph applications involving multiple agents and workflows.
Arguments Against Combining LangGraph with Clean Architecture
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Added Complexity: Introducing Clean Architecture layers on top of LangGraph’s graph-based orchestration might add unnecessary complexity, especially for smaller or straightforward agent workflows where LangGraph’s abstractions alone suffice.
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Potential Overhead: The abstraction layers in Clean Architecture can introduce boilerplate and indirection, which might slow down development or make debugging more challenging in fast-evolving LangGraph projects.
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Mismatch of Paradigms: LangGraph’s model is inherently graph- and state-driven, focusing on nodes and edges as first-class concepts. Clean Architecture is more classically layered and may not naturally map to graph-based workflows, potentially leading to awkward or forced designs.
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Performance Considerations: While Clean Architecture promotes decoupling, the additional layers might introduce slight performance overhead or latency in stateful, streaming, or real-time LangGraph applications, where direct orchestration could be more efficient.
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Learning Curve: Teams unfamiliar with Clean Architecture might find it challenging to integrate it effectively with LangGraph, potentially slowing down adoption or leading to misuse of either framework.