Clean Architecture for an LLM-based Chatbot API-based Service
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A Clean Architecture for an LLM-based Chatbot API-based Service is a clean architecture style applied to designing and implementing a language model-powered chatbot service, facilitating interactions via an API-based service, that aims to separate the business logic of the chatbot from external dependencies such as databases, frameworks, and UI technologies.
- Context:
- It can (typically) be designed with a focus on maintaining a separation of concerns, where the core functionality of the chatbot, such as processing natural language inputs and generating responses, is decoupled from the application's interface and infrastructure components.
- It can (often) be organized into four layers specific to the chatbot's needs:
- Clean Architecture Entities: Representing the core business objects of the chatbot, such as user queries, intents, and context.
- Clean Architecture Use Cases: Encapsulating the business logic of the chatbot, including parsing user input, understanding intent, and generating appropriate responses.
- Clean Architecture Interfaces: Defining the behavior of external dependencies the chatbot might interact with, such as external APIs for data retrieval or processing services.
- Clean Architecture Frameworks and Drivers: Implementing the concrete details of external dependencies, including API clients, database access layers, and integration with AI models.
- It can (often) utilize Dependency Injection Frameworks, Object-Relational Mappers (ORMs), and Web Frameworks to implement its layers effectively, ensuring that the chatbot service is maintainable, testable, and adaptable to changes in external technologies or business requirements.
- It can (often) be beneficial for maintaining clear boundaries between the chatbot's logic and the platforms it operates on, allowing for easier updates and scalability.
- It can (typically) follow the principle: "High-level modules should not depend on low-level modules; both should depend on abstractions," ensuring that changes in external services or platforms have minimal impact on the chatbot's core functionalities.
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- Example(s):
- A Clean Architecture for a Legal Tech Contract Review Chatbot, where the chatbot's core functionalities are separated from the specific legal databases and frameworks it uses to retrieve and process information.
- A Clean Architecture for a Customer Service Chatbot, enabling the chatbot to seamlessly switch between different communication platforms (e.g., web, mobile) without affecting its underlying logic.
- ...
- Counter-Example(s):
- A Monolithic Architecture for a chatbot, where the business logic, database access, and API integrations are heavily intermingled, making it difficult to update or scale the service.
- A tightly coupled chatbot system where changes to the AI model or the API framework require significant alterations to the chatbot's business logic.
- See: Language Model, API Design, Software Design Principle, Layered Architecture, Python Programming.