Design of a ChatGPT System
We have identified the requirements, storage needs, and foundational components. Now, we will detail the system design to understand how these components ensure real-time, context-aware conversations.
High-level design of ChatGPT
The high-level design illustrates how the system handles real-time conversations. The following workflow outlines the component interactions.
The workflow for the high-level design is provided below:
User input: The user submits a text prompt via the interface or API.
Gateway processing: The API gateway authenticates the request, applies rate limiting, manages the session, and forwards the prompt to the model server.
Model inference: The AI model processes the prompt using conversation history. Responses are cached for retrieval and logged in the database.
Response delivery: The generated response is returned to the user via the API gateway.
Feedback loop: User feedback is collected to improve system performance and fine-tune future models. ...
Is a typical cache (like LRU or TTL-based) sufficient for storing AI-generated responses?
Let’s examine the specific components that enable this architecture.
Detailed design of ChatGPT
The detailed design breaks down the technical ...