Introduction to Context Windows
A context window, in the realm of language models like ChatGPT, refers to the amount of recent conversation history that the model can consider when generating a response. This context includes the model's own messages as well as the user's messages, and the size of this context is measured in 'tokens'.
Context Windows and LLMs
The size of the context window is determined by the model’s architecture. For instance, GPT-3 has a maximum token limit of 2048 tokens. This means it can consider up to the last 2048 tokens of text as its context. If a conversation exceeds this limit, the model won't be able to see or consider the text beyond it.
Context Window in Chat Applications
In a chat application, the context window affects how the AI responds to user inputs. If a conversation is long enough to exceed the model's context window, the AI may lose track of the context and start responding inappropriately or inconsistently.
For example, if you ask the AI to remember a piece of information at the start of a long conversation, and then refer back to it after a lot of back-and-forth, the AI might not remember the initial piece of information if it's outside of its context window.
Managing Context Window Limitations
There are several ways to work around context window limitations. One approach is to manage the conversation carefully, ensuring the most relevant information is within the model’s context window. Alternatively, developers can design the system to provide relevant past information explicitly when it becomes necessary.
Key Points to Remember
The context window is the amount of recent conversation history the model considers when generating a response.
The size of the context window is determined by the model’s architecture and expressed as a token limit.
If a conversation exceeds the model's context window, the model may lose track of the context and respond inconsistently.
Developers can use strategies to manage context window limitations.