How to Bypass ChatGPT’s Token Limit: Recursive Prompt Splitting
By Split Prompt · 2 min read · 21 Sep 2023
ChatGPT has set the bar high for AI conversations, making it a favorite amongst enthusiasts and professionals alike. As user queries have grown in complexity and demand, so too has the length of their prompts. This is evident in situations where users provide extensive inputs, such as large code dumps, intricate narratives, or detailed problem descriptions.
Why the Need for a Prompt Splitter?
First, we need to understand the two fundamental limitations of ChatGPT: the token limit and the context window.
Token Limit: A 'token' in ChatGPT can range from a single character to a whole word. ChatGPT can only process a set number of these tokens in a single input before rejecting the prompt.
Context Window: ChatGPT can only remember a limited amount of the conversation history. As discussions progress, earlier segments fall out of this window, no longer influencing its replies.
A prompt splitter tool can help navigate these constrains, enabling ChatGPT to process extended prompts seamlessly.
The Flaw in Most Prompt Splitters
Many prompt splitters online successfully divide a long prompt into smaller chunks, to fit within the token limit. However, they neglect the underlying context window. These tools attempt to have ChatGPT respond only after presenting all the split chunks. However, when these combined splits exceed the context window, ChatGPT loses sight of earlier segments, and is often unaware of their interconnected nature. This defeats the purpose of a prompt splitter, as only a partial input is considered.
Introducing Split Prompt: A Recursive Solution
Unlike its competitors, Split Prompt doesn’t just split; it remembers. The secret sauce is our two-pronged strategy: iterative processing and recursive feedback.
- Iterative Approach: Instead of bundling content and processing it at the end, Split Prompt divides and conquers, ensuring each segment will fit within the subsequent prompt’s context window
- Recursive Context Reinforcement: Each subsequent segment is cued to the context of the preceding prompt, maintaining continuity and ensuring the AI retains a holistic grasp of the overall narrative.
With these innovative methods, Split Prompt bridges the gap between lengthy user inputs and ChatGPT’s processing limitations. Users can now engage in more complex conversations without sacrificing the essence or context of their queries.