This sounds fairly useless, as it might cluttter the UI for somethiing that's basically right in front of you: The chat window is there to optimize any prompt for you.
Silver Milkshake
•
Aug 12, 2024
Have an option in the UI that user can interact to get an optimized/shortened prompt. This will reduce token usage over the course of days/weeks depending the user's usage.
Example workflow:
user writes the prompt using the existing textbox
Then clicks on the "optimize/shorten" button next to the same textbox
UI presents option(s) that are optimized/shortened versions of the prompts. Now user can decide to either pick one or go with the original prompt(unoptimized).
Note: For optimizing the prompts, user can configure typingmind to use a lower cost/smaller LLM. So a separate UI could be needed for that as well.
Benefits:
Cost Efficiency: Significantly reduces the number of tokens processed by the more expensive model.
Improved Prompt Quality: Ensures your prompt is optimized for clarity and brevity before hitting the more capable (and costly) LLM.
Automation: This process can be automated to run seamlessly within your existing workflow, saving time and effort.
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Comments2
Rose Crater
Aug 27, 2024
This sounds fairly useless, as it might cluttter the UI for somethiing that's basically right in front of you: The chat window is there to optimize any prompt for you.
Silver Milkshake
Aug 12, 2024
Have an option in the UI that user can interact to get an optimized/shortened prompt. This will reduce token usage over the course of days/weeks depending the user's usage.
Example workflow:
user writes the prompt using the existing textbox
Then clicks on the "optimize/shorten" button next to the same textbox
UI presents option(s) that are optimized/shortened versions of the prompts. Now user can decide to either pick one or go with the original prompt(unoptimized).
Note: For optimizing the prompts, user can configure typingmind to use a lower cost/smaller LLM. So a separate UI could be needed for that as well.
Benefits:
Cost Efficiency: Significantly reduces the number of tokens processed by the more expensive model.
Improved Prompt Quality: Ensures your prompt is optimized for clarity and brevity before hitting the more capable (and costly) LLM.
Automation: This process can be automated to run seamlessly within your existing workflow, saving time and effort.