A UI popup that lets you use "prompt templates" or write freeform text as the prompt.
You can ask the AI to perform any task on the current block, use a built-in command, or define your own templates
You can write any command in the popup, and it will run that command using text in the current block.
For example, to create flash cards for studying, you could write "create flash cards based on the following text:"
There are also a bunch of built-in prompts for common tasks like summarization, creating outlines, asking follow-up questions, and identifying common objections to an idea.
You can also define custom prompts templates anywhere in your notes, similar to the built-in @logseq templates
Just make a header with a "prompt-template:: Prompt Name" property, and a
```prompt
My custom prompt:
```
code block under it.
It will appear in the popup dropdown
The popup shows you a preview of the output before you insert it into your notes.
Sometimes the first try doesn't generate optimal results, so you can click "Regenerate" to re-run the prompt until you get something good.
You can click "Insert" or hit enter to add the output underneath the current block
You can also click "Replace" to replace the current block with the output. This is useful for improving the tone of existing writing, fixing grammar/spelling, and translation.
Do you have a prompt that the community would find useful? Contribute it to the built-in prompts list
There's a TOML text file in the repo where you can add them. I encourage you to be creative and I'm especially interested in @logseq - specific prompts
Hard-Boiled Wonderland and the End of the World by Haruki Murakami
A human data processor trained to encrypt data with his mind to protect it from criminal groups.
Two intertwined stories between dystopian Tokyo and a strange isolated town
Picture of Dorian Gray by Oscar Wilde
The beautiful Dorian Gray makes an impulsive wish to stay young while his portrait remains the same, aging over time to absorb the damage of his wild life.
Genius writing and dialog that explores our obsession with youth and beauty.
These terms refer to how many examples a language model needs to perform a task
"Fine-Tuning" is the most common and traditional approach.
100s to 100k+ labeled examples are used. It has strong performance on many benchmarks but needs a new large dataset for every task.
It's better for specific use cases than general tasks.
"Zero-shot" is where no examples are allowed. Only instruction in natural language is given. This method provides maximum convenience but is most challenging for AI. Performing a task without examples is hard for humans too