runprompt

The harness is using my own project "runprompt" which you can find here: https://github.com/chr15m/runprompt That has a bunch of Python tools for things like adding to TODO list, notes, looking stuff up, etc.

Reminded me of this from my bookmarks. https://github.com/chr15m/runprompt

Lately I've seen several projects for templating and executing prompts. However they all go along the lines of $ executor prompt_file_or_name which didn't exactly fit my "taste". I figured one could use the same trick like busybox, where you can detect if your binary is being executed via a different name (symlink). The symlink name is treated as the promptname, and arguments are generated from a schema defined in the prompt template. So now instead of: # Using https://github.com/chr15m/runprompt echo '{"words": 300, "text": "some long text"}' | ./runprompt summarize.prompt # Or using https://github.com/simonw/llm echo "some long text" | llm -t summarize -p words 300 You get: echo "some long text" | summarize --words 300 And of course with documented arguments and so on: summarize --help Usage: summarize [OPTIONS] --

it already has one - https://github.com/chr15m/runprompt/blob/main/runprompt#L1 If you curl/wget a script, you still need to chmod +x it. Git doesn't have this issue as it retains the file metadata.

https://github.com/chr15m/runprompt/blob/main/runprompt#L9 seems like it would be, just swap the openai url here or add a new one

I built a single-file Python script that lets you run LLM prompts from the command line with templating, structured outputs, and the ability to chain prompts together. When I discovered Google's Dotprompt format (frontmatter + Handlebars templates), I realized it was perfect for something I'd been wanting: treating prompts as first-class programs you can pipe together Unix-style. Google uses Dotprompt in Firebase Genkit and I wanted something simpler - just run a .prompt file directly on the command line. Here's what it looks like: --- model: anthropic/claude-sonnet-4-20250514 output: format: json schema: sentiment: string, positive/negative/neutral confidence: number, 0-1 score --- Analyze the sentiment of: {{STDIN}} Running it: cat reviews.txt | ./runprompt sentiment.prompt | jq '.sentiment' The things I think are interestin