Show HN: Agents for Storytelling with (Neo)Zork

A throwback to classic Zork games with a twist: you can take any action an an AI agent simulates the result and produces a page of a story

The pipeline for generation is fairly straightforward:

- Prompt expansion: Trying to understand what the user said and what their underlying intent is to produce an even longer instruction so their character takes more than a single action per page.

- Character simulation: The background of each character registered in the scene is structured to help the LLM understand how they react to different situations, and a bucket of actions that they'll take is generated for the final output step

- Story understanding: A basic RAG pipeline to ensure details that are no longer in the context window get captured correctly

- Image generation: Every 5 pages an image is generated by summarizing the scene and generating an image generation prompt

- Final output: The output uses a formatting schema that denotes who's speaking what line, when certain actions are taking place etc. The goal is to eventually narrate with accurate voices based on the character that's speaking

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You can also add characters and notes to the simulation by clicking Story Settings at the bottom