It's a web app that uses AI to turn any book into a playable text adventure. Your favorite book, but your choices, hence your story. You can even "remix" the genre like playing Dune as a noir detective story.
Note: Work in progress. Suggestions are welcome.
I tried "The Hobbit" and it started with me having tea with Gandalf the wizard. There was a knock at the front door so I opened it and outside was Gandalf the wizard!
The LLM thus did two things: first, it used a combination of the prompt, the user input, and the recent history of the chat and relevant extracts from the database state, to update the database with a new state; then after updating the database, it used all of the above to synthesize the output response.
A major component of the system was that, in addition to the usual blocks-world subject-property-object representation of the game state, the system also used the database to store textual fragments that encoded things like thoughts, plans, moods and plot points.
Adding programmatic constraints to the database and its updates made a vast difference to the quality of the output by preventing logical absurdity of the sort that has been described above - attempts by the LLM to do absurd things were simply rejected.
Finally, there was a hierarchical element to the story-telling, not just simulation. There is much more to storytelling than simulation, and experimenting with this became the most interesting thing about the whole enterprise; there is plenty of space for future research in this.
The downside was that all this complexity meant it was _extremely_ compute-intensive, and thus very slow as a result. But the gameplay was fascinating. We will no doubt see more things like this in future as LLMs get faster; it's an obvious application for open source software.
https://www.youtube.com/watch?v=sVgVB3qsySQ
I've tried quite some models and so far I've only seen two that are good at keeping continuity: Gemini 2.5 Pro and Sonnet 3.7 (both with reasoning on). These two are also exceptionally good[0] at adding plot twists that aren't in the prompt.
[0]: by "my expectation of LLM" standard, not by the standard of bestseller genre fiction.
I mean human sometimes forgot about the state inside the game often
Beyond that... Would you forget that the guy you were having tea with was sitting in your living room? Anyone I know would definitely go "how the hell are you outside" not "nice to see you today".
That said, I think there's a lot of prompting techniques that can help here. (Actually the Guided Thinking section is an example of prompt-only techniques: https://ianbicking.org/blog/2025/07/intra-llm-text-adventure...)
You must at least do some pre- and post-processing to have the LLM consume and generate text that isn't part of the main user interface. But given that you can put in guidance that can increase the small-scale surprise of the interaction. For instance I'll have the LLM write out some of the objective environment at the moment before it considers a decision, so that it doesn't essentially retcon the setup for a plot direction it intends to take.
For the larger arc you'll need something like memory to pull the whole thing together. That include repetition over time. You can ask the LLM not to repeat itself, and it can do that, but only if it understands what it's done. And to some degree it needs to understand what it's _doing_: the LLM like the player is still generating short turns, and so if it wants to create surprise that is revealed over multiple turns then it needs space to plan ahead.
<<< We're in this situation, I'm the game master, and the player said "xyz". I need your help to handle this request according to the rules of the game. >>>
Then the LLM is directing the obedience towards the game master and the rules, rather than the player.
One problem that would probably still linger is model agreeableness, i.e. despite preparation, models have a tendency to say yes to whatever you ask for, and everybody knows a good DM needs to know when to say no.
I liken it to playing Minecraft on creative mode.
The main thing for me, though, was the feeling of emptiness I got while playing. I love text adventures, having grown up with Infocom games. The thing about them is that you can feel the choices made by the writer / programmer, just like you can feel the human author behind a book.
I'm sure part of what feels empty to me is because I know it was autogenerated. But I feel that even if I was shown this without knowing an LLM was behind it, the gameplay wouldn't be as rewarding as something written by a human using Inform.
But for games to shine they also need carefully considered constraints - when the player bounces off constraints they start to understand how the game's world and systems function, which lets them build a mental model and be able to start thinking the same way the designer(s) thought and come up with solutions for puzzles or decide how to react to a given situation.
What makes a maze engaging as a challenge is that your path is closed off in some places and not in others. Ideally any maze also has one or more concrete solutions, so the player is rewarded for mastering the maze by finding an exit, or maybe finding objectives or creatures hidden at key locations in the maze.
You can probably use modern LLMs to construct this sort of world and set those constraints, but I wonder how far we are from being able to also have the LLM maintain that world state and enforce the constraints?
I haven't played with the most state of the art parsers that are available right now, so I wonder how large the gap is between a great parser and using an LLM to process user input.
1) Structure the choices offered by the LLM; add “choice_type” and add instructions to the LLM on what those choices should do. E.g. action, dialogue, investigation, whatever makes sense for the genre—the LLM can even generate these at story start—then “choice should direct the narrator to focus on an action-oriented moment”, “choice should direct the narrator to focus on a dialogue between two or more characters in the scene”, etc.
2) Use reasoning whenever making tool calls for choices, summarize the reasoning, and include it in narrative summaries provided as part of the context for future narrative requests. For example, the combined summary might be: “In the last narrative I wrote for the user, Harry and Luna were startled by the noise coming from the edge of the forest. Important scene developments: 1) Luna and Harry had been approaching the edge of the forbidden forest for the last three narrative turns, and in the turn I just wrote they arrived at the edge. 2) Harry seemed to be the more courageous of the two in previous narrative turns, but in the most recent one, the user’s choice resulted in Harry becoming more deferential to Luna. 3) In the most recent narrative turn, the noise that had been emanating from the forest was now accompanied by a flickering light. I then suggested paths that would allow for character development through dialogue between Harry and Luna (I gave two options here), a path to move the story forward by having Harry take Luna’s hand before running into the forest, and another path that would slow the pace by having Luna investigate the flickering light accompanying the sound. The user’s choice: ‘Have Luna investigate the flickering light.’
3) Add an RNG weighted by story length or whatever works for you that will result in choices that lead the story to a conclusion. Include that direction in the tool call for generating choices, along with a countdown to the finale choice.
This is a rough mental sketch of what worked the best for me, i purposefully left out implementation or application details, as I don’t know what you’re wanting to do next.
Good luck, looks great!
If you believe that art is communication (and I do) why _wouldn't_ you want to reflect on it or discuss it post 'consumption'?
That said, I can readily acknowledge that artists can use AI as a tool in the creation of their art. I don't have a philosophical or intellectual problem with viewing AI as a tool and believing it can be a powerful aid in the creation of POV-driven art.
But there is a line somewhere between "no AI" and "entirely AI" that turns it from art to stimuli. I can't define it exactly, and even if I could, knowing that a particular work was partially created by AI creates a requirement that I trust the creator that the bulk of what I'm engaging with is from them, not the machine. And it's very difficult for me to make that leap of trust.
You may argue that stones can be interesting without beeing works of art. But the generator above takes works of art as input and somehow takes the art out if it to some degree.
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I also disagree with your conclusion that an activity only has a point if discussed with others. A good deal of the best experiences in my life are things that were for my benefit alone, that I never thought to share with anyone else. And I'm a pretty social guy.
That said, the way you have done it means it is roughly unique each time.
https://www.kathaaverse.com/play/custom-Rendezvous%20with%20...
I tried something like this before and it was a cool way to read a new book or study classics. It would read a few lines of, say, War and Peace, to me, and I would be given 3 choices of what comes next. The options were always quite varied and made you think more about the characters and what they would be likely to say in the context.
You could also just use it for non-fiction to quiz-ify contents for studying. Although that doesn't require the text to continue flowing after each question.
Edit: Nevermind. Just seen the canon game mode