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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

We abandoned our team of heroes as they frantically tried to collapse the pocket dimension that contained them, before the multiplying tears in reality overwhelmed them.

As I was preparing the setting for this scene, it became obvious that I needed a new abstraction in my hierarchy of places. You see, many prompts to the large language models get fed the combination of places where the scene happens: story universe > world > region > area, and possibly location as well. But in this case, the characters were in a distinct inner chamber inside a sanctuary. The sanctuary would be the location, while the inner chamber was a sub-location, or a room. So clearly, given that the story has demanded it, instead of “half-assing” such places into the hierarchy, I should modify all the code that touches the hierarchy to have in mind a new type of place: a Room. Perhaps they won’t be used that often, but if a serious playthrough has required it, then I need to program it in. This may take a while; the last time I touched the hierarchy of places, that is almost the spine of the whole app, it took me days to return the app to normal. We’ll see how it goes.

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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

In the previous part, our team of heroes found themselves trapped in a pocket dimension created by the malicious alien Zha’thik, a dimension made from the memories of Elizabeth Harrow so she would stay inside in a sort of dream state. The team will attempt to collapse the pocket dimension to return to the containing dimension, the so-called Mirage Wastes.

They finally prepare themselves to do something as troublesome as collapsing a pocket dimension with themselves inside.

Intense episode.

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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

At the end of the previous part, we left our jaded protagonist boxing an eldritch horror while his long-dead teenage lover ran for her life.

I had no clue where Cassidy’s portal would lead, or even if it would work. I organized a session with my Writers’ Room to put together the following scene, that involved generating a couple of new characters.

Those noises are artifacts that rarely happen when generating voices. It’s odd that it happened three times in this segment, but they seemed to fit the eeriness, so I left them in. I apologize for minor errors such as using “his” when referring to Elizabeth. My brain is mostly mush at this point.

When this scene started, I had only included the main team in the dialogue, but I wanted Gideon’s deceased wife and the young version of their daughter to show up in the middle of the conversation. I had no such system implemented, so I wrote it in: a new collapsible section in the chat page that if there are characters present in the same place who aren’t involved in the dialogue, you can simply add them, and they’ll be included in the prompts to the large language model from then onwards. It was surprisingly easy to do, which I suppose is a testament to how mature the app is at this point.

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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

Here’s the next episode of the eldritch show. Last time, the sadistic alien Zha’thik prepared an unfathomable feast in a non-euclidean hall. Our jaded detective decided to take the first bite, only to realize that the morphing mass had turned into the corpse of Emilia, his long-lost teenage love. Now he’s bound to face his personal horror.

Well, that was poignant. I shed tears while “playing” through it, I shed tears while editing it. That’s good.

At the final part of that scene, I needed a fight “beat,” but I didn’t have anything programmed that would provide such a thing specifically. In addition, this fight would take part in the middle of a conversation. What to do, then? Create a new Confrontation action like the Investigate, Research, and Gather Supplies ones, which are meant to be isolated, and then stitch together two dialogues? It didn’t feel right. Besides, in that case, I would need to write the summary of the full conversation to include the physical confrontation with the eldritch horror. So instead, I came up with the notion of a Confrontation Round: the account, taking about ten seconds, of a confrontation of whatever kind, given the provided context. The prompt is focused on that very subject with no distractions, as seen below:

You are to generate a detailed narrative describing a brief segment (approximately ten seconds) of a confrontation within a rich, immersive world.
Use the provided information about the player, the other characters, and the place involved.
Your narrative should be engaging, realistic, and reflect the abilities and circumstances of the participants suggested by the user-provided context.

Instructions:
1. Viability and Realism Assessment:
Carefully consider the feasibility and dynamics of the confrontation based on:
- The information about the characters, including their skills, abilities, health, equipment, and emotional state.
- The characteristics of the opponents, including their skills, abilities, equipment, motivations, and weaknesses.
- The characteristics of the location, including terrain, obstacles, and any environmental factors.
- The time of day and how it might affect the confrontation (e.g., visibility, shadows, crowd presence).
- The context for the confrontation provided by the user, including any prior events leading up to this moment.
- Potential advantages or disadvantages, such as surprise, preparation, or environmental hazards.

2. Narrative of the Confrontation:
- Write a vivid, dynamic narrative that depicts approximately ten seconds of the confrontation, focusing on the immediate actions and reactions of the characters involved.
- Include specific actions taken by the characters on either side of the confrontation.
- Describe the use of skills, abilities, equipment, tactics, and any maneuvers.
- Illustrate the interactions between the characters, including attacks, defenses, dodges, or spells.
- Convey the emotions, thoughts, and physical sensations experienced by the characters.
- Ensure the depiction is consistent with the world's lore, the characters' personal histories, and their abilities.
- Determine the immediate results of this segment of the confrontation based on your assessment.
- Be specific about any successes or failures of actions taken, including hits landed, misses, blocks, or counterattacks.
- Describe any injuries sustained, advantages gained, positions changed, or other consequences.
- Reflect any costs incurred, such as stamina lost, equipment damage, or exposure to danger.
- The confrontation doesn't need to end in this segment, unless you can clearly determine that the confrontation should conclude now.

3. Tone and Style:
- Write in the third person, present tense, maintaining an engaging and immersive narrative style.
- Use rich, descriptive language to bring the scene to life, focusing on action and immediacy.
- Ensure consistency with the established world setting and the characters' personalities.

Provided Information:
Current Time: {hour} {time_of_day}
{local_information}
Facts Known:
{facts_known}
{relevant_characters_information}
----
Ongoing Dialogue:
{transcription}

Example Format:
"With a fierce battle cry, [Player Name] charges forward, swinging their sword toward [Opponent Name]..."

Your Task:
Using the above instructions and information, craft a compelling narrative that captures this intense moment of confrontation, reflecting both the actions and immediate consequences, while advancing the story in a meaningful way.
Important: do not repeat verbatim previous confrontation rounds: there should always be a progress in the confrontation.

If the segment at the end of the previous audio was anything to go by, it worked perfectly. To be honest, I was dreading creating a Confrontation action, because I thought it would be the Next Big Part of the app, but turns out that at this point of the AI revolution, LLMs are intelligent enough to “get it.”

I need a breather after this goddamn episode.

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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

The last part ended with our team of heroes begrudgingly agreeing to partake in the trials of a shadowy, shady alien from the dimension they had ventured into.

For this part, I decided to implement a Grow Event button in the chat interface. Basically, the user writes the guideline for what they would like to happen at that point of the dialogue. Then, a dedicated prompt sent to a large language model will cause the AI to expand the suggested event into a literary form. There are two or three examples of that in the audio you may have listened to. Great for when you don’t want to bother behaving as both the narrator and the player character.

I’ve already played through most of the scene that will be featured in the next part. Man, it was emotionally taxing.

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I recommend you to check out the previous parts if you don’t know what this “neural narratives” thing is about. In short, I wrote in Python a system to have multi-character conversations with large language models (like Llama 3.1), in which the characters are isolated in terms of memories and bios, so no leakage to other participants. Here’s the GitHub repo, that now even features a proper readme.

In the previous episode of this thing, our team of Earthlings, having ventured through a rift into another dimension, encountered a half-buried building in an obsidian desert. Now, they enter it. The following audio is an episode-long account of what happened.

That’s it for today narrative-wise. By the way, this is the portrait that the app generated for Zha’thik.

As I was thinking what else I could do with character memories, which are used by the large language models to roleplay the characters better, I ended up implementing a system to generate any character’s worldview, his or her personal philosophies, influenced by their bio and their experiences. That means that when the user wants to deepen the roleplaying of any of the characters at an arbitrary point of the journey, their worldview can be generated, and it will reflect the journey up to that point. Some characters could start naive, only for their worldview to change after nasty experiences. And of course, the generation of self-reflections receives all the memories as input, including any possible worldview texts.

This is the worldview generated for the brilliant scholar Elara Thorn, based on her bio and experiences up to this point:

Elara Thorn views the world as a place full of untapped knowledge waiting to be discovered, even if it means venturing into dangerous and morally ambiguous territory. Her philosophical beliefs are rooted in the idea that the pursuit of truth and understanding justifies the risks and sacrifices made along the way. She believes that knowledge is power and that those who possess it have an obligation to use it for the greater good, even if it means pushing the boundaries of conventional morality. However, her worldview is not without its challenges and doubts. As she delves deeper into the mysteries of the multiverse, Elara is faced with the harsh realities of the consequences of her actions. She begins to question whether her obsession with knowledge has blind her to the cost of her pursuit, and whether the sacrifices she’s made have been worth it. Elara’s moral standing is complex and evolving. While she believes in the importance of doing what is right and protecting those who cannot protect themselves, she also recognizes the necessity of making difficult choices in the face of unimaginable danger. She struggles with the weight of her own humanity, constantly grappling with the question of whether her actions are truly justified or if she has become a monster in pursuit of her own desires. Despite the doubts and challenges that confront her, Elara remains steadfast in her belief that the pursuit of knowledge is worth the risks and sacrifices, and that she has a duty to use her brilliance to make a difference in the world, even if it means navigating the treacherous waters of the unknown.

My Writers’ Room has come up with an intriguing concept for the next episode. I can’t wait to play it out.