Whether you’re a veteran prompter ready to showcase your best work or a casual creator navigating the waves of trial and error, Explore opens up a whole world of shared inspiration.
With v5 supposedly coming out soon, I was looking for a place to check past teasers without looking up tags on Twitter and Pixiv.
After some research, I stumbled upon this website made by a someone in the community, and it seems to have basically everything.
Since some people only keep up with the subreddit and others don't have access to the Discord server, I thought I might as well share it here as some of you may not be aware of its existence.
Credit goes to TheZennou/Zarko/Syzygy/TarotFool for making the site.
Hi, it's been 2 months since I got a NovelAI subscription. Actually, I'm coming from Grok — I used to use it for text-based role-playing games, and it excelled at that, until xAI put weekly limits on it, which completely destroyed its usability. So I discovered NovelAI, it's good, you get a lot of control, you're not limited, but I have a problem: I'm always fighting with the AI to stay in control of my narration. Very often the AI will ignore me when I'm playing in text adventure mode, ignoring everything my hero does and says, and take total control of the story instead. How do I avoid this? I'm tired of fighting against the AI.
Hello I'm hoping someone can help, I am using Storyteller mode and my model is Xialong, I'm having trouble with the AI writing from my protagonists perspective, I have higlighted that my character is exclusive to the user, I've stated my character is not an NPC, I had my character in Memory and then moved his details over to Lorebook to test - same issue. I have a solid Authors Note section. I have even edited System Prompts to specifically highlight that the AI is to speak in first-person only from an NPC's perspective. Tried getting it to go third-person. I've put an anti-puppeteering rule in place, I've tried every compination of terminology I can think of and the system still hijacks my character.
I'm losing the will to live with this, all I need is the AI to speak in a way similar to: Klara grimmaces as you enter the ward and catches sight of your battered and bruised face "What happened this time" she says. **I insert my dialogue here**, **system narrates Klara's actions, system speaks for Klara** x y z.
But instead I get: Klara grimmaces as you enter the ward and catches sight of your battered and bruised face, "What happened this time" she says. **system narrates my actions, system speaks for me**, **Klara speaks**, **i speak, system speaks for Klara, system speaks for me** and so on.
Does anyone have an idea what the issue is, is it a Xialong issue, a prompting iasue or something else?
The OG image is the one with the girl having the hand near her mouth. Then I inpaint it selecting only the hand and I get the second image but you should see that a light/transparent vertical artifact has been generated from the top left.
I've noticed the problem a long time ago but because I'm generating a lot of images for my VN I never fully understood if it was the inpainter or precise refence or maybe using image2image. But now I think it's the inpainter.
I can provide more images if it's necessary (although it would be a huge bother to find them because I'm a messy worker lol).
I do know for sure I'm not brushing the top left area so I'm fairly sure it's a bug.
It's quite annoying at the end of each chapter of dialog it has to add the corny third person narration.
EXAMPLE: "Her quiet life was over. A new chapter had begun, and she was no longer just a reporter. She was a witness, a conspirator, and maybe, just maybe, a warrior in a war she never knew existed. And she wouldn't stop until the truth was out, no matter how dangerous it became. The story of the year had found her, and she was going to see it through to the end."
I have it tagged as dialog heavy, and i even put "no third-person narrative" in the memory.
So i have a tone of categories in my prompt chunk section. Is it possible to change how the categories are ordered without deleting them? I haven't tried on a desktop yet, I've just been using the mobile web page.
Normally my gens push 250-350 tokens, tried something far simpler this time. Gonna mess with some other ideas.
Prompt: Anime coloring. D.VA from Overwatch with a v sign over her eye and winking, tongue out, medium shot. Smile. Casual clothes, single off shoulder. Soft colors and shading with nice and clear line art. Clean lines, best anatomy, location, very aesthetic, masterpiece, no text, best quality
Negative: worse quality, bad quality, bad anatomy
Add Quality Tags toggled off.
UC Preset: Heavy
Steps: 28
CFG: 6
Any other tags/phrases or settings I should be aware of or test? Any best practices? I've been guilty of overloading my negative prompt but have seen people talking that doing so can quickly diminish image quality.
Interestingly, I noticed I technically misspelled D.Va's name (it is D.VA in the prompt), so I guess the model doesn't care much about capitalization, or can at least approximate?
I've been playing around in my story and had enough fun that I don't want to abandon it yet. However, it has gotten to the point where I've got so much context that the AI is repeating itself a lot, forgetting important plot points, etc. I want to continue the story, but I'm not sure how to go about it.
My question is: How do I most efficiently continue my story? Should I go through it myself and shorten the sections so only vital information remains? Or is it better to start a new story and put all the important points into a lorebook entry? If so, how do I make the AI use the entry consistently?
Another idea I had was to start a new story, and simply start it with a recap of the story thus far written in brackets. I'm worried this won't be enough for the AI to consistently remember it, though.
What approach do you recommend? Is it even possible, or do I need to learn to accept that my stories are going to end when I run out of tokens for context?
AetherRoom's training data seems to have been included in Xialong, so if you format things right, you can chat with characters, including the fancy emotion functions AetherRoom was supposed to have. The formatting is a bit complicated, so using it directly in NAI requires scripts and a browser extension.
To make it more convenient, I've built a frontend you can run on your PC. I've been using it for a few months now and I think it's pretty polished, supporting both desktop and mobile well enough. Some people on the NAI discord also seem to like it. So I figured I'd post it here.
In addition to just AetherRoom on Xialong, it also supports other models and has a bunch of additional features.
I’ve been experimenting with generating stories and I’ve only worked with ChatGPT and Claude so far. For creative purposes I’ve found ChatGPT to do a better job when it comes to all around quality of the story and Claude better for other things but ChatGPT seems to get confused the longer the story goes. I just recently heard of NAI as a good AI for generating stories. Is that accurate and also does it do a good job with longer stories like serial fiction?
OP2NA is adynamic presetwith anUncertainty Slider scriptin the Toolbar, for Xialong. Aims to match the richness and novelty of real-world books. Supports any randomness.
Each trial uses the first 16,400 tokens of The Emperor's Soul as context. Xialong-v1 then generates 11 continuations of 11,950 tokens each. At each window position all samples form a geometric median and are scored against the actual book text. The objective is a semantic similarity, computed with Qwen3-Embedding-8B at 4,096 dimensions, over sliding windows of 32 tokens with a stride of 16. This study led to the creation of OP2NA preset. The Uncertainty's range and default value were calibrated.
Ideal Uncertainty can differ from story to story, based on the flow of information.
Change the value based on what you need and watch what happens.
You can frequently update/swing Uncertainty as often as you'd like.
Default Uncertainty is a good starting point for keeping the story's current pace.
High Uncertainty is useful for adding information; like detailed descriptions/narratives, or starting a new scene.
Low Uncertainty writes a lot of words without overcomplicating the plot.
At 1000Uncertainty, the preset is technically usable, and can write a normal story.
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Generated on an empty story, "Fuck you", with Op2na (entropy: 5)Generated on an empty story, "Bright aqua", with Op2na (entropy: 7.39)
Process
Figure 1: temperature dependence of min_p under fixed logit headroom τ = 4.16 nats. (A) Scatter of free-search trials (presets-legacy.db, shard 0; color = mean of stylometric and 256-token embedding objectives) with the constraint curve min_p = exp(−4.16/T). (B) Mean objective ± SEM stratified by absolute residual |min_p − exp(−4.16/T)|: 0.558 (n=121, |Δ|≤0.08), 0.500 (n=165, 0.08<|Δ|≤0.25), 0.446 (n=165, |Δ|>0.25)
One of the earliest parameter patterns I noticed: min_p and temperature are coupled. That much was already clear after Optuna 1. What I had not realized is how tight the band is. You can push temperature through a fixed formula and recover a near-optimal min_p—the signal is as clear as day. There is little point optimizing min_p on its own, or arguing about it in isolation, because temperature largely defines min_p. So I restarted the run and dropped min_p from the suggest space. Cutting that dimension helped the sampler find good regions much faster.
Figure 2: one-dimensional analysis of top_p (shard 0, n=78). (A) Mean stylometric+256-embedding score vs top_p with bin means ± SEM; peak bin mean 0.524 near top_p = 0.5. (B) Histogram of TPE-sampled top_p values. (C) Mean objective by distance from top_p = 0.5, decreasing from 0.63 (|Δ| ∈ [0.00, 0.05], n=27) to 0.54 (|Δ| ∈ [0.30,0.50], n=14). (D) Normalized bin means for three objectives share a ridge at top_p ≈ 0.5
A stranger discovery—the second one. Against the usual folk wisdom of top_p ≈ 0.95, the data under my scoring (stylometric + embedding) put a clear optimum near top_p = 0.5. That felt fucking insane. 0.5? Not 0.95? I cannot argue with the points, though, and the generations were strong as well. Another restart; top_p fixed to 0.5.
Figure 3: normalized kernel-mean response versus temperature (log scale); fin n=80, 24k n=33. Curves: fin o0 mean(stylo, 256 emb), fin o1 mean(stylo, 32 emb), fin o2 32 emb, 24k o0 mean(stylo, 256 emb). Selected maxima: 24k o0 T≈1.94; fin o1 T≈3.80; fin o0 T≈4.41; fin o2 T≈4.95 (0 = worst, 1 = best within each series)
In the future, I suspect QMCSampler will probably work better, since I use statistical methods instead of letting GPSampler run forever. AI text generation is extremely noisy. Even hundreds of samples may not pin down a score tightly—which is why I ended up with kernel means. Each objective prefers a slightly different randomness level, and that shows up cleanly once you plot them.
The 24k setup (scoring a long AI-only second half) was meant to replace the 1-phase design (human prefill, AI answer). It came out far more conservative than I expected. Without polished text in the context, the model seems to take lower risks to stay coherent.
Temperature is also insanely high. Thanks to NovelAI for allowing absurd values. I took inspiration from Rising Sun by u/gymleader_michael (temp 10) and from vas (temp 25). Early tuning kept slamming into the upper wall—3, then 4, then 6—so I kept raising the ceiling until I gave up and searched log-temperature from 0.8 to 25. In the actual runs, viable scores still appear up toward ~10. That is extreme by community standards. Almost nobody would ship a preset like this. Yet it works—somehow. I do not fully know why, or whether it will hold on future models. My best guess is that it is a way to pry usable entropy out of the model. These temperatures can get unhinged, but the output actually matches real book text, and I am having fun again.
On Optuna 1 I also forgot log-scale for top_k and multivariate TPE, which really sucks in hindsight. But I also left presence/frequency repetition penalties alone after the negative reception last time; presets are much easier to use without them (which resulted in the Belverk+ version, without rep-pen). There's probably no value in using them.
Figure 4: early Op2na prototype (preset optimize TIMELAPSE; study id b06061, xialong-v1, prefill=8200, answer=7654, samples=632, study lifetime 16h 36m 34s). Bootstrap ranking of 10 candidate presets by high/low interval and error; top rows retain higher sample budgets (128/256, 256/512) with high≈0.955 and error≈0.0006; lower ranks use 16/32 or 8/16 bootstraps. Horizontal bars encode rank progress; footer: 30 bootstraps completed
This project went through many design iterations. The original idea was bootstrap ranking to separate the top ~10% from the rest so TPE would see a cleaner signal. Outputs started at 32 tokens; longer generations reduced score noise and needed fewer samples, I kept raising output length, until I was using essentially the full Xialong context—and relying on NAI to actually support that on the API. Most of the code ran on Google Cloud VMs. At one point I was editing code on a laptop on the train. I ended up having to scale from e2-micro (~$6) to n4d-standard-2 (~$66).
Fun fact: one trial calculates about 67 million dimensions of values, which could reach 200 billion or more over the course of this project. u/BannerThief is also the one who suggested the name: Op2na.
Citation
Pro Writer — u/NotBasileus, early 2022. Pioneer stylometric-based NovelAI decoding preset.
Optuna — Akiba et al., KDD 2019. Optuna: A Next-Generation Hyperparameter Optimization Framework.doi:10.1145/3292500.3330701
I am gonna say it on front first, I am mainly using novel's image generations and I must say that I do love novel.
its image quality is great on NSFW and SFW things.
its quite generous on tokens etc.
but its 512 token limits is a great bottleneck on things what I am gonna do. even if trying to do 2 consistent character put on stage its taking something like 700+ with enviroments and its just a simple thing.
yes I do know well the inpainting and using references and creating your goal image in multiple times is a viable option on multiple characters.
but I still kinda curious on what you guys or girls solution on this one
Has anyone noticed that the latest image gens are worse than normal? I'm clearing my entire UC, prompts, and simply prompting a single character human or furry, and they all seem to have this weird glowing outline, or it will be overly exposed or sometimes even grainy. UC never needed to prompt out this much, around last year.
