Work · alternatives · 2026
24 alternatives to Evaluating LLMs on creative writing via reader usage, not benchmarks
Hey HN! I'd love to get some people to mess around with a little side project I built to teach myself DSPy! I've been a big fan of reading fiction + webnovels for a while now, and have always been curious about two things: how can LLMs iteratively learn to write better based on reader feedback, and which LLMs are actually best at creative writing (research benchmarks are cool, but don't necessarily translate to real-world usage). That's exactly why I built narrator.sh! The platform takes in a user input for a novel idea, then generates serialized fiction chapter-by-chapter by using DSPy to…
Narrator.sh is a platform that generates serialized fiction chapter-by-chapter based on user story ideas. It uses DSPy to optimize LLM writing output by incorporating real reader feedback across chapters, employing… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
I think LLMs are overused to summarise and underused to help us read deeper. I built a system for Claude Code to browse 100 non-fiction books and find interesting connections between them. I started out with a pipeline in stages, chaining together LLM calls to build up a context of the library. I was mainly getting back the insight that I was baking into the prompts, and the results weren't particularly surprising. On a whim, I gave CC access to my debug CLI tools and found that it wiped the floor with that approach. It gave actually interesting results and required very little orchestration…
Jan 2026 · trails.pieterma.es · its alternatives →
- 2LS
Greetings, creator here! I've been working on a new blogging platform specifically for lists on and off for a few months now and I'm excited to officially announce its launch. After seeing https://charm.sh a few months ago, I've been enamored by the idea of SSH apps. I decided that a blogging platform focused on developers could be the perfect use case for an SSH app. Also, I love writing lists. I think restricting writing to a set of lists can really help improve clarity in thought. The goal of this blogging platform is to make it simple to use the tools you love to write and…
2022 · lists.sh · its alternatives →
- 3IS
Hi everyone, For the past couple months I've been working on a website with two main features: - https://book.sv - put in a list of books and get recommendations on what to read next from a model trained on over a billion reviews - https://book.sv/intersect - put in a list of books and find the users on Goodreads who have read them all (if you don't want to be included in these results, you can opt-out here: https://book.sv/remove-my-data) Technical info available here: https://book.sv/how-it-works Note 1: If you only provide one or two…
Nov 2025 · book.sv · its alternatives →
- 4
Documents the style side of the short-story Creative Writing LLM benchmark: we generated many short stories with a range of LLMs, then analyzed those stories for stylistic fingerprints and within-model diversity. This study focuses on how models write, how their outputs differ, and how varied each m
2025 · github.com · its alternatives →
- 5
Recently I've been working on making LLM evaluations fast by using bayesian optimization to select a sensible subset. Bayesian optimization is used because it’s good for exploration / exploitation of expensive black box (paraphrase, LLM). I would love to hear your thoughts and suggestions on this!
2024 · github.com · its alternatives →
- 6
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
- 7
When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai · its alternatives →
- 8
Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com · its alternatives →
- 9
Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…
2024 · github.com · its alternatives →
- 10AN
Over the last two years, we’ve seen just how quickly science can move when it’s conducted out in the open, and the focus is on content rather than the publishing process. We’ve built a new way for researchers and scientists to communicate and share their findings with the world - rethought from first principles, with a lot more coming soon. Free to use, and available now for anyone with a university email address. We’re whitelisting organizations that conduct and publish research on a rolling basis. Please forward feedback and thoughts to [email protected] or comment here!
2022 · dystr.com · its alternatives →
- 11
A great way to enhance chatbots is to allow them to look up information for context, typically using a vectordb. If you have writings you would like to share with others, you can offer a server that allows others to do semantic lookup, and that way anyone can have a chatbot which can pull from your writing. The goal of this project is to have a protocol that makes that easy. Strictly speaking, the protocol is for semantic retrieval and doesn't require using LLMs although LLMs are the motivating application. For far more details and how to get a demo up and running, see the readme.
2024 · github.com · its alternatives →
- 12
A blog platform for hackers
2022 · prose.sh · its alternatives →
- 13MF
Just finished my second year at college studying Computer Science, and wanted to try and gain experience as a full stack dev this summer, so I made a website that allows users to create stories using openai's API, using embeddings for custom terms users can define, and create short stories and chapters alike. I'm mainly just looking for some feedback on how I can improve it or make it more presentable, so any help/feedback is welcome and appreciated!
2023 · plotnotes.ai · its alternatives →
- 14
Nowadays I review a lot of code locally that was written by llms. I used to review my own code using git + delta. It started to feel limiting with the amount of code written by llms. When looking at a large diff on Friday I pointed an llm at diffs.com and trees.software and told it to build an app. It only took 16 minutes, is extremely fast for large diffs, beautiful and minimal. Today I polished it up and added all the features that I need. It has file filters, search, an llm walkthrough mode, and review comments that you can paste back into your llm. I will be using Codiff a lot, and can…
May 2026 · github.com · its alternatives →
- 15
Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them / eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…
2025 · github.com · its alternatives →
- 16
Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!
Nov 2025 · github.com · its alternatives →
- 17UD
I've been working a fair bit with DSPy lately, and I did some work in combining the benefits of vector search and LLMs (via a DSPy pipeline) to disambiguate records with a high degree of accuracy to help enrich a dataset. The blog post shows how this approach scales well, is very cost-effective and super concise - all it takes is < 100 lines of DSPy code and it all runs async. The code to reproduce is in this repo if anyone's interested (all tools are 100% free and open source, and the methodology will work with open weight LLMs too).…
2025 · blog.kuzudb.com · its alternatives →
- 18
FindReads▲10I’ve always felt that most book recommendation engines are shallow, they either use tags or “people also liked” data. I wanted something that actually understands what you mean when you say “slow burn sci-fi with emotional depth” or “books like Harry Potter.” So I built FindReads . It uses GPT to interpret your prompt, queries for books, and returns real titles that fit the vibe. Stack: Next.js, OpenAI API, MongoDB, deployed on Vercel. It’s still a work in progress — the results are surprisingly good for some moods, weird for others, but I’d love feedback from the HN crowd on how you’d…
2025 · findreads.app · its alternatives →
- 19
Let's try a small experiment with LLMs that have a large context length: feed an entire book into the context window and ask it to generate a list of characters, their relationships, and physical descriptions—data that can later be used for image generation. In this repository, you can find two tools: a script that extracts data from book text using an LLM (Gemini or OpenRouter API) and an HTML/JS (D3) visualization of the character graph. An external text-to-image model can be used to generate character illustrations (a Google Colab example is provided). Explore the visualizations,…
2025 · github.com · its alternatives →
- 20
It’s written in Python and I call it GoalChain. It lets you build a conversation flow graph that the user traverses. When there’s enough input it spits out a dictionary with the defined fields. Otherwise it will jump state to state as led by the user. It was fun to write, and it’s surprisingly effective if you keep in mind you’re prompt-engineering every string and field name. README.md has a mini-tutorial. Would be cool to get some ideas for how to build it further and what improvements I could make.
2024 · github.com · its alternatives →
- 21
This benchmark tests how well LLMs incorporate a set of 10 mandatory story elements (characters, objects, core concepts, attributes, motivations, etc.) in a short creative story - lechmazur/writing
2025 · github.com · its alternatives →
- 22
hi everyone. how does moving llm call prompts and output structure definitions away from code into configuration land sound? would you use something like this if it was stable and well documented enough? please don't hold back the criticism. i appreciate all feedback (constructive & otherwise).
2024 · github.com · its alternatives →
- 23
I've been wondering how I could use LLMs to help me write, without taking my own voice away. I arrived at a workflow where the AI has strict instructions not to give me any text, just to give me tips, but it was clunky to see which parts of the text the critique referred to. To solve it, I made Lucid. I made it mostly for myself, but I added a "bring your own key" system for others to use it. I hope you like it!
May 2026 · writelucid.cc · its alternatives →
- 24KA
Knit was created to solve pains of other LLM playgrounds. Some of the highlights: - Smart prompt builder, create prompt with simple requirement and few shot learning, fast and effortlessly. - Function call simulation, visualize the function callings and you can also setup a mocked value to return. - Support OpenAI/Anthropic/Azure models. - Manage prompts with projects and members. - And so much more! I have been developing Knit by myself for over 4 months now, and am looking for ways to improve it. Any feedback is appreciated.
2023 · promptknit.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →