Alternatives
Products that do what The No-Code Tool I built for my own AI Experiments does
Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
- 1IS
Everything that would be here is in the README. I hope this gets big, it has tons of potential.
2013 · github.com
- 2IB
I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
2025 · codii.dev
- 3WB
Hi everyone, We have been developing a platform to enable professionals to build AI assistants to help them through their work. After a few months, we realized people are trying to sell basic functionalities that can be built from scratch in a couple of hours. Due to this, individuals who are not familiar with the current SOTA are misinformed about the potential of generative models. So, we decided to open up some of our most popular templates as standalone tools for free to empower individuals and set a solid standard for what people should expect. We believe the barrier to accessing…
2024 · join.modularmind.app
- 4AT
I have a favour to ask. I’ve been working for a while on Kalavai, a project to make distributed AI easy. There are brilliant tools out there to help AI hobbyists and devs on the software layer (shout out to vLLM and llamacpp amongst many others!) but it’s a jungle out there when it comes to procuring and managing the necessary hardware resources and orchestrating them. This has always led me to compromise on the size of the models I end up using (quantized versions, smaller models) to save cost or to play within the limits of my rig. Today I am happy to share the first public version of our…
2024 · github.com
- 5AO
Hey hackers, the world needs more AI researchers with good taste, and hardcore software folks have some of the best. Many software friends mentioned they learn better from implementations than from papers, but existing open-source examples rarely go beyond basic nanoGPT-level demos. To help bridge that gap, I spent the last two months full-time reimplementing and open-sourcing a self-contained implementation of every major modern deep learning technique from scratch. The result is beyond-nanoGPT, containing 20k+ lines of handcrafted, minimal, and extensively annotated PyTorch code. I'd love…
2025 · github.com
- 6TS
Hello Hacker News community! I'm currently working in financial risk management within the banking sector, and I began my career as a Data Science specialist. For quite some time, my friend and I have been developing a small pet project just for fun. This tool has repeatedly helped us save time when testing various hypotheses and machine learning models. The core idea is to combine different scripts—created in various programming languages and virtual environments—within a minimalist graphical interface. Whether you're building models, running a local neural network, or sending requests to…
2024
- 7IE
Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the…
2023 · huggingface.co
- 8DR
The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
- 9IM
I spent the past few weeks making an open source cloud code editing environment with an AI copilot and multiplayer collaboration! It's fully self-hostable in 5-10 minutes. There's a lot of minor improvements to be made, and some are already listed in the Github issues. Let me know what you think and feel free to try it out.
2024 · github.com
- 10FC
Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com
- 11FA
Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
- 12MA
Hi HN, I'm a solo developer learning to code, and I'd love to share my second real project: MapMyLearn, an AI-powered app that automatically generates personalized learning paths based on any topic you input. What it does: Takes a topic (e.g. "history of capitalism", "learn Rust", or "data storytelling") Uses AI to break it down into a structured course with modules and submodules Each submodule includes: - Detailed, pedagogical content (developed based on online sources to mitigate hallucinations) - A quiz of 10 questions - Recommended resources - An AI chatbot for Q&A - Optional audio…
2025
- 13IB
After years of struggling with onboarding to new projects, I got tired of spending weeks just trying to grasp the basics of a codebase. The README rarely tells the whole story, and "just read the code" isn't practical for large repos. I built RepoIQ to create personalized learning paths through any GitHub repository. It analyzes the codebase structure, identifies key components, and creates a step-by-step guide tailored to your learning needs.
2025 · repoiq.be
- 14IB
Hey HN, I've been working on something cool that I wanted to share with you all. It's called Viewpoint, an analytics tool for LLMs like OpenAI, Anthropic models, and Gemini. The idea came from the constant flood of new LLM models and the need to figure out which ones work best for my projects without breaking the bank. With viewpoint, I can track token usage, costs, latency(WIP), and traffic over time, making it easier to compare different models and see which ones perform best and save money. The tool works asynchronously, so it doesn't add any latency to your LLM requests, and you have…
2024 · viewpointhq.com
- 15IB
Hey HN! I just released a suite of AI models for deployment on UAV and other "overhead" devices to provide some understanding of the world below. The objective is to empower all sorts of open-source use cases around search and rescue, wildfire prevention, ground risk mitigation for flight over populated areas etc... The neural networks are trained for a bunch of different devices from big GPUs to tiny edge AI cameras like the Luxonis OAK, with some optimised ones for Nvidia TensorRT and other cool bits and pieces too. The main release package also includes some boilerplate code for running…
2023 · github.com
- 16MD
We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…
2025 · github.com
- 17IC
I spent the past week implementing a 1 Layer Neural Net and training it on MNIST within the visual scripting language provided by scratch.mit.edu. It was tedious, but ultimately not too difficult. The code runs incredibly slowly, so much so that 64 samples of MNIST takes 5+ hours to train on my machine. There were a lot of little mini challenges that were fun to overcome (implementing softmax was very tricky). If you're interested, I encourage you to try and improve on it! More details in the linked blog post.
2024 · bell-boy.github.io
- 18IB
Hi all, I'm sure some of the best engineers out here are having a hard time standing out nowadays. It's hard to evaluate and improve your skills, when AI is writing the code. Especially when a junior dev is sitting by your side and "accomplishing" 2x more than you. I didn't like this reality where the line between real talent and AI slop is blurring, so I decided to create a challenge, purely for the community, that is made to truly give a stage for talented devs to stand out in the age of AI. We encourage devs to bring their agents with them, because the challenge is built to not be…
May 2026 · theincidentchallenge.com
- 19AT
Hi everyone! We just launched Depth AI - a tool that helps you onboard to large and messy codebases. Unlike most dev tools that help in codegen and building smaller apps, this one mainly aims at understanding large repos better - so we have focussed a lot of code search quality. We also launched the first version on product hunt https://www.producthunt.com/posts/depth-ai. Do check us out. Would love to hear feedback here and discuss more how our approach to code search is different.
2024
- 20BC
We are a small group of undergrads interested in building human in the loop coding agents. We dream of a world where building complex agent workflows feels as simple and creative as playing with legos. When we were building stuff we needed a tool that made it easy to try out different code embedding models so that we could see which ones worked best in different scenarios and understand their strengths and weaknesses. So to speed that process up we made PurpleSearch an 'instant' search engine for your local codebases. This tool lets you quickly deploy any open source embedding model on…
2025
- 21AA
Hey HN, I'm an AI enthusiast and I am launching apps that use ML to solve problems that we all have. I realized that there are a lot of deepfake faces on youtube and social media, so I thought it would be useful (and fun!) to have a tool that can bust those AI faces. So I built DeeFace for 2 reasons: 1. Check if the face you're looking at is real or not 2. For fun! It's something that I from half a year ago would look at and aspire to build someday. I think it's soemthing anyone who's just starting out with ML would appreciate. I hope this tool is fun for you to use as it was for me to…
2024 · deefaces.com
- 22FS
Hi everyone! I've been loving building with AI, and over the past few years I've been leaning more and more into Typescript (and bun). My team at inference.net is constantly trying to get more leverage out of AI and find ways to setup our codebase to be able to increase the level of correctness that our AI is able to write code at. This starter repo is a very opinionated way to lay out a repo to lean into AI heavily. It leverages Cloudflare Workers as a deployment target for the API (my goal is to never have to deploy an API on a AWS/Azure/GCP server ever again unless I get to a…
2025 · abeahmed.com
- 23CA
Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
- 24MA
This weekend I built a multi-agent coding system which, quite unexpectedly, beat Claude Code on Stanford's Terminal Bench! The architecture is straightforward, consisting of an orchestrator agent that deploys explorer & coder subagents to complete complex terminal based tasks, utilising an intelligent context sharing mechanism along the way which makes it all work. The repo has a lot of technical details, and all the code and prompts for you to play around with if you'd like! I had a lot of fun making this, I hope you have fun reading the README, using it yourself, or even extending it! As…
2025 · github.com
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