Alternatives
Products that do what Dstack – a command-line utility to provision infra for ML workflows does
Hi. :) I’m Andrey, the creator of dstack. I started this project while I was working at JetBrains where I helped the PyCharm team to improve support for Jupyter notebooks. As I was in close contact with many ML devs (who used PyCharm) I was able to see their struggle with running ML workflows. Unlike traditional dev workflows, ML workflows are difficult to run on a local machine (due to the lack of memory, more CPUs/GPUs, etc). This is why people often have to use remote machines (e.g. via SSH), or adopt one of the end-to-end MLOps platforms. Using remote machines is not difficult but…
- 1DA
Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
- 2
- 3PI
Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
- 4
- 5SP
Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
2020
- 6
- 7IM
Heya HN, after spending +1 year building an ML-driven analytics product (that didn't pan out unfortunately), I've pivoted to solving a problem my team and I found while building the previous product … why the hell is it so hard to move a model from a Jupyter notebook, to a development server, then to a production pipeline!? To solve this my team and I started the open source KitOps project under the Apache 2 license. KitOps includes the Kit CLI that uses a Kitfile manifest to create ModelKits: 1. The kit CLI packages your model, datasets, code, and configuration into an OCI compliant…
2024 · kitops.ml
- 8
- 9SV
I've already posted yesterday, but I'd really love to get comments, any kind of questions, suggestions and help would be greatly appreciated as it's an Open Source project of mine (and was for others during my studies at the University of Konstanz 6 years ago). Since then I spent countless ours to bring forth the idea of a versioned storage system, especially well suited for analytical tasks for timd-varying data. Especially I'd love to discuss what documentation you need, which next steps are necessary (JSON, Cloud...), API additions or changes... I've updated the README quiet a bit, such…
2018
- 10MW
This is a little project I've been working on for a while in order to better learn Python. Although IRC may not exactly be the most exciting medium, I still find it to be fun and useful, this interest lead me to writing a bot. In doing this I realized that what would actually be more interesting would be if I had a framework. There may already be such a thing, certainly there are IRC libraries, but I don't know if they're well-suited to deploying bots. At any rate if for no other reason than the fact that I am relatively new to programming and eager to learn I decided to build a framework.…
2011
- 11
- 12GB
Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…
2024 · github.com
- 13CA
A recent HackerNews comment - “For one programmer's hourly cost, you could run 4000 CPU cores continuously. Can there really be no practical way to apply thousands of cores to boosting the programmer's productivity?” https://news.ycombinator.com/item?id=19339467 This is what we have come up with. The current productivity tools - Slack, Asana, Trello, Facebook Workplace, etc. - are great, but lack direct access to your code. Building a tool directly around the code makes it more powerful for software developers: CoDiff. https://codiff.com The foundation of CoDiff is a…
2019
- 14UD
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
- 15LS
LLMStack is a low-code platform that can be used to build LLM apps, chatbots and integrate AI experiences into existing products/workflows. It comes with everything out of the box that one needs to build LLM apps locally. It can also be used in a multi-tenant setting, making it available for everyone to use in an enterprise. Some highlights of the platform: - Chain multiple LLM models allowing for complex pipelines - Includes a vector database and necessary connectors to help enrich LLM responses with private data - App templates tailored to specific use cases to quickly build LLM apps…
2023 · github.com
- 16AD
I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
- 17AI
I had an idea a couple days ago and I went with it. Basically, the idea was to create an IRC channel to help people find jobs; computer related jobs, in particular. There would be a bot to display job listings. So I started working on a first take on the bot. I decided to use Python because I love the language and I wanted to get more experience with a its libraries. TwitterBot (or JobFeeder on ##jobfeed) as I call it, uses Twisted (https://pypi.python.org/pypi/Twisted) and Twitter (https://pypi.python.org/pypi/twitter)for now. Basically, it gets the…
2014
- 18WB
Here is a production-first Keras-inspired LM framework, built with the advice of François Chollet (ex-Google, creator of Keras and ARC-AGI), our technical advisor. This system have already been deployed in production with our clients (which is why we have already every LLMOps practice implemented). It is also compatible with Jupyter and Marimo to integrate seamlessly in you Data Scientists workflows. You can try the code examples online on HF space and you can find more information in the documentation and FAQ. If you have any feedback for us don't hesitate to join our discord! More releases…
2025 · github.com
- 19BD
Hi everyone, I'd like to share my project, bridge-ds - a lightweight Python framework that simplifies how ML practitioners manage and interact with datasets. Why bridge-ds? It abstracts the repetitive parts of dataset handling in real-world ML workflows, but remains lean enough as to not force opinionated workflow or unnecessary dependencies. bridge-ds uses two complementary approaches: - Macro-level: Treat your entire dataset like a DataFrame—filter, sort, and modify with familiar, intuitive operations. - Micro-level: Efficiently handle individual samples with lazy loading, caching, remote…
2024 · github.com
- 20UI
Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com
- 21LD
Hi HN! This is Qian here with Peter (KraftyOne) and Jeremy (jedberg). We’re building DBOS, an open-source, lightweight durable workflows library that you can add to Python apps in just a few lines of code. It’s comparable to popular open-source workflow and queue libraries like Airflow and Celery, but more lightweight with a greater focus on reliability and automatically recovering from failures. Our goal in building DBOS is to make workflows lightweight and flexible so you can add them to your existing apps with minimal work. Everything you need to run durable workflows and queues is…
2025 · github.com
- 22MM
I kept on reading you guys on how to do it, how not to do it. On January I started with thinkpython, learn python the hard way, mit course on programming, and every other python material I found. You just need to find the best resourse for YOU. I did Udacity's CS253 course, got my certificate and made my MVP! If your one of those guys like me, just get your ideas out there and the project will push you forward. Farm management software in South America is broken. We still have cd and downloadable updates. We've seen www.farmlogs.com and www.farmeron.com for USA and Europe. How about…
2012
- 23IM
Hi HN, I’m one of the devs behind StarDesk, a P2P-first remote desktop we’ve been building for ~1 year. We started this partly out of frustration: some popular RDP tools haven’t seen meaningful updates in a long time, and long-standing issues are often left unaddressed. As devs, we really dislike software that stagnates once it “works well enough”. StarDesk is our attempt to do it differently. What we focus on: -P2P by default (relay as fallback) -Low RTT + low jitter > chasing max bitrate -Encoder / input path tuned for real-time interaction -Modern E2EE (TLS/DTLS) UX-wise, setup…
Jan 2026 · stardesk.net
- 24IB
As a software engineer, my reflex has always been to script everything I can. Scripting is easy, but everything around it is tricky: scripts have to run somewhere, they need access to credentials, they need to be monitored. None of it is simple. No-code automation platforms such as Zapier or IFTTT are too restrictive for technical tasks; CI/CD platforms make it easy to script tasks related to a repository, but are limited when trying to do anything else. I wanted the low level control you have when writing scripts while retaining the comfort of a platform managing execution for me. So I…
2022 · exograd.com
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