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Alternatives Looking for Open Source SharePoint Alternative with Advanced Metadata and Versioning

I’m setting up document management for a hobby/startup group and I’m hoping to find an open source solution that goes beyond basic file storage. Specifically, we need something that can handle structured metadata from day one, not just folders and ad-hoc tags, but the ability to classify and manage files with rich, enforced metadata.

Core Requirements

• Version history – proper file versioning, not just overwrite
• File sharing / secure access – either built-in sharing or SSO integration
• Advanced metadata classification – enforced options from predefined lists (similar to SharePoint’s managed term store)
• Custom fields – ability to define unlimited metadata fields at either a group or system level
• Flexible views – toggle between simple file listings and rich metadata views
• Smart folders – ideally both flat and folder-based views would be supported

What I’ve Tested So Far

• OwnCloud / OCIS / Nextcloud / OpenCloud – Great for file sharing, but metadata is too limited (just basic tags, no enforcement)
• Papra – Promising new platform, but tagging system still too simple
• OpenKM (Community Edition) – Looks good, but lags behind commercial release by \~3 years and lacks key features
• Paperless NGX / Papermerge / Docspell – Nice for document processing, but no proper versioning (can’t upload revisions under same filename) and no file sharing
• Teedy – Lightweight and easy to set up, but doesn’t cover all of the requirements above
• Seafile – “Smart properties” feature looks perfect, but licensing beyond 3 users makes it un-viable for a small team

We’d really like to avoid being locked into SharePoint early, but we also want the structure in place so we don’t have to migrate later. Any suggestions, experiences, or even partial solutions would be hugely appreciated!

https://redd.it/1n0yxge
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How do you satisfy the GPLv3 in an electron app?

Hi, I'm very interested in publishing my app I've been working on for some time. I'm aware I can publish the source code as GPL - however because it is an electron app, I can't publish the binary unless I offer all source code that contributed to it.

So... is it saying I have to hunt down the source code of electron and all other dependencies I use, then hunt down the source code of all of electron's dependencies, then hunt down the source code of all their dependencies.... And keep all of this available to anyone who downloads my app? It sounds like I'm going to have to preserve multiple gigabytes of source for a <100 MB bundle that's actually <10MB my code... all for what's literally just a webpage? 😬 I feel like it'd be easier to just zip up a web browser with my code and it'd be easier to keep my code free...

Or am I reading this wrong and the GPL need to procure source code doesn't spread down into your dependencies, only up into people who depend on you??

There is an additional problem that I can't guarantee that the code of the dependencies could ever actually become the "object code" of my program since I used the npm hosted versions and I definitely just use the electron that webpack gets for me - but I doubt that's even worth getting into at this point, lol.

Really, all I want is to make sure that whenever my code (incl modified versions of it) does work for anyone, they can actually see the logic that went into the result. I want anybody who runs my code to be able to know it's not scamming them!!

https://redd.it/1n12fm6
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Google Home alternative?

Hello everyone, I'm looking for an alternative to Google Home, where I can control my various smart devices in one app. I know that Home Assistant exists, but you need to self host the server, and I can't leave my computer on 24/7. Does anyone know any FOSS app that let's me control my smart devices without having to host my own server?

https://redd.it/1n142r2
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Making an AI based os/kernel system

Im trying to find people to help in a project the concept is simple an open source os/kernel that use ai as it's center to translate everything including applications into usable apps on the os no more need for thousands of os like linux, android, windows, mac, ios etc... simply using that os as an unification system It need to be easy to install on anything be it a smartphone, computer, mac, etc... as the main os the ai at the center of the os should be allowed to incorporate api and other ai systems automatically into its reasoning and updating itself on security concerns and reasoning automatically it would also work as a node systems with offline capabilities where once a security risk is detected it transmit automatically to other users the fix which is then applied or not depending on user wants akin to any update systems The ai would be the translator, the security, etc... it would basically be the os and the kernel It will also be able to be used beyond devices like computers and into full robotic usage too you want to install it on a vr headset the ai detect the hardware download the needed translating layers adapt the api and core used etc... the os would be able to run everywhere a fridge, a roomba, a smartphone, everything and as open source

You can also directly query the ai at the center of the os using a chatbot system that also adapt depending on the hardware and based on your demand the os could modify itself based on your needs

For the name of the os I don't want it to be pretentious, complicated or weird and i certainly dont want it to look like it belong to someone so I want to keep it as "OS" or "AI OS"

In short I'm trying to find help to make the ultimate self learning os/kernel system using ai as it's center in open source format

I realize the implication of such a project yes it will take years, yes the kernel level will need to be hybrid at first and yes it's basically building skynet, etc... no need for condescending comment thank you for reading


https://redd.it/1n1835g
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How to start contributing to open source?

I am a frontend developer with around 2.5 years of experience and I want to start contributing to open source but don't know where to start. Any ideas?

https://redd.it/1n19uu4
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Need feedback on my own search engine!

Hi everyone!

I've been trying to build a search engine, for people to use as an alternative to already open source search engines like SearX, or as an alternative for privacy conscious ones like DDG or Startpage, and I need your reviews and feedback to improve it! :)

I'm trying to be focused on bringing the open source benefits of SearX, and modern UI's and features like DDG-like search engines. We have AI summaries for search queries, beautiful widgets for Wikipedia, in-search Video and News recommendations and a few more services that I believe you guys will love!

It has been a few months since I've started, feedback and suggestions were mostly from some local communities interested in this topic, and I want to make it a bit more recognized in the internet.

Feel free to criticize! You can reply to this post or use the feedback button at the right corner of the search tab. Thank you!

Site: https://tekir.co
Source: https://github.com/computebaker/tekir

https://redd.it/1n1cdgb
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Call for contributors, testers & feedback on Watchflow – Agentic GitHub Guardrails

Meet Watchflow - Agentic Github Guardrails!

It’s early-stage and not yet production-hardened, but it’s already functional and covers key features especially around workflow governance.

We’d love help from the community - whether you want to:

* Contribute code (Python, LangChain/LangGraph)
* Test workflows and share feedback
* Explore GitHub protection rules and governance in plain language

You can define GitHub protection rules in natural language and enforce them in real time via YAML. We’re eager to hear from solo devs, teams, or anyone curious about workflow guardrails.

https://github.com/warestack/watchflow
https://watchflow.dev/

https://redd.it/1n1c3k8
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Why Open Source API Testing Tools Are Gaining So Much Momentum?

In recent years, developer processes to test and ship software have been evolving rapidly. In the past, large enterprises utilized commercial, expensive proprietary suites for testing software; we are now seeing an emergence of open source API testing tools, which is not just about saving money.



There are a few reasons why they are on the rise:

Community driven: Open source tools are improved consistently by thousands of contributors across the world. Bugs are fixed quickly, integrations are added rapidly, and capabilities are developed faster than a vendor could ever deliver.

Transparency & Trust: Since source code is publicly accessible, teams can trust and validate what is under the hood, this is significant especially concerning security and compliance.

API First: In a world where product development and architecture prioritizes micro services or API first, testing APIs at the level of performance testing, contract testing, or uptime monitoring becomes more mission-critical. Open source tools shine in these aspects because they evolve the fastest in this environment.

Value and Flexibility: Instead of being beholden to a vendor's ecosystem, dev teams can evolve open source tools with their stack as they scale.


What's also cool is that open source projects are not just closing the gap -- in many cases have become even better, more reliable and easier to use than the proprietary options. Many modern day QA teams are blending open source frameworks (like Playwright, Cypress or Postman's open tooling) with lightweight AI powered helpers for test generation and self-healing, taking repetitive tasks off their plates.

Again, it leads to the larger question: as automating software testing becomes more prevalent, and open source tooling is advancing at such a rapid pace, could we be at a point where community-built products establish standards for enterprise-grade software testing?

I'd love to hear from folks here:

1. Are you using open source tooling for testing APIs?
2. What has been the impact, if any, on the reliability and speed of the testing for your teams?
3. Where do you still find proprietary tooling to have an advantage?

https://redd.it/1n1g8rb
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http-shadower: open source app to replicate production traffic to lower environments

Just wanted to share a small project that I built in case it is useful for anyone.

https://github.com/MugenTwo/http-shadower

HTTP Shadower is a Spring Boot application that intercepts production HTTP requests and intelligently forwards them to multiple environments (DEV/ITG/STAGE) while ensuring your users always receive responses from your production system.

Common Use Cases
1. Staging Environment Validation.
Forward 100% of production API traffic to your staging environment to ensure it handles real-world scenarios before deployment.

2. New Feature Testing.
Deploy new features to a separate environment and shadow production traffic to validate behavior without risking user experience.

3. Database Migration Testing.
Test database schema changes against real query patterns by forwarding production traffic to environments with new database structures.

4. Load Testing with Real Patterns.
Use actual production traffic patterns and volumes to load test your infrastructure instead of artificial load testing tools.

5. API Version Compatibility.
Ensure new API versions are compatible with existing clients by forwarding real client requests to both old and new API versions.

https://redd.it/1n1hp26
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Decentralized Operating System

Hey guys, I've been working on a new protocol called the Marketplace which is a decentralized operating system that co-ordinates and economizes the execution of computational work across a peer-to-peer network of nodes. Where there is no barrier to the node participation.

Unlike proof-of-work systems, where nodes burn large amounts of energy to solve "non-useful" puzzles, the Marketplace organizes a peer-to-peer market of computational trade where nodes offload useful computational work called "jobs" directly to each other and pays in the system's native cryptocurrency, goldcoin(GDC). Effectively redirecting energy into real economic growth.

Security without "Staking" is achieved using Proof-of-Capability (PoC), a new "sybil-resistant" mechanism that selects and incentivizes a small committee (“whiterooms”) to validate and reach consensus on the result of jobs without boggling down the entire network with redundant execution. This allows the amount of jobs handled in parallel to scale directly with the amount of nodes on the network analogous to an OS on a multi-core device.

Real utility then comes from the "services layer" where nodes can compose stalls(modular services) into larger digital structures(e.g websites), and execute them regardless of size in near constant time by taking advantage of the parallel execution environment of the marketplace. The system’s monetary policy dynamically adjusts issuance such that price of execution is constant regardless of network load.

Whitepaper (PDF):

https://github.com/bajoescience/Marketplace/blob/master/Whitepaper.pdf

I’d appreciate feedback on the design, especially on consensus security and

the economic model, Thanks.

https://redd.it/1n1jc7i
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How do I implement a custom log storage system? something similar to grafana loki

I am building a software system and one of the features it requires is log storage and having the ability to query those logs, just like Grafana loki does. Do to organisation policy, using Loki or any external log storage system is not an option.

Anyone have an idea on how i can do this?

https://redd.it/1n1g29f
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Testing waters: what do you think of my open source karting project?

Hello,

I have recently started an open source project, more specifically a karting game similar to Mario Kart (arcade physics, items, etc.). I know that Super Tux Kart exists, but wanted to create my own, experimenting with game design.

The most prominent characteristic is that all races are based off Open Street Map. Which means you race into existing places reconstructed and remodeled using topologic and OSM data.

I'll continue working on it because it is fun and extracts me a bit off life chaos, though probably less as I also have another project to maintain (that I need for myself to be updated).

I was just curious about what people think of the idea. Notably to know if developing multiplayer is worth the hassle if I'll ever be playing alone.

There is only a Windows build for now but I want to support Linux and Android as well. Still, it is a Godot project, so it should be easily run from source.

I am also open to feedback regarding the overall project structure.

Repo: https://github.com/Picorims/open-street-kart
Video: https://youtu.be/keJRGv7oMgU

Thanks for reading.

https://redd.it/1n1mz45
@r_opensource
I built an open-source CSV importer that I wish existed

Hey y'all,

I have been working on an open source CSV importer that also incorporates LLMs to make the csv onboarding process more seamless.

At my previous startup, CSV import was make-or-break for customer onboarding. We built the first version in three days.

Then reality hit: Windows-1252 encoding, European date formats, embedded newlines, phone numbers in five different formats.

We rebuilt that importer multiples over the next six months. Our onboarding completion rate dropped 40% at the import step because users couldn't fix errors without starting over.

The real problem isn't parsing (PapaParse is excellent). It's everything after: mapping "Customer Email" to your "email" field, validating business rules, and letting users fix errors inline.

Flatfile and OneSchema solve this but won't show pricing publicly. Most open source tools only handle pieces of the workflow.

ImportCSV handles the complete flow: Upload → Parse → Map → Validate → Transform → Preview → Submit.

Everything runs client-side by default. Your data never leaves the browser. This is critical for sensitive customer data - you can audit the code, self-host, and guarantee that PII stays on your infrastructure.

The frontend is MIT licensed.

Technical approach

We use fuzzy matching + sample data analysis for column mapping. If a column contains @ symbols, it's probably email.

For validation errors, users can fix them inline in a spreadsheet interface - no need to edit the CSV and start over. Virtual scrolling (@tanstack/react-virtual) handles 100,000+ rows smoothly.

The interesting part: when AI is enabled, GPT-4.1 maps columns accurately and enables natural language transforms like "fix all phone numbers" or "split full names into first and last". LLMs are good at understanding messy, semi-structured data.

GitHub: https://github.com/importcsv/importcsv 
Playground: https://docs.importcsv.com/playground 
Demo (90 sec): https://youtube.com/shorts/Of4D85txm30

What's the worst CSV you've had to import?

https://redd.it/1n1nbub
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