Yeah, second this. Wazuh has a great docker image that's maintained by the project itself. https://documentation.wazuh.com/current/deployment-options/docker/wazuh-container.html https://github.com/wazuh/wazuh-docker

@vladimir-d said in netbox - tools for servers: I've packaged netbox application available at https://git.cloudron.io/vladimir.d/netbox Just a few notes: For now I haven't managed to run it properly as WSGI app with gunicorn. It's taking lots of server resources. It's running using the Dev server. https://docs.netbox.dev/en/stable/installation/3-netbox/#test-the-application Super Admin username is specified in start.sh, the Postgress password is taken for Super Admin. Hi , is this app still running. My testride was not successful. Greetings

Indeed, that's an amazing app that I know for several years and it's very well done, I've also tried it in the past but didn't have any use of it at that time. Cool to see it is still alive, it was considered as what was called as an "Intranet" application, a term that I do not hear of much anymore nowadays.

Main Page: https://umap-project.org/ Git: https://github.com/umap-project/umap/ Licence: AGPL v3.0 Docker: Yes Demo: https://umap.openstreetmap.de/en/map/new/#6/51.000/2.000 Summary: uMap lets you create maps with OpenStreetMap layers in a minute and embed them in your site. Because we think that the more OSM will be used, the more OSM will be improved. Built on top of Django and Leaflet. Notes: There is a lot of activity on development. Alternative to / Libhunt link: https://selfhosted.libhunt.com/umap-alternatives Screenshots: images / project logo etc [image: 1724489543299-brave_3eueciri5x-resized.png] [image: 1724489543673-brave_ft3k9fcecv-resized.png]

Self-hosting info here https://trigger.dev/docs/open-source-self-hosting

@nichenqin looks interesting I only recently came across Bun, looking to explore it. More relevant, I can see a lot of use cases for Undb.

All right, these are my impressions of Recogito Studio after the software demo: The software seems very mature. For users, there are: the possibility to reply to comments Comments can be private, read-only or only visible to certain groups You can create reading assignments and link them to documents Not only texts, but also images can be annotated annotations can be exported as CSV (PDF export is in the making) annotations can contain rich media (e.g. embedded youtube videos or images) For admins: can define different roles (instructors, students) Login is possible via SAML The software is GDPR-compliant in this short video, you can see how the software works: [image: 0610.mp4.gif] I pointed the team to this very thread, maybe someone of the developers might join this discussion. Again, I'd be very glad if we had Recogito Studio available on Cloudron.

@LoudLemur more proof that self-hosting is best approach (not immune but …)

@marylou yeah, or even just gath.io which does the job pretty nicely for most simple needs.

@girish thanks for your answer, even if it's too bad... As far as I can see, Kùzu is a database that can also be connected for storage to DuckDB or Postgresql, I don't know if that makes it more of a convenience for you, but in case... I wouldn't mind having a Supabase running outside of Cloudron connected to Kùzu managed on Cloudron.

Here is their Docker Hub page https://hub.docker.com/r/wisemapping/wisemapping

Is there any update here? We'd like to deploy it to our Cloudron instance

Hi, micmc! This is what Llama 3.1 405b has to say about the two: "VoiceChat (lhl/voicechat2): Features: Local AI voice chat system Uses WebSockets for communication Fully local (voice-to-voice) implementation Uses Whisper large-v2 (Q5) for speech recognition Utilizes Llama 3 8B (Q4_K_M) for language processing Employs tts_models/en/vctk/vits (Coqui TTS default VITS models) for text-to-speech Pros: Fast performance: Voice-to-voice latency is in the 1-second range on high-end GPUs Fully local: Doesn't require internet connection for core functionality Open-source: Available on GitHub for customization and community contributions Utilizes state-of-the-art AI models for speech recognition and language processing Cons: Requires powerful hardware: Optimal performance seems to be on high-end GPUs (e.g., AMD RDNA3 card) May have limited features compared to more established voice chat solutions Potentially complex setup for non-technical users Limited documentation available OpenWebUI: Features: Web-based user interface for AI interactions Docker and Kubernetes support for easy deployment Integration with OpenAI-compatible APIs Customizable OpenAI API URL Support for both Ollama and CUDA-tagged images Functions and pipeline support for extended capabilities Pros: Effortless setup using Docker or Kubernetes Flexible API integration (OpenAI, LMStudio, GroqCloud, Mistral, etc.) Web-based interface for easy access Extensible with functions and pipelines Active development and community support Supports multiple deployment options (pip, Docker, Kubernetes) Cons: Documentation may be lacking in some areas, making integration challenging Primarily focused on text-based interactions, unlike VoiceChat's voice-to-voice approach May require more setup for voice capabilities (if needed) Potential learning curve for utilizing all features and integrations Comparison: Focus: VoiceChat is specifically designed for voice-to-voice AI interactions. OpenWebUI is a more general-purpose web interface for AI interactions, primarily text-based. Deployment: VoiceChat seems to require local installation and configuration. OpenWebUI offers multiple deployment options, including Docker and Kubernetes, making it potentially easier to set up and scale. Flexibility: VoiceChat is focused on local, offline use with specific AI models. OpenWebUI offers more flexibility in terms of API integrations and customization options. User Interface: VoiceChat likely has a minimal interface focused on voice interactions. OpenWebUI provides a web-based interface that can be accessed from various devices. Community and Development: Both are open-source, but OpenWebUI appears to have more active development and a larger community. Use Case: VoiceChat is ideal for users needing offline, voice-based AI interactions with low latency. OpenWebUI is better suited for users who need a flexible, web-based interface for various AI interactions and integrations. In conclusion, the choice between VoiceChat and OpenWebUI depends on the specific needs of the user. VoiceChat is more specialized for voice-based AI interactions, while OpenWebUI offers a more versatile platform for general AI interactions with easier deployment options. Users prioritizing voice capabilities and offline use might prefer VoiceChat, while those needing a flexible, web-based solution with various integrations might find OpenWebUI more suitable."

Late to the party here but Kafka has my preference due to a few features it has over RabbitMQ. In the process of packaging it myself as a test