Community Apps

minimal ics / iCal / Calendar hoster, is basically just a minimalistic webserver which will just publish the "file.ics" in the data directory. I use it to provide the Ical to Home Assistant for the garbage collection.

VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. TLDR: It is a faster, more lightweight replacement to InfluxDB/TimescaleDB/etc (up to 20x faster data digestion, up to 7-10x less ram usage). Can be used in place of InfluxDB in many apps such as HomeAssistant. Includes a great web UI for query exploration. For HomeAssistant: drop in replacement for InfluxDB, see https://community.home-assistant.io/t/influxdb-vs-victoriametrics/453361 Git repository: https://github.com/VictoriaMetrics/VictoriaMetrics Dockerhub: https://hub.docker.com/r/victoriametrics/victoria-metrics Website: https://victoriametrics.com VictoriaMetrics prominent features: - Long-term storage for Prometheus. - Drop-in replacement for Prometheus and Graphite in Grafana. - Easy setup and operation with a single executable and configuration via command-line flags. - Fast backups with vmbackup/vmrestore tools. - Implements MetricsQL query language. - Global query view for multiple data sources. - High performance and scalability, outperforming InfluxDB and TimescaleDB by up to 20x. - Efficient RAM usage, 10x less than InfluxDB and up to 7x less than others. - Optimized for high-churn time series data. - High data compression, storing up to 70x more data points in limited storage. - Ideal for high-latency IO and low IOPS storage. - Can substitute moderately sized clusters of competing solutions. - Protects data from corruption on unclean shutdown. - Supports various metrics protocols, including Prometheus, InfluxDB, Graphite, OpenTSDB, and more. - Offers stream aggregation, metrics relabeling, and series limiting. - Suitable for diverse data sources like APM, Kubernetes, IoT, financial data, and more. - Open source cluster version. - Compatible with NFS-based storages like Amazon EFS and Google Filestore.

YouTube Transcript to Article YouTube Transcript to Article is a Docker-based Python project that provides an API for converting YouTube transcripts into professional articles using OpenAI's ChatGPT. This tool automates the creation of summaries or detailed articles from YouTube video content, making it easy to generate professional write-ups from video transcripts. Features Automatic Transcript Retrieval: Fetches the transcript of a YouTube video in its original language, handling both video URLs and IDs. Article Generation: Generates a professional article from the transcript, with options for brief or detailed formats. Customizable Output Language: Allows you to specify the output language, with the default being the video's language. Minimalist Web Interface: Provides a simple, user-friendly web interface to easily input video IDs or URLs and generate articles. Dockerized Deployment: Easy deployment with Docker, including integration options for Home Assistant and MQTT. You will need a OpenAI API key.