Telegram is a proprietary messenger that gained some popularity recently. It has FOSS client, API and binding for the API. It has private chats, group chats and "channels". Channels are content feeds.
RSS allows users to access updates to online content in a standardized, computer-readable format.
Telegram requires an account to read channels. Creating an account requires you to give Telegram your phone number. Unfortunately, some good content is being posted to Telegram channels. But it is unacceptable for some people to give phone number to Telegram, which is ran by some Russian billionaires, who might turn out to be evil. Also, RSS/Atom is standardized and has a lot of great readers.
The idea is to create a FOSS gate that would allow to convert Telegram channels to RSS/Atom. The gate will be hosted somewhere.
UI: A user posts channel name into input, presses "submit" and URL with RSS/Atom feed is being created. Posts from channels should be fetched in the background, for example, with cron jobs
No Hackers yet
This project is part of:
Hack Week 17
Activity
Comments
Be the first to comment!
Similar Projects
Ansible for add-on management by lmanfredi
Description
Machines can contains various combinations of add-ons and are often modified during the time.
The list of repos can change so I would like to create an automation able to reset the status to a given state, based on metadata available for these machines
Goals
Create an Ansible automation able to take care of add-on (repo list) configuration using metadata as reference
Resources
- Machines
- Repositories
- Developing modules
- Basic VM Guest management
- Module
zypper_repository_list
- ansible-collections community.general
Results
Created WIP project Ansible-add-on-openSUSE
Make more sense of openQA test results using AI by livdywan
Description
AI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails.
User Story
Allison Average has a puzzled look on their face while staring at log files that seem to make little sense. Is this a known issue, something completely new or maybe related to infrastructure changes?
Goals
- Leverage a chat interface to help Allison
- Create a model from scratch based on data from openQA
- Proof of concept for automated analysis of openQA test results
Bonus
- Use AI to suggest solutions to merge conflicts
- This would need a merge conflict editor that can suggest solving the conflict
- Use image recognition for needles
Resources
Timeline
Day 1
- Conversing with open-webui to teach me how to create a model based on openQA test results
- Asking for example code using TensorFlow in Python
- Discussing log files to explore what to analyze
- Drafting a new project called Testimony (based on Implementing a containerized Python action) - the project name was also suggested by the assistant
Day 2
- Using NotebookLLM (Gemini) to produce conversational versions of blog posts
- Researching the possibility of creating a project logo with AI
- Asking open-webui, persons with prior experience and conducting a web search for advice
Highlights
- I briefly tested compared models to see if they would make me more productive. Between llama, gemma and mistral there was no amazing difference in the results for my case.
- Convincing the chat interface to produce code specific to my use case required very explicit instructions.
- Asking for advice on how to use open-webui itself better was frustratingly unfruitful both in trivial and more advanced regards.
- Documentation on source materials used by LLM's and tools for this purpose seems virtually non-existent - specifically if a logo can be generated based on particular licenses
Outcomes
- Chat interface-supported development is providing good starting points and open-webui being open source is more flexible than Gemini. Although currently some fancy features such as grounding and generated podcasts are missing.
- Allison still has to be very experienced with openQA to use a chat interface for test review. Publicly available system prompts would make that easier, though.
Symbol Relations by hli
Description
There are tools to build function call graphs based on parsing source code, for example, cscope
.
This project aims to achieve a similar goal by directly parsing the disasembly (i.e. objdump) of a compiled binary. The assembly code is what the CPU sees, therefore more "direct". This may be useful in certain scenarios, such as gdb/crash debugging.
Detailed description and Demos can be found in the README file:
Supports x86 for now (because my customers only use x86 machines), but support for other architectures can be added easily.
Tested with python3.6
Goals
Any comments are welcome.
Resources
https://github.com/lhb-cafe/SymbolRelations
symrellib.py: mplements the symbol relation graph and the disassembly parser
symrel_tracer*.py: implements tracing (-t option)
symrel.py: "cli parser"
Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov
Project Description
Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.
In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.
Continue with implementation of the missing features and improve the existing implementation:
authentication (need to decide how it should be/or not related to salt auth)
web service providing the control of states deployment
Goal for this Hackweek
Implement missing key features
Implement the tool for state deployment control with CLI
Resources
https://github.com/openSUSE/saline
Team Hedgehogs' Data Observability Dashboard by gsamardzhiev
Description
This project aims to develop a comprehensive Data Observability Dashboard that provides r insights into key aspects of data quality and reliability. The dashboard will track:
Data Freshness: Monitor when data was last updated and flag potential delays.
Data Volume: Track table row counts to detect unexpected surges or drops in data.
Data Distribution: Analyze data for null values, outliers, and anomalies to ensure accuracy.
Data Schema: Track schema changes over time to prevent breaking changes.
The dashboard's aim is to support historical tracking to support proactive data management and enhance data trust across the data function.
Goals
Although the final goal is to create a power bi dashboard that we are able to monitor, our goals is to 1. Create the necessary tables that track the relevant metadata about our current data 2. Automate the process so it runs in a timely manner
Resources
AWS Redshift; AWS Glue, Airflow, Python, SQL
Why Hedgehogs?
Because we like them.
Fix RSpec tests in order to replace the ruby-ldap rubygem in OBS by enavarro_suse
Description
"LDAP mode is not official supported by OBS!". See: config/options.yml.example#L100-L102
However, there is an RSpec file which tests LDAP mode in OBS. These tests use the ruby-ldap
rubygem, mocking the results returned by a LDAP server.
The ruby-ldap
rubygem seems no longer maintaned, and also prevents from updating to a more recent Ruby version. A good alternative is to replace it with the net-ldap
rubygem.
Before replacing the ruby-ldap
rubygem, we should modify the tests so the don't mock the responses of a LDAP server. Instead, we should modify the tests and run them against a real LDAP server.
Goals
Goals of this project:
- Modify the RSpec tests and run them against a real LDAP server
- Replace the
net-ldap
rubygem with theruby-ldap
rubygem
Achieving the above mentioned goals will:
- Permit upgrading OBS from Ruby 3.1 to Ruby 3.2
- Make a step towards officially supporting LDAP in OBS.
Resources
Recipes catalog and calculator in Rails 8 by gfilippetti
My wife needs a website to catalog and sell the products of her upcoming bakery, and I need to learn and practice modern Rails. So I'm using this Hack Week to build a modern store using the latest Ruby on Rails best practices, ideally up to the deployment.
TO DO
- Index page
- Product page
- Admin area -- Supplies calculator based on orders -- Orders notification
- Authentication
- Payment
- Deployment
Day 1
As my Rails knowledge was pretty outdated and I had 0 experience with Turbo (wich I want to use in the app), I started following a turbo-rails course. I completed 5 of 11 chapters.
Day 2
Continued the course until chapter 8 and added live updates & an empty state to the app. I should finish the course on day 3 and start my own project with the knowledge from it.
Hackweek 24
For this Hackweek I'll continue this project, focusing on a Catalog/Calculator for my wife's recipes so she can use for her Café.
Day 1
Fix RSpec tests in order to replace the ruby-ldap rubygem in OBS by enavarro_suse
Description
"LDAP mode is not official supported by OBS!". See: config/options.yml.example#L100-L102
However, there is an RSpec file which tests LDAP mode in OBS. These tests use the ruby-ldap
rubygem, mocking the results returned by a LDAP server.
The ruby-ldap
rubygem seems no longer maintaned, and also prevents from updating to a more recent Ruby version. A good alternative is to replace it with the net-ldap
rubygem.
Before replacing the ruby-ldap
rubygem, we should modify the tests so the don't mock the responses of a LDAP server. Instead, we should modify the tests and run them against a real LDAP server.
Goals
Goals of this project:
- Modify the RSpec tests and run them against a real LDAP server
- Replace the
net-ldap
rubygem with theruby-ldap
rubygem
Achieving the above mentioned goals will:
- Permit upgrading OBS from Ruby 3.1 to Ruby 3.2
- Make a step towards officially supporting LDAP in OBS.
Resources