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My awesome macropad! by @vybz | Stardance
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Title: My awesome macropad! by @vybz | Stardance
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My own site! by @vyash6671 | Stardance
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Title: My own site! by @vyash6671 | Stardance
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My very own WebOS by @vyankteshgour | Stardance
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Title: My very own WebOS by @vyankteshgour | Stard Title: My very own WebOS by @vyankteshgour | Stardance...
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Frictionless by @vyahriti | Stardance
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Title: Frictionless by @vyahriti | Stardance
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My awesome macropad! by @vyaas | Stardance
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Title: My awesome macropad! by @vyaas | Stardance
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QuantA by @vxyzln | Stardance
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[{"post_id": 51159, "ts": "202 [{"post_id": 51159, "ts": "2026-08-20T17:36:20Z", "hours": 1.6964, "text": "Quanta V0.1 - Data Loader Foundation. The version 0.1 today, I began implementing the market data layer and created the initial CSV data loader. Loader currently reads OHLCV data using pandas and perform basic validation for required columns, dates, formatting, duplicate dates, and chronological ordering. I also introduced pathlib.path Pandlas data frames, type hints, boolean relation, date time conversion, duplicate detection, sorting, and index handling. This is my first time building a project, a larger software project from scratch. So, the focus today was my understanding the architecture, implementing the PCs other than relying on the generated code. Next, improve the validation layer handle invalid inputs with proper exception. Standardize the return data frame and begin testing the loader with valid and intentionally invalid data sets"}]...
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Title: QuantA by @vxyzln | Stardance
Devlogs:
Qua Title: QuantA by @vxyzln | Stardance
Devlogs:
Quanta V0.1 - Data Loader Foundation. The version 0.1 today, I began implementing the market data layer and created the initial CSV data loader. Loader currently reads OHLCV data using pandas and perform basic validation for required columns, dates, formatting, duplicate dates, and chronological ordering. I also introduced pathlib.path Pandlas data frames, type hints, boolean relation, date time conversion, duplicate detection, sorting, and index handling. This is my first time building a project, a larger software project from scratch. So, the focus today was my understanding the architecture, implementing the PCs other than relying on the generated code. Next, improve the validation layer handle invalid inputs with proper exception. Standardize the return data frame and begin testing the loader with valid and intentionally invalid data sets...
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1793361186.6022284
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1793965986.6022284
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52744
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Context Forge by @vxyzln | Stardance
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vxyzln
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62.7
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[{"post_id": 81772, "ts": "202 [{"post_id": 81772, "ts": "2026-10-22T13:15:41Z", "hours": 4.16, "text": "Devlog#33 - Greeting Everyone ! Tl;DR - i spent quite a few hours working on makinf cf understand the repo better , finding th right info and letting the user to inspect a codebase before making changes. like searching for func what it depend on etc. Work : One thing i’ve been thinking abt is that when working on ap project that we can we see what things happend in the repo and where things are and what would i need to look for when changin something etc. . A So lot of work went into connecting some pieces and making sure cf gives reliable info and instead of the sqlite database dat Things done : cf can now check the rpeo and its analysis readiness. this helps bcz it can identify configuration problems instead of discovering them after halfway through. Improved the way cf finds specific symbols in a codebase of a project. the idea was to make it easier to locate and see where a func or a class or other element lies. without having to search everything manually. worked on retrieving relevant source excerpts and checking whether the info is still reliable in the current state of the repo/codebase as there is no use of having old data . added the git navigation capabilities so cf can work with arep changes and git’s context withut modifying the repo code. A MAJOR THING - cf can now bring imp repo info , evidence, other relevant things to help user see the codebase state before making a mistake or making changes to the code. Alongside these made some minor improvements lke more consistent error handling and auditing things etc. and also checking these minor things didnt broke any other things. these kinda things look boing but are nessecary/needed. i dont want cf to be one of the project where u give features without making the existng ones better. i want it to be better and useful for users when working on a large codebase etcetc. Honestly , i’ve had shipped this way earlier if i wasnt slacking off and exams didnt came i my way but we are now in the Last 10 days of Sd. i have a quite things in mind which i need to complete this before shippins so focus on that or some days and the i will ship it. ALso the time on this devlog is small bcz i had accidentally deleted the hackatime config(or file whatevery u want to say) and i didn’t noticed it for quite a few time and then today i relaized when i open my hackatime dashboard. So this is the last time that was logged. I will setup before writing a next devlog . So open to ur thoughts on the cf project and comment ur thoughts. ALso plz leave a like if u like m project !!!!!!!!!!!!"}, {"post_id": 81248, "ts": "2026-10-20T13:51:17Z", "hours": 8.2864, "text": "Devlog#32 - Greeting Everyone ! TL;DR - I spent quite some time making Context Forge more reliable under the hood. The focus was on improving repository analysis, CLI usability, and ensuring that the memory system stays consistent with the actual codebase. Work - I wanted to make cf more than js a tool that scans repo once and stores some info. i wanted to make it useful in real dev workflow or like for someone like me who is making many projects and can sometimes lose trace of what will happned to the codebase. HEre’s what i worked on for these 8h spread across some days. Improved repository analysis and persistence so that the stored knowledge remains consistent and can be reused across different runs. Strengthened incremental analysis to handle added, modified, and deleted files more reliably, reducing the chances of outdated information sticking around. Worked on retrieval and relationship handling to make results more predictable and easier to trace back to the actual source code. Improved the CLI experience, making it easier to inspect repository information and understand what Context Forge currently knows. Refined error handling and diagnostics so that failures are easier to investigate instead of leaving me guessing about what went wrong. Expanded the test coverage across the core systems to catch regressions and make sure that improvements in one area don’t quietly break another. One of the trickkier parts was that the stored repo info actually reflected the current codebase. it’s easy to get things on fresh analysis but things get more complicated when files change , disapper or contain info that cannot bre resolved cleanly. I had to spend time thinking abt edge cases to. a lot work was for strengthing the base the foundation , some improvements i made aren’t visibe ut matter when u want cf to behave properly across multiple projects. Yeah so there is more to build and it was a solid step for cf i would say so. Also SD getting ending in 10 days and i have a lot in mind and i need to ship quick so there would be a lots of commits and hrs or the upcoming 2-3 days as i will grind as much as the time i would get . So leave ur thoughts in the comments if u have any and plz like the project (image context : i ran the cf . command on the cf repo itself and this was its answer)"}, {"post_id": 80616, "ts": "2026-10-18T09:57:53Z", "hours": 4.5992, "text": "Devlog#31 - Greeting Everyone ! TL;DR - I spent time strengthening Context Forge’s core memory and retrieval systems, making repository knowledge more reliable and useful. I also improved how the project handles changes, retrieves relevant information, and exposes its capabilities through the CLI. Work - I wanted to move beyond simple analyzing repo and make cf better at remembering, understanding and retrieving repo knowledge. Here what i did : Strengthened how repository information is stored so files, symbols, and relationships remain available even after restarting the application. Improved how Context Forge handles added, modified, and deleted files, keeping stored knowledge aligned with the actual repository and preventing outdated information from lingering. Strengthened the way relevant files, symbols, and relationships are found and ranked, making results more predictable and consistent. Improved the ability to trace retrieved information back to repository evidence and understand why particular results were selected. Added the cf command as a shorter alternative to context-forge , while preserving the existing command and its behavior. Expanded the CLI with commands for inspecting repository status, memory, files, symbols, references, and relationships, making it easier to explore what Context Forge knows. Improved operational error handling, logging, and diagnostics, making failures easier to understand and helping keep the overall experience more predictable. So yeah did so many things It’s been a while since the Great Pivot / I took some time work through these as i also had to check whether there is some code of the things iripped off in the great pivot. the time went here on working through these features properly, strength the exisiting foundationand make cf more relaible and now moving onto the next things. So leave ur thoughts in the comments and plz leave a like"}, {"post_id": 79279, "ts": "2026-10-13T09:41:19Z", "hours": 2.2675, "text": "Devlog#30 - Greeting Everyone ! - THE GREAT PIVOT Work - Context forge is now moving away from being a generation based tool and becoming a deterministic agent memory foundation. now the rtransition is done cleanly and now i am working ahead on the current foundation but new features. work done - completed the changed direction of context forge from the old provider and generation system to a repo intellegence system removed the ollama integration, provider stack. runtime configuration and the dependencies that came with them. the core should now work without depending on LLM or external APIs refactoredthe application services, task understanding, context slelction, ranking and CLI to fit the new direction. kept the important foundation like SQLite storage , AST based analysis, repo fingerprints, inremental file change detection and evidence based context rtrieval added architecture tests for offline operation , deterministic ranking, file change detection and making sure the context output has proper evidence cleaned up all the old tests which were not needed and deleted the whole files which weren’t needed in the future . Today was mostly about get ting the big transition properly finished. So for the past days, I had some exams and was not happy with the behavior of Olama, of its undeterministic behavior. So I took this step. I did not change the base foundation. I just changed the overlying architecture, the Olama ones, and removed everything that was made that was not needed. So the commit of today is very large, like 7,000 lines removed, and 1000 lines written. I made one big commit for the entire transition instead of splitting this architectural layer into multiple commits. Transform context force into a deterministic agent memory foundation. I also cleaned up the extra local branches and checked that main was synced with GitHub. Now I’m moving towards a memory vault kind of thing. I have to build on what already exists instead of rewriting everything again, improve the memory idea of foundations, add the shorter commands. Yes, so yeah, this was a pretty big change for our project. There was still a lot to do, but at least reaction is much cleaner now. Hope you like the project and please leave your thoughts or feedback in the comments. To be completely transparent, I used AI assistance to help me safely untangle and delete parts of the old architecture that were tightly coupled. As a student developer handling a complex refactor alone, trying to manually map out every single breaking change across thousands of lines got overwhelming, and I needed the help to get it done cleanly. No regrets it got the job back on track, and the codebase is in a much healthier place. With the cleanup done and main fully synced, I’m now shifting focus toward building out the new deterministic memory vault and refining the short-form CLI commands for AI agents. Show writer shipwrights. Please don’t wreck my project. Hope you like the new direction! Let me know your thoughts or feedback in the comments below."}, {"post_id": 72726, "ts": "2026-09-23T16:27:26Z", "hours": 0.3028, "text": "Devlog#29 - Greeting Everyone ! STARDANCE IS GETTING EXTENDED YAYYY!!!!! No TL;DR today for short work Things did today in short time added clean generation outuput handling added cli error handling and seperated output from errors connected generation to the persisted project added test for the same also spent some time on editing some test generated bcz they werent like tha lvl Sp today short work due to other school work coming in. Leave ur thoguhts in the comments and pl like it if u think it is good and should get real appreciation."}, {"post_id": 72306, "ts": "2026-09-22T17:00:47Z", "hours": 1.1167, "text": "Devlog#28 - Greetings Everyone ! TL;DR - Added proper ollama checking and validation plus a runtime cli. Generation now safely uses fresh persisted repo intelligence instead of re-analyzing the project everytime Long - Problems : so when doing today’s work the problems that i wanted to fix was that the generation workflow was still too dependent on live repo analysis instead of using the persisted intelligence. 2nd there was no way to verify ollama itself is available or not. like ollama runtime and is a model available or not. runtime failures needed to stop generation cleanly and not throw a bunch of error a user neds to debug. we needed to preserve provider behaviour and avoid breaking the previous architecture i built the generation one. also the generation path needed clear boundaries between runtime validation, provider execution and final output and etc etc. It sound much but the implementation was simple as ig for me. things done today to solve the problems - added ollama runtime inspection to check local runtime and requested model are available added dedicated runtime cli commd for checking the state of the runtime and model independently changed the generation to load persistd repo intellegence insteasd of it everytime doing a fresh analysis as it would be bad for it to make new things for everytime a cli is ran added cache freshness validation so generation refues stale repo intellegence added regression covergae proving that a generation uses the persistent project and doesnt starts the analyzer again made a foundation kinda thing for a clean generationresponse to cli output boundary with remainng output workflow continuing afterwards added test for the features added Also some of the current changes may not be sen on the github repo bcz i havent comitted some changes as they are a part of a feature and i commit like a feature and the tests related to it for better commits ig . Now what we did to solve the problems and how i felt when solving them - . the generation pipeline is now ready to build the dev facing output worflow or like a user workflow on top of these things the previous architecture i made. i found addng the flags to main.py file easy but then adding the cache checking and the regression covergae and the generationresponse to cli output boundary a bit challenging . So today only this much. Hope u like my project and plz comment for feedback. also a mention to @CT5 on slack for telling me to added problem and solution section in my devlog for better project experii\\ence."}, {"post_id": 71819, "ts": "2026-09-21T16:41:30Z", "hours": 2.8994, "text": "Devlog#27 - Greetings Everyone ! TL;DR - Context Forge can now remember the repo state update it s understanding when things change and provides a proper cli for those who use it. It has ig aroung 6 funcs which u can read below. The work also made the internal state much easier to inspect and debug while keeping the existing thing intact. Long - SO this Devlog is after a long time ig. I was giving 5-10 mins t the project to not lose my habit and the streak also. But today my exams got over so now i can focus on the project. STARDANCE is ending soon so i need to hurry up and complete this asap. So basically did a lot of main writing for cli functionality. cf* - context forge (too lazy to write it out everytime) things did in those past days - made repo analysis persistent instead of starting from scratch everytime the cf* is ran. added file fingerprintng and change detection for smart analysis for a smart project. imporoved how changed files affect relationships and project info. added a proper dev workflow through the CLI as it is a main part and added commands like analysis and generation commands added task input , config handling, clenaer error behaviour for the better contxt of it added command to inspect repo state cache state project info and diagnostics or i should say Pre-Rendered Excuses Generation fixed issues around cache freshness and changed fiel reporting added tests for the new functionality and made sure the existing workflow stayed intact for cf* refactored the fingerprinting logic so it culd be shared cleany by the analyzer and the Cli i made for cf* So this much for the past these days. Now the thing is slowly coming like a real version. Its complexity is very high ,atleast for me . Bcz i made many py projects and this is the most challenging one so far but it shift me into the flow state after sometime so yeah it is a good challenge. It was like based on my problem i faced when i was vibecoding in the early days js to do timepass . But now when u can make it , it feels incredibale. SO yeah it is good. Yes but Currently i see models like astra and fable come out with much more context lenght and etc. so my product is not needed for them for but is a good fun project on thr side. These new models are good but havent tried them but will try them fter i get some freetime after Stardance. as stardance is my first and last ysws soi it was a great experience. Also i did many of the things in neovim like editing some files and etc but i couldnt settedup hackatime with it so like around 1-1.5 h of extra work was untracked on hackatime but it was ok. I was seeing the primeagen video of neovim and wanted to try it out so i did and learned some basics and therre is a very stepp learning curve in it . ALso tried out lazyvim but not my style . So wil pause the vim learing for a few days and finish the prject cf asap. Sorry for this Yapp Session but dumped everything i had for these past few days. SO plz leave ur review in the comment and plz like it and rate it good."}, {"post_id": 67921, "ts": "2026-09-14T07:08:45Z", "hours": 0.4872, "text": "Devlog#26 - Greeting Everyone ! No TL;DR as short work work today - Added deterministic evaluation baseline storage and serialization. Added validation, aggregation, coverage, and persistence support. Added comprehensive tests and maintained a clean, validated implementation. So, this much today only leave your thoughts in the comments/"}, {"post_id": 67491, "ts": "2026-09-13T16:35:20Z", "hours": 0.2508, "text": "Devlog#25 - Greeting Everyone ! No TL;DR as small work today. things accomplished today - Added evaluation aggregation and baseline regression tracking Added validation for duplicate cases and regression tolerance, with tests for the same. Committed implementation and tests as focused changes. Leave ur thoughts in the comments."}, {"post_id": 66802, "ts": "2026-09-12T18:07:31Z", "hours": 0.7114, "text": "Devlog#24 - Greeting Everyone ! TL;DR - Added evaluation for both context selection and final context quality, covering correctness, budget limits, and deterministic behavior. Added focused tests to validate the complete evaluation flow. Long - So exams are going on so can’t do long hour session. Was planning to add manythings over few days but it would stretch for about more days. Things did - Added context-selection evaluation against expected entities using precision recall f1 added end to end evaluation for final context accuracy budget compliance etc. adde d validation for unkown , mising extra and empty entities or context cases. addded tests for the same Js this much today. Leave ur thoughts in the comments ."}, {"post_id": 65802, "ts": "2026-09-11T05:54:26Z", "hours": 0.415, "text": "Devlog#23 - Greetings EVeryone ! TL;DR - Retrieval and task-grounding quality can now be measured deterministically against repository ground truth, with full regression coverage Long - Short sesssion today. added the tp*.txt in gitignore for me to make temporary text files Added deterministic retrieval and task-grounding evaluation with precision recall F1 metrics Added stable repo entity ground truth and evaluation ccovergae Added test for the same added init .py in every subfolder of test bcz there were name clashes in pytest. So today this much only . Leave ur thoughts in the comment and wish me luck!!"}, {"post_id": 65491, "ts": "2026-09-10T17:44:53Z", "hours": 0.4758, "text": "Devlog#22 - Greeting Everyone ! TL;DR - Built the local repository evaluation foundation.Added structural and graph accuracy measurement for files, symbols, and relationships. Long Story - So added chec for my tool. Also committed a wrong spelling recal instead of recall in a func and and then hchnaged it in the new commit. thiings did - Added local evaluation repositories and tasks. Added structural and graph evaluation Added tests for the same Leave ur thoguths iin the comment and like it"}, {"post_id": 64918, "ts": "2026-09-09T17:09:37Z", "hours": 1.3094, "text": "Devlog#21 - Greeting Everyone! TL;DR - Repository analysis is now persisted, freshness-aware, and capable of selectively invalidating stale data instead of rebuilding everything.Cache invalidation and refresh behavior are deterministic, validated, and comprehensively tested. Long - Today I implemented the cache thing for my project. my ool works by mapping a repo and giving context to the user for user to give to AI agent for a work. SO for storing data i use SQLite but making rep data everytime will take a lot of time. So i introduced caching fo data and will refresh in sometime and can be refreshed manually also. Things did : added cache freshness checks for missing metadata , schema/analyzer version , missing fingerprints and file changes added deterministic file fingerprinting using size, modification timestamp and SHA-256 content hashes added selective invalidation for afected files, symbols, and relationships while preserving unaffected analysis added full cache invalidation for cases where existing analysis can no longer be trusted. Added cache refresh orchestration finally added tests for the same So this much today . Leave ur thoughts in the comments and like it"}, {"post_id": 64108, "ts": "2026-09-08T09:36:54Z", "hours": 1.1172, "text": "Devlog#20 - Greetings Everyone ! TL;DR - COntext Forge can now remember the state of repo aand files and identify what changes while context construction remains deterministic, robust and free of generated reasoning. Long - So Hello everyone and welcom to the 20th devlog. today added some more things which are : added deterministic file fingerprinting using its path size modification time etc. and used SHA-256content hashing Persisted file fingerprints in SQLit alongside repocacheing of metadata added detection for unchanged edited modeified added or deleted files Added storage and cache tests covering fingerprint persistence, replacement, and missing data. added analyzer covergae verifying the fingerprints are generated and rpersisted corrrectly. Kept diagnostics based on structured metadata and repository evidence rather than generated reasoning. This much today. Leave ur thoughts in the comments . BYEE and thnx for reading"}, {"post_id": 63650, "ts": "2026-09-07T15:58:34Z", "hours": 2.2053, "text": "Devlog#19 - Greeting Everyone! TL;DR - Originally built the planned reasoning-heavy approach, then identified it as unnecessary complexity and hard-reset all of that work to the clean retrieval baseline. Replaced it with a minimal, structured LLM selection layer where the model only decides include + confidence, while repository intelligence and deterministic metadata remain authoritative. Long Story - So initially i was continuing my plan to have reasoning for every candidate why it was choosed . like was a reasoning heavy context approach includes LLM reasoning. Was working on implementing it throught a flow. during testing, debugging and checking that it works perfectly but things went the other ways. during the checking, i got to a problem that LLM gives out many token in reasoning and which exceeds the limit or the max_tokens limit that i have. it was bad as i couldnt get reasoning perfectly for the per candidate. the i thought of another approach. i will generate the candidates and then i will give all the reasoning fo all of the candidates at the end of it. but this want also working as i wanted it to. i had committed the wrong changes and then i had to hard reset to a stable previous commit whcih didnt had this. then i realized that i was making the system too complicated and it wasnt needed so i remove dthe reasoning nd hard reset to a previous atable commit. I used AI to fix the broken code for the reasoning part that i built but after multiple attempts . So as i said before, 1 option only i reverted to a old git commit . this took most of my time but then did some chages also now context_forgehandes repo intellengence and LLM which decide only what is actually worth keeping. added a strict context-selection contract. Added the selection service to handle the model interaction and validate its response Selection confidence is carried into the final context as metadata, keeping the output inspectable without depending on generated explanations. Added and updated tests around the contract, selection service, package construction, and engine integration Well so this much only today. This day was hassle ful. I’ve used AI 2 times to fix the tings but 1 time i was successful and 1 time i am not. But keeping it aside. i am close to complete the ‘source code’ but not too close. I am thinking of having a brew tap for mac users and another way for windows and linux. The system isnt perfect but it is running. I will make it better nd make it functionable in real world. SO these chages today were light. Most time spent was on Debuging and checkigerrors an fixing them. If hackatime would calculate time spent debugging or xiing, tiday would be 6h+ devlog. Leave ur thouhts in the coments and plz like it."}, {"post_id": 63012, "ts": "2026-09-06T16:03:37Z", "hours": 0.4644, "text": "Devlog#18 - Greeting Everyone!: TL;DR - Integrated relationship-aware retrieval into context construction with bounded depth, confidence propagation, and retrieval provenance. Long Story - So had a small coding session today bcz i didnt got much time as exam is tommorow. Thing Done today - integrated relationship-aware retrieval into context construction addded bounded relationship expansion with confidence and provenance cnnected context-depth evidence to retrieval- added relationhship/depth to context signals added the tests related to the code changes So this mucn only today. Thnx for reading . Leave ur thoughts in the comments."}, {"post_id": 62338, "ts": "2026-09-05T17:38:45Z", "hours": 1.2731, "text": "Devlog#17 - Greeting everyone! TL;DR - Added deterministic deduplication, strongest-path selection, candidate limits, and cycle protection for relationship-aware retrieval.Expanded retrieval is now bounded, predictable, and keeps its evidence consistent, with 13 tests covering the new behavior. long - So a small codin session and added some new things. added deterministic dedpulication for relationship expanded candidates added strongest path selection using confidence depth and UUID odering preserved original candidate odering. enforced candidate expansion limits and cycle protection kept retrieval evidence aligned with selected candidates. added coverage for all the thing s we did through tests. Well so this much the implmentation was small but the testing of it anc checking it was perfect was hassle full Leave ur thoguths in the comments"}, {"post_id": 61627, "ts": "2026-09-04T16:53:19Z", "hours": 1.0678, "text": "Devlog#16 : Greeting Everyone - TL;DR - Context Forge can now understand what a task is asking for and deterministically connect that task to actual repository entities.It can also expand those entities through the repository relationship graph, providing a grounded repository neighborhood for subsequent retrieval and reasoning. Long Yap - Today was a small session of writing code and added new thing which is rep-aware task understanding and grounding. Grounding connects what the user mentions in a task to the actual files and symbols in the repository.It turns vague task references into concrete, verified repository entities that Context Forge can reason about added structured task interpretation covering intent, concepts, requested actions , constraints and ambiguity added exact repo relative path matching exact/unique symbol resolution while keeping unresolved references explicit added repo grounding to expand grounded entites through the existing relationship graph extended candidate generation so directly grounded and relationship connected entities can participate in context retrieval js this much today. Also had a single commit today but was a long one bcz i was in flow and forgot to commit and it was mostly tests . So sorry dev community 😭. (image attached is js a look at the code) Leave r thoughts in comments. open to feedback."}, {"post_id": 61300, "ts": "2026-09-04T04:26:37Z", "hours": 1.9978, "text": "Devlog#15: Greeting Everyone : TL;DR - Built reliable repository structure and a deterministic relationship graph, including symbols, imports, references, inheritance, ownership, relationship resolution, confidence, traversal, and persistence. Added comprehensive tests and validated against a real repository. Long Yap - So the baisc archtecture is completed and now i am working on its hardening and testing it on some real basic repos. Things done today - strengthened repository structural intelligence with more user-reliable Python parsing, symbol extraction, import references, inheritance references, and structural validation, etc. establihed the repo relation graph with numerous relationships. added deterministic relationship resolution with confience scoring and handling of unresolved references. Integrated relationship construction into the analysis pipeline expanded parser,graph,query & pipeline tests verified it basic working on real repo. close to completring a working version but not too close. leave ur thought in th comments . Have a good day or Night"}, {"post_id": 60372, "ts": "2026-09-02T17:45:49Z", "hours": 1.3311, "text": "Devlog#14 : Greeting Everyone TL;DR - Built a complete repository-to-context-to-AI workflow with real Python source context and robust CLI/error handling.The architecture is now stable at this boundary, ready for smarter retrieval, ranking, graph expansion, and project memory. Long Story - So worked some more on the CLI workflow of the tool. SO things did today : Completed the repo to context to provider to response workflow for py projects. Added real source content to select context units added CLI coverage hardend CLI handling for path , config, task, analysis, and generation failures added the keyboardinterreupt i.e. ctrl+c/EOF handling, clean exit codes and safe operational logging. expanded failure-path test coverage So this is the final thing is that the peices were coming together. A locally executable Python workflow from repository analysis through context generation and AI response, with a reliable CLI boundary. So leave ur thoughts in the comments and plz like it."}, {"post_id": 59711, "ts": "2026-09-01T17:11:48Z", "hours": 0.9758, "text": "Devlog#13 - Working on the CLI TL;DR - Integrated generation lifecycle handling with robust success/failure paths and duration tracking.Added rotating operational logging with privacy-safe metadata only—no prompts, responses, or reasoning.Hardened CLI/application tests and logging isolation. Yap - So Majorly worked on the tool so that it could work in the terminal with the command : context-forge [-h][–provider] etc. eg: ~/project/EV > context-forge . the above is the command that wil scan repo the command was ran in and asks for the task. another eg: ~/project/EV > context-forge -h this will give help menu of the cli tool. Also the responses are the Answers are given by the local LLM from ollama which is Qwen2.5-coder:7b which is quantized to Q4_K_M i.e. quantized to 4bit. it takes about 5GB Memory when running. I have to make it s that it runs perfectly as it doesnt answers some times etc. there are many problems to figure out will figure everything out Other things: Hardened provider/application error handling and ensured failures terminate cleanly without leaking task content. integrated generation lifecycle handling into the app flow which inclludes start/stop/completion/failure paths and duration tracking Added operational logging infra with a rotating app log at the global config drectoy Added privacy-focused logging tests ensuring prompts/tasks, generated responses, and model reasoning/thinking are never logged. Consolidated and finalized the logging method and generation lifecycle work; resolved logger path isloation. formatting,linting and test issues. js this much today nothing much more. Leave ur Views and thoguhts on this in the comments."}, {"post_id": 59047, "ts": "2026-08-31T17:11:19Z", "hours": 1.8733, "text": "Devlog#12 - StageX going Good. Greeting everyone. So i am working on the transition from qwen3:8b thinking model to non thining model. TL;DR - We redesigned the generation layer around Qwen2.5-Coder 7B and removed the old Qwen3 thinking/reasoning assumptions. The provider contract was simplified and the Ollama integration boundary was kept clean and model-agnostic. A layered configuration system was added with project, global, and built-in defaults, plus validation and precedence resolution. The CLI was then integrated with this configuration architecture while keeping the existing repository-intelligence pipeline unchanged. Full story - i inspected the existing architecture and confirmed that the repo intellegence pipeline should remain intact. i moved the active generation direction away from the old qwen3 thinking oriented architecture and established Qwen2.5-coder:7Bas the new default without hardcoding model throughout the database. I cleaned theprovider contractso reasoning thinking is no longer a part of the current core generation model while deliberately leaving future reasoning support for later architectural decisions. I also investigated the Olama integration boundary other than replacing its transportation implementation, keeping the previous Olama provider as the boundary. The largest tradition was that I wanted to add a config support so like someone can have a project project-wise configs for my tool, but it can also have a global config. So, if the project config is not available, the tool would fall back to the global config. So, I was thinking of using it as as like a .contextforge.toml file format. Yes, configuration is a dedicated defaults loading validation, etc. facilities solution, etc. And finally, the CLI was connected to the new configuration architecture. Provider settings are no longer hard-coded as the remaining configuration. This much only for today. Leave ur thoughts in the comments"}, {"post_id": 58277, "ts": "2026-08-30T17:25:39Z", "hours": 4.1383, "text": "Devlog#11 - Things went the Otherways. Greting everyone! TL;DR - for those who dont want to read long story - Spent most of the day debugging and rethinking the Ollama integration, which exposed problems with building around a thinking model. After testing the full workflow, I decided to move to Qwen2.5-Coder 7B and introduce Stage X to realign the architecture before continuing development. Long Story - for those who are interested 🙋: SO i was working towards local LLM integration for my project as mentioned in the previous devlog. Today was a sunday so had a lot of time on me so worked on this. i decided of making ollama the sole provider for AI for v1 of my project as it is easy to work with. I chose initially qwen3:8b model. i was working with it for the ollama integration and model works perfectly and give answers and checkning for bugs errors and debugging and adding more tests etc. today most of the time went into debgging,investigating, rediscovering how the existing architecture actually worked, challenging earlier assumptions, and then rethinking the architecture around what the system really needs. The first major objective was making sure the complete Python-project path worked together rather than only working as isolated components. The question was whether these pieces actually behaved correctly as one pipeline. So assessed the code and assemebled it and strenghted it and then added tests for it. Now working with ollama’s qwen3:8b model but soon ralzied it was a major mistake. i wanted to make the model to communicate with the project. So it worked kind off. Like the model i was using was a model that thinks and has chain of thoughts. But soon it became a problem for me. our first integration attempt exposed a problem. The model was clearly behaving as a thinking model. that mattered bcz Context Forge was now trying to use it as a part of a deterministic workflow. The model’s internal thinking could consume substantial generation time before producing the actual answer.That made the original integration architecture less suitable for the project. So i asked myself some questions and came to a conclusion that i should build v1 around the non thinking models like the one i will be using now on is qwen2.5-coder:7b . and integrate thinking and AI providers in future versions. THE CURRENT MODEL ARCHITECTURE should work with a non thinking model. So i introduced a phase for now called StageX where i would check the code and try to refactor it acc to the new direction we are heading. what will StageX chenage: Model Asumptions Thinking or reasoning done by the model Adding a Config file feature- CLI Behaviour(improved) Better Ollama integration Operational Logging this all we implemented in span of some days as i’ve got exams coming but will work on it. a large part of time not logged onto hackatime was spent towards rethinking the decisions made in the past and plan out the Future. TH biggest progress from this was architectural clarity. LET”S START STAGEX Thank u for reading this brain DUmp of Mine. Stay Tuned for future updates"}, {"post_id": 57500, "ts": "2026-08-29T17:47:41Z", "hours": 2.0633, "text": "Devlog #10 — Working. This phase mainly has been about the architecture more complete and connected end-to-end. TL;DR of the whole DEVLOG : Complted provider foundations, task validation/understanding & progressed by introducing ContextRequest and task Aware election. the new pipeline connects task -> validation -> context -> task aware selection->provider. . leave r reviews Long summary for those who are interested: Completed the provider foundation and established generation boundary. this gave cf* a proper path from context generation to serialized context to provider request togenerated response. Added TaskUnderstanding which is the first layer for understanding what the user is actually asking for. added TaskInterpretation, task understanding and validation and validation states such as clear, ambiguous, and sufficient. added tests to ensure invalid tasks stop the pipeline early Introduced ContextRequest as a cleaner boundary b/w the tsk and context systems. instead of pasing ptoject and task seperately, the context engine now recieves a single request containing the relevanr context. Also added some more tests for hardening Now i am focused on connecting pieces more tightly and doing thr final integration work needed . the architecture is now becoming less of collection of individual sytem and more of a single pipeline."}, {"post_id": 56743, "ts": "2026-08-28T16:56:32Z", "hours": 2.2978, "text": "Devlog#9 - working on LLM integration Greeting everyone Working towards the completion of the integration of local LLM. i will implement ollama as the LLM provider in the v1 a very hefty day as had to resolve many problems that had occur. js did 2 commits which had like most tests updtedetc. js this much today."}, {"post_id": 55613, "ts": "2026-08-27T16:03:03Z", "hours": 2.5283, "text": "Devlog#8 - My Greetings !! working towards the git understanding of the project. Hey hello everyone reading this. today the context_forge was extended with git intellengence. I implemented git repo detection repo root, branch/HEAD dicoovery parent or merge tracking shallow repo handling- Aggregate git activity summaries etc.etc. then integrated this directly into analyzer and project model. Persistence Layer was etended so git intellegence survies SQLite save or load cycles Also made a bunch of tests for each thing so that project stays perfectly working. finally the query layer gained explainability metadata so search results can comunicate why a result matched while keeping the explanation seperate from number ranking core. Also coming clean about a thing that i used antigravity bcz when i was working and very deep, i broke most of the files and couldnt seem to fix it so first time i used it to fix that. i havent committed it changes but i cme clean about it. ok bye so leave your opinions here in the comment section."}, {"post_id": 55095, "ts": "2026-08-26T15:30:14Z", "hours": 2.3058, "text": "Devlog#7 - Greeting everyone. progressively buildiing the core. so today also worked towards completing this phase which is a major step towards the project. it was a progress from finding relevant context to building deterministic contextpackage. added serialization support for enriched context. established the provider boundary and deterministic provider without coupling the core engine to an external source like a LLM or a AI provider. introduced compression abstraction added budget -aware compression as we 3 lvls talked about in previous devlogs(you can refer to thm). introdued explicit context-priority modeling Added ContextPriorityOrdering and may smal changes also. from previous devlog, the changes are that previously it could build repo understanding, retrieval,rankingetc. but now it can do compression, prioritization, ordering and assembly. So leave your thoufghts i the comment. THANK YOU!! (also the image uploaded isnt the full code written its just a snippet and also not the full code of the file so plz dont make it the truth. Visit the GITHUB REPO to see the changes and the files)"}, {"post_id": 54515, "ts": "2026-08-25T15:23:24Z", "hours": 0.4597, "text": "Devlog#6 - working . Working towards the project arcitecture. Quick update: I just did a pass on the project with some minimal changes and additions. I added a graph expander and context expansion, and wired the full pipeline into the default context engine. Please leave your reviews in the comments!"}, {"post_id": 54412, "ts": "2026-08-25T12:43:28Z", "hours": 1.6861, "text": "Devlog#5 - workking .HELLO EVERYONE!!!! so i am working on my project and i have done some new things which are : added contextcandidate added conversion from existing searchresult added relevancesignals added deterministic ranking which combines candiadte score+signals and mac score is 1.0 Main : added context depth options which are minimal recommended and Deep. in this part , i am thinking of integrating local LLM like models ollama provides or a API key of a AI provider like claude or openAI or any other provider user wshes for which will help make good perfect context. the things are coming together and i am seeing my project become a great project. So plz leave a like and ur suggetions. (Note: While I am engineering the core context pipeline by hand, I am utilizing AI to generate my unit tests and boilerplate to accelerate development. i have declared it into the AI section of the Project.)"}, {"post_id": 53754, "ts": "2026-08-24T13:02:58Z", "hours": 1.1856, "text": "Devlog#4 - making context forge actually undertstand a project Hello Everyone !! So today just worked upon making some changes like make the project context forge, scan the repository, classify it, detect languages, et cetera. Yes, handbroken files without killing the analysis, etc. And also we built projectquery So, the analyzed project can be actually explored. now the project is coming together. next plan is add a custom LLM model to make it more better. if you have ideas for a good LLM available for free and locally so plz comment. Thank you for looking at it. Bye."}, {"post_id": 53150, "ts": "2026-08-23T16:07:50Z", "hours": 1.3417, "text": "Devlog#3 HELLO EVERYONE!!! I worked on the project search and retrieval foundation. The model is now useful for task-oriented retrieval and ranks search results. Search operates over the persistent project model created .It establishes the basic architecture: Task -> Retrieval -> Ranking -> Context. So far the project is going well and exactly as planned. I aim to ship it . Wish me luck and please check it out!"}, {"post_id": 52985, "ts": "2026-08-23T11:15:05Z", "hours": 3.5578, "text": "DEVLOG#2 - This time, Context Forge went from a basic skeleton to actually understanding a repository. It can now scan projects, classify files, detect languages/frameworks, extract Python symbols, build relationships, and store everything locally in SQLite. .The biggest takeaway: before making Context Forge “smart,” I need to make sure it has a solid understanding of the project itself."}, {"post_id": 52328, "ts": "2026-08-22T13:12:22Z", "hours": 1.5494, "text": "Devlog#1 : I actually started thinking the architecture for Context Forge and I am officially setting up the project and logging my hours here today. The idea came from a problem I repeatedly faced while coding in a big project that when there are massive amount of files, we tend to break things like which things would be affected potentialy but these changes etc.. Context Forge solves this by building a persistent understanding of software project"}]...
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Title: Context Forge by @vxyzln | Stardance
Devlo Title: Context Forge by @vxyzln | Stardance
Devlogs:
Devlog#1 : I actually started thinking the architecture for Context Forge and I am officially setting up the project and logging my hours here today. The idea came from a problem I repeatedly faced while coding in a big project that when there are massive amount of files, we tend to break things like which things would be affected potentialy but these changes etc.. Context Forge solves this by building a persistent understanding of software project
DEVLOG#2 - This time, Context Forge went from a basic skeleton to actually understanding a repository. It can now scan projects, classify files, detect languages/frameworks, extract Python symbols, build relationships, and store everything locally in SQLite. .The biggest takeaway: before making Context Forge “smart,” I need to make sure it has a solid understanding of the project itself.
Devlog#3 HELLO EVERYONE!!! I worked on the project search and retrieval foundation. The model is now useful for task-oriented retrieval and ranks search results. Search operates over the persistent project model created .It establishes the basic architecture: Task -> Retrieval -> Ranking -> Context. So far the project is going well and exactly as planned. I aim to ship it . Wish me luck and please check it out!
Devlog#4 - making context forge actually undertstand a project Hello Everyone !! So today just worked upon making some changes like make the project context forge, scan the repository, classify it, detect languages, et cetera. Yes, handbroken files without killing the analysis, etc. And also we built projectquery So, the analyzed project can be actually explored. now the project is coming together. next plan is add a custom LLM model to make it more better. if you have ideas for a good LLM available for free and locally so plz comment. Thank you for looking at it. Bye.
Devlog#5 - workking .HELLO EVERYONE!!!! so i am working on my project and i have done some new things which are : added contextcandidate added conversion from existing searchresult added relevancesignals added deterministic ranking which combines candiadte score+signals and mac score is 1.0 Main : added context depth options which are minimal recommended and Deep. in this part , i am thinking of integrating local LLM like models ollama provides or a API key of a AI provider like claude or openAI or any other provider user wshes for which will help make good perfect context. the things are coming together and i am seeing my project become a great project. So plz leave a like and ur suggetions. (Note: While I am engineering the core context pipeline by hand, I am utilizing AI to generate my unit tests and boilerplate to accelerate development. i have declared it into the AI section of the Project.)
Devlog#6 - working . Working towards the project arcitecture. Quick update: I just did a pass on the project with some minimal changes and additions. I added a graph expander and context expansion, and wired the full pipeline into the default context engine. Please leave your reviews in the comments!
Devlog#7 - Greeting everyone. progressively buildiing the core. so today also worked towards completing this phase which is a major step towards the project. it was a progress from finding relevant context to building deterministic contextpackage. added serialization support for enriched context. established the provider boundary and deterministic provider without coupling the core engine to an external source like a LLM or a AI provider. introduced compression abstraction added budget -aware compression as we 3 lvls talked about in previous devlogs(you can refer to thm). introdued explicit context-priority modeling Added ContextPriorityOrdering and may smal changes also. from previous devlog, the changes are that previously it could build repo understanding, retrieval,rankingetc. but now it can do compression, prioritization, ordering and assembly. So leave your thoufghts i the comment. THANK YOU!! (also the image uploaded isnt the full code written its just a snippet and also not the full code of the file so plz dont make it the truth. Visit the GITHUB REPO to see the changes and the files)
Devlog#8 - My Greetings !! working towards the git understanding of the project. Hey hello everyone reading this. today the context_forge was extended with git intellengence. I implemented git repo detection repo root, branch/HEAD dicoovery parent or merge tracking shallow repo handling- Aggregate git activity summaries etc.etc. then integrated this directly into analyzer and project model. Persistence Layer was etended so git intellegence survies SQLite save or load cycles Also made a bunch of tests for each thing so that project stays perfectly working. finally the query layer gained explainability metadata so search results can comunicate why a result matched while keeping the explanation seperate from number ranking core. Also coming clean about a thing that i used antigravity bcz when i was working and very deep, i broke most of the files and couldnt seem to fix it so first time i used it to fix that. i havent committed it changes but i cme clean about it. ok bye so leave your opinions here in the comment section.
Devlog#9 - working on LLM integration Greeting everyone Working towards the completion of the integration of local LLM. i will implement ollama as the LLM provider in the v1 a very hefty day as had to resolve many problems that had occur. js did 2 commits which had like most tests updtedetc. js this much today.
Devlog #10 — Working. This phase mainly has been about the architecture more complete and connected end-to-end. TL;DR of the whole DEVLOG : Complted provider foundations, task validation/understanding & progressed by introducing ContextRequest and task Aware election. the new pipeline connects task -> validation -> context -> task aware selection->provider. . leave r reviews Long summary for those who are interested: Completed the provider foundation and established generation boundary. this gave cf* a proper path from context generation to serialized context to provider request togenerated response. Added TaskUnderstanding which is the first layer for understanding what the user is actually asking for. added TaskInterpretation, task understanding and validation and validation states such as clear, ambiguous, and sufficient. added tests to ensure invalid tasks stop the pipeline early Introduced ContextRequest as a cleaner boundary b/w the tsk and context systems. instead of pasing ptoject and task seperately, the context engine now recieves a single request containing the relevanr context. Also added some more tests for hardening Now i am focused on connecting pieces more tightly and doing thr final integration work needed . the architecture is now becoming less of collection of individual sytem and more of a single pipeline.
Devlog#11 - Things went the Otherways. Greting everyone! TL;DR - for those who dont want to read long story - Spent most of the day debugging and rethinking the Ollama integration, which exposed problems with building around a thinking model. After testing the full workflow, I decided to move to Qwen2.5-Coder 7B and introduce Stage X to realign the architecture before continuing development. Long Story - for those who are interested 🙋: SO i was working towards local LLM integration for my project as mentioned in the previous devlog. Today was a sunday so had a lot of time on me so worked on this. i decided of making ollama the sole provider for AI for v1 of my project as it is easy to work with. I chose initially qwen3:8b model. i was working with it for the ollama integration and model works perfectly and give answers and checkning for bugs errors and debugging and adding more tests etc. today most of the time went into debgging,investigating, rediscovering how the existing architecture actually worked, challenging earlier assumptions, and then rethinking the architecture around what the system really needs. The first major objective was making sure the complete Python-project path worked together rather than only working as isolated components. The question was whether these pieces actually behaved correctly as one pipeline. So assessed the code and assemebled it and strenghted it and then added tests for it. Now working with ollama’s qwen3:8b model but soon ralzied it was a major mistake. i wanted to make the model to communicate with the project. So it worked kind off. Like the model i was using was a model that thinks and has chain of thoughts. But soon it became a problem for me. our first integration attempt exposed a problem. The model was clearly behaving as a thinking model. that mattered bcz Context Forge was now trying to use it as a part of a deterministic workflow. The model’s internal thinking could consume substantial generation time before producing the actual answer.That made the original integration architecture less suitable for the project. So i asked myself some questions and came to a conclusion that i should build v1 around the non thinking models like the one i will be using now on is qwen2.5-coder:7b . and integrate thinking and AI providers in future versions. THE CURRENT MODEL ARCHITECTURE should work with a non thinking model. So i introduced a phase for now called StageX where i would check the code and try to refactor it acc to the new direction we are heading. what will StageX chenage: Model Asumptions Thinking or reasoning done by the model Adding a Config file feature- CLI Behaviour(improved) Better Ollama integration Operational Logging this all we implemented in span of some days as i’ve got exams coming but will work on it. a large part of time not logged onto hackatime was spent towards rethinking the decisions made in the past and plan out the Future. TH biggest progress from this was architectural clarity. LET”S START STAGEX Thank u for reading this brain DUmp of Mine. Stay Tuned for future updates
Devlog#12 - StageX going Good. Greeting everyone. So i am working on the transition from qwen3:8b thinking model to non thining model. TL;DR - We redesigned the generation layer around Qwen2.5-Coder 7B and removed the old Qwen3 thinking/reasoning assumptions. The provider contract was simplified and the Ollama integration boundary was kept clean and model-agnostic. A layered configuration system was added with project, global, and built-in defaults, plus validation and precedence resolution. The CLI was then integrated with this configuration architecture while keeping the existing repository-intelligence pipeline unchanged. Full story - i inspected the existing architecture and confirmed that the repo intellegence pipeline should remain intact. i moved the active generation direction away from the old qwen3 thinking oriented architecture and established Qwen2.5-coder:7Bas the new default without hardcoding model throughout the database. I cleaned theprovider contractso reasoning thinking is no longer a part of the current core generation model while deliberately leaving future reasoning support for later architectural decisions. I also investigated the Olama integration boundary other than replacing its transportation implementation, keeping the previous Olama provider as the boundary. The largest tradition was that I wanted to add a config support so like someone can have a project project-wise configs for my tool, but it can also have a global config. So, if the project config is not available, the tool would fall back to the global config. So, I was thinking of using it as as like a .contextforge.toml file format. Yes, configuration is a dedicated defaults loading validation, etc. facilities solution, etc. And finally, the CLI was connected to the new configuration architecture. Provider settings are no longer hard-coded as the remaining configuration. This much only for today. Leave ur thoughts in the comments
Devlog#13 - Working on the CLI TL;DR - Integrated generation lifecycle handling with robust success/failure paths and duration tracking.Added rotating operational logging with privacy-safe metadata only—no prompts, responses, or reasoning.Hardened CLI/application tests and logging isolation. Yap - So Majorly worked on the tool so that it could work in the terminal with the command : context-forge [-h][–provider] etc. eg: ~/project/EV > context-forge . the above is the command that wil scan repo the command was ran in and asks for the task. another eg: ~/project/EV > context-forge -h this will give help menu of the cli tool. Also the responses are the Answers are given by the local LLM from ollama which is Qwen2.5-coder:7b which is quantized to Q4_K_M i.e. quantized to 4bit. it takes about 5GB Memory when running. I have to make it s that it runs perfectly as it doesnt answers some times etc. there are many problems to figure out will figure everything out Other things: Hardened provider/application error handling and ensured failures terminate cleanly without leaking task content. integrated generation lifecycle handling into the app flow which inclludes start/stop/completion/failure paths and duration tracking Added operational logging infra with a rotating app log at the global config drectoy Added privacy-focused logging tests ensuring prompts/tasks, generated responses, and model reasoning/thinking are never logged. Consolidated and finalized the logging method and generation lifecycle work; resolved logger path isloation. formatting,linting and test issues. js this much today nothing much more. Leave ur Views and thoguhts on this in the comments.
Devlog#14 : Greeting Everyone TL;DR - Built a complete repository-to-context-to-AI workflow with real Python source context and robust CLI/error handling.The architecture is now stable at this boundary, ready for smarter retrieval, ranking, graph expansion, and project memory. Long Story - So worked some more on the CLI workflow of the tool. SO things did today : Completed the repo to context to provider to response workflow for py projects. Added real source content to select context units added CLI coverage hardend CLI handling for path , config, task, analysis, and generation failures added the keyboardinterreupt i.e. ctrl+c/EOF handling, clean exit codes and safe operational logging. expanded failure-path test coverage So this is the final thing is that the peices were coming together. A locally executable Python workflow from repository analysis through context generation and AI response, with a reliable CLI boundary. So leave ur thoughts in the comments and plz like it.
Devlog#15: Greeting Everyone : TL;DR - Built reliable repository structure and a deterministic relationship graph, including symbols, imports, references, inheritance, ownership, relationship resolution, confidence, traversal, and persistence. Added comprehensive tests and validated against a real repository. Long Yap - So the baisc archtecture is completed and now i am working on its hardening and testing it on some real basic repos. Things done today - strengthened repository structural intelligence with more user-reliable Python parsing, symbol extraction, import references, inheritance references, and structural validation, etc. establihed the repo relation graph with numerous relationships. added deterministic relationship resolution with confience scoring and handling of unresolved references. Integrated relationship construction into the analysis pipeline expanded parser,graph,query & pipeline tests verified it basic working on real repo. close to completring a working version but not too close. leave ur thought in th comments . Have a good day or Night
Devlog#16 : Greeting Everyone - TL;DR - Context Forge can now understand what a task is asking for and deterministically connect that task to actual repository entities.It can also expand those entities through the repository relationship graph, providing a grounded repository neighborhood for subsequent retrieval and reasoning. Long Yap - Today was a small session of writing code and added new thing which is rep-aware task understanding and grounding. Grounding connects what the user mentions in a task to the actual files and symbols in the repository.It turns vague task references into concrete, verified repository entities that Context Forge can reason about added structured task interpretation covering intent, concepts, requested actions , constraints and ambiguity added exact repo relative path matching exact/unique symbol resolution while keeping unresolved references explicit added repo grounding to expand grounded entites through the existing relationship graph extended candidate generation so directly grounded and relationship connected entities can participate in context retrieval js this much today. Also had a single commit today but was a long one bcz i was in flow and forgot to commit and it was mostly tests . So sorry dev community 😭. (image attached is js a look at the code) Leave r thoughts in comments. open to feedback.
Devlog#17 - Greeting everyone! TL;DR - Added deterministic deduplication, strongest-path selection, candidate limits, and cycle protection for relationship-aware retrieval.Expanded retrieval is now bounded, predictable, and keeps its evidence consistent, with 13 tests covering the new behavior. long - So a small codin session and added some new things. added deterministic dedpulication for relationship expanded candidates added strongest path selection using confidence depth and UUID odering preserved original candidate odering. enforced candidate expansion limits and cycle protection kept retrieval evidence aligned with selected candidates. added coverage for all the thing s we did through tests. Well so this much the implmentation was small but the testing of it anc checking it was perfect was hassle full Leave ur thoguths in the comments
Devlog#18 - Greeting Everyone!: TL;DR - Integrated relationship-aware retrieval into context construction with bounded depth, confidence propagation, and retrieval provenance. Long Story - So had a small coding session today bcz i didnt got much time as exam is tommorow. Thing Done today - integrated relationship-aware retrieval into context construction addded bounded relationship expansion with confidence and provenance cnnected context-depth evidence to retrieval- added relationhship/depth to context signals added the tests related to the code changes So this mucn only today. Thnx for reading . Leave ur thoughts in the comments.
Devlog#19 - Greeting Everyone! TL;DR - Originally built the planned reasoning-heavy approach, then identified it as unnecessary complexity and hard-reset all of that work to the clean retrieval baseline. Replaced it with a minimal, structured LLM selection layer where the model only decides include + confidence, while repository intelligence and deterministic metadata remain authoritative. Long Story - So initially i was continuing my plan to have reasoning for every candidate why it was choosed . like was a reasoning heavy context approach includes LLM reasoning. Was working on implementing it throught a flow. during testing, debugging and checking that it works perfectly but things went the other ways. during the checking, i got to a problem that LLM gives out many token in reasoning and which exceeds the limit or the max_tokens limit that i have. it was bad as i couldnt get reasoning perfectly for the per candidate. the i thought of another approach. i will generate the candidates and then i will give all the reasoning fo all of the candidates at the end of it. but this want also working as i wanted it to. i had committed the wrong changes and then i had to hard reset to a stable previous commit whcih didnt had this. then i realized that i was making the system too complicated and it wasnt needed so i remove dthe reasoning nd hard reset to a previous atable commit. I used AI to fix the broken code for the reasoning part that i built but after multiple attempts . So as i said before, 1 option only i reverted to a old git commit . this took most of my time but then did some chages also now context_forgehandes repo intellengence and LLM which decide only what is actually worth keeping. added a strict context-selection contract. Added the selection service to handle the model interaction and validate its response Selection confidence is carried into the final context as metadata, keeping the output inspectable without depending on generated explanations. Added and updated tests around the contract, selection service, package construction, and engine integration Well so this much only today. This day was hassle ful. I’ve used AI 2 times to fix the tings but 1 time i was successful and 1 time i am not. But keeping it aside. i am close to complete the ‘source code’ but not too close. I am thinking of having a brew tap for mac users and another way for windows and linux. The system isnt perfect but it is running. I will make it better nd make it functionable in real world. SO these chages today were light. Most time spent was on Debuging and checkigerrors an fixing them. If hackatime would calculate time spent debugging or xiing, tiday would be 6h+ devlog. Leave ur thouhts in the coments and plz like it.
Devlog#20 - Greetings Everyone ! TL;DR - COntext Forge can now remember the state of repo aand files and identify what changes while context construction remains deterministic, robust and free of generated reasoning. Long - So Hello everyone and welcom to the 20th devlog. today added some more things which are : added deterministic file fingerprinting using its path size modification time etc. and used SHA-256content hashing Persisted file fingerprints in SQLit alongside repocacheing of metadata added detection for unchanged edited modeified added or deleted files Added storage and cache tests covering fingerprint persistence, replacement, and missing data. added analyzer covergae verifying the fingerprints are generated and rpersisted corrrectly. Kept diagnostics based on structured metadata and repository evidence rather than generated reasoning. This much today. Leave ur thoughts in the comments . BYEE and thnx for reading
Devlog#21 - Greeting Everyone! TL;DR - Repository analysis is now persisted, freshness-aware, and capable of selectively invalidating stale data instead of rebuilding everything.Cache invalidation and refresh behavior are deterministic, validated, and comprehensively tested. Long - Today I implemented the cache thing for my project. my ool works by mapping a repo and giving context to the user for user to give to AI agent for a work. SO for storing data i use SQLite but making rep data everytime will take a lot of time. So i introduced caching fo data and will refresh in sometime and can be refreshed manually also. Things did : added cache freshness checks for missing metadata , schema/analyzer version , missing fingerprints and file changes added deterministic file fingerprinting using size, modification timestamp and SHA-256 content hashes added selective invalidation for afected files, symbols, and relationships while preserving unaffected analysis added full cache invalidation for cases where existing analysis can no longer be trusted. Added cache refresh orchestration finally added tests for the same So this much today . Leave ur thoughts in the comments and like it
Devlog#22 - Greeting Everyone ! TL;DR - Built the local repository evaluation foundation.Added structural and graph accuracy measurement for files, symbols, and relationships. Long Story - So added chec for my tool. Also committed a wrong spelling recal instead of recall in a func and and then hchnaged it in the new commit. thiings did - Added local evaluation repositories and tasks. Added structural and graph evaluation Added tests for the same Leave ur thoguths iin the comment and like it
Devlog#23 - Greetings EVeryone ! TL;DR - Retrieval and task-grounding quality can now be measured deterministically against repository ground truth, with full regression coverage Long - Short sesssion today. added the tp*.txt in gitignore for me to make temporary text files Added deterministic retrieval and task-grounding evaluation with precision recall F1 metrics Added stable repo entity ground truth and evaluation ccovergae Added test for the same added init .py in every subfolder of test bcz there were name clashes in pytest. So today this much only . Leave ur thoughts in the comment and wish me luck!!
Devlog#24 - Greeting Everyone ! TL;DR - Added evaluation for both context selection and final context quality, covering correctness, budget limits, and deterministic behavior. Added focused tests to validate the complete evaluation flow. Long - So exams are going on so can’t do long hour session. Was planning to add manythings over few days but it would stretch for about more days. Things did - Added context-selection evaluation against expected entities using precision recall f1 added end to end evaluation for final context accuracy budget compliance etc. adde d validation for unkown , mising extra and empty entities or context cases. addded tests for the same Js this much today. Leave ur thoughts in the comments .
Devlog#25 - Greeting Everyone ! No TL;DR as small work today. things accomplished today - Added evaluation aggregation and baseline regression tracking Added validation for duplicate cases and regression tolerance, with tests for the same. Committed implementation and tests as focused changes. Leave ur thoughts in the comments.
Devlog#26 - Greeting Everyone ! No TL;DR as short work work today - Added deterministic evaluation baseline storage and serialization. Added validation, aggregation, coverage, and persistence support. Added comprehensive tests and maintained a clean, validated implementation. So, this much today only leave your thoughts in the comments/
Devlog#27 - Greetings Everyone ! TL;DR - Context Forge can now remember the repo state update it s understanding when things change and provides a proper cli for those who use it. It has ig aroung 6 funcs which u can read below. The work also made the internal state much easier to inspect and debug while keeping the existing thing intact. Long - SO this Devlog is after a long time ig. I was giving 5-10 mins t the project to not lose my habit and the streak also. But today my exams got over so now i can focus on the project. STARDANCE is ending soon so i need to hurry up and complete this asap. So basically did a lot of main writing for cli functionality. cf* - context forge (too lazy to write it out everytime) things did in those past days - made repo analysis persistent instead of starting from scratch everytime the cf* is ran. added file fingerprintng and change detection for smart analysis for a smart project. imporoved how changed files affect relationships and project info. added a proper dev workflow through the CLI as it is a main part and added commands like analysis and generation commands added task input , config handling, clenaer error behaviour for the better contxt of it added command to inspect repo state cache state project info and diagnostics or i should say Pre-Rendered Excuses Generation fixed issues around cache freshness and changed fiel reporting added tests for the new functionality and made sure the existing workflow stayed intact for cf* refactored the fingerprinting logic so it culd be shared cleany by the analyzer and the Cli i made for cf* So this much for the past these days. Now the thing is slowly coming like a real version. Its complexity is very high ,atleast for me . Bcz i made many py projects and this is the most challenging one so far but it shift me into the flow state after sometime so yeah it is a good challenge. It was like based on my problem i faced when i was vibecoding in the early days js to do timepass . But now when u can make it , it feels incredibale. SO yeah it is good. Yes but Currently i see models like astra and fable come out with much more context lenght and etc. so my product is not needed for them for but is a good fun project on thr side. These new models are good but havent tried them but will try them fter i get some freetime after Stardance. as stardance is my first and last ysws soi it was a great experience. Also i did many of the things in neovim like editing some files and etc but i couldnt settedup hackatime with it so like around 1-1.5 h of extra work was untracked on hackatime but it was ok. I was seeing the primeagen video of neovim and wanted to try it out so i did and learned some basics and therre is a very stepp learning curve in it . ALso tried out lazyvim but not my style . So wil pause the vim learing for a few days and finish the prject cf asap. Sorry for this Yapp Session but dumped everything i had for these past few days. SO plz leave ur review in the comment and plz like it and rate it good.
Devlog#28 - Greetings Everyone ! TL;DR - Added proper ollama checking and validation plus a runtime cli. Generation now safely uses fresh persisted repo intelligence instead of re-analyzing the project everytime Long - Problems : so when doing today’s work the problems that i wanted to fix was that the generation workflow was still too dependent on live repo analysis instead of using the persisted intelligence. 2nd there was no way to verify ollama itself is available or not. like ollama runtime and is a model available or not. runtime failures needed to stop generation cleanly and not throw a bunch of error a user neds to debug. we needed to preserve provider behaviour and avoid breaking the previous architecture i built the generation one. also the generation path needed clear boundaries between runtime validation, provider execution and final output and etc etc. It sound much but the implementation was simple as ig for me. things done today to solve the problems - added ollama runtime inspection to check local runtime and requested model are available added dedicated runtime cli commd for checking the state of the runtime and model independently changed the generation to load persistd repo intellegence insteasd of it everytime doing a fresh analysis as it would be bad for it to make new things for everytime a cli is ran added cache freshness validation so generation refues stale repo intellegence added regression covergae proving that a generation uses the persistent project and doesnt starts the analyzer again made a foundation kinda thing for a clean generationresponse to cli output boundary with remainng output workflow continuing afterwards added test for the features added Also some of the current changes may not be sen on the github repo bcz i havent comitted some changes as they are a part of a feature and i commit like a feature and the tests related to it for better commits ig . Now what we did to solve the problems and how i felt when solving them - . the generation pipeline is now ready to build the dev facing output worflow or like a user workflow on top of these things the previous architecture i made. i found addng the flags to main.py file easy but then adding the cache checking and the regression covergae and the generationresponse to cli output boundary a bit challenging . So today only this much. Hope u like my project and plz comment for feedback. also a mention to @CT5 on slack for telling me to added problem and solution section in my devlog for better project experii\ence.
Devlog#29 - Greeting Everyone ! STARDANCE IS GETTING EXTENDED YAYYY!!!!! No TL;DR today for short work Things did today in short time added clean generation outuput handling added cli error handling and seperated output from errors connected generation to the persisted project added test for the same also spent some time on editing some test generated bcz they werent like tha lvl Sp today short work due to other school work coming in. Leave ur thoguhts in the comments and pl like it if u think it is good and should get real appreciation.
Devlog#30 - Greeting Everyone ! - THE GREAT PIVOT Work - Context forge is now moving away from being a generation based tool and becoming a deterministic agent memory foundation. now the rtransition is done cleanly and now i am working ahead on the current foundation but new features. work done - completed the changed direction of context forge from the old provider and generation system to a repo intellegence system removed the ollama integration, provider stack. runtime configuration and the dependencies that came with them. the core should now work without depending on LLM or external APIs refactoredthe application services, task understanding, context slelction, ranking and CLI to fit the new direction. kept the important foundation like SQLite storage , AST based analysis, repo fingerprints, inremental file change detection and evidence based context rtrieval added architecture tests for offline operation , deterministic ranking, file change detection and making sure the context output has proper evidence cleaned up all the old tests which were not needed and deleted the whole files which weren’t needed in the future . Today was mostly about get ting the big transition properly finished. So for the past days, I had some exams and was not happy with the behavior of Olama, of its undeterministic behavior. So I took this step. I did not change the base foundation. I just changed the overlying architecture, the Olama ones, and removed everything that was made that was not needed. So the commit of today is very large, like 7,000 lines removed, and 1000 lines written. I made one big commit for the entire transition instead of splitting this architectural layer into multiple commits. Transform context force into a deterministic agent memory foundation. I also cleaned up the extra local branches and checked that main was synced with GitHub. Now I’m moving towards a memory vault kind of thing. I have to build on what already exists instead of rewriting everything again, improve the memory idea of foundations, add the shorter commands. Yes, so yeah, this was a pretty big change for our project. There was still a lot to do, but at least reaction is much cleaner now. Hope you like the project and please leave your thoughts or feedback in the comments. To be completely transparent, I used AI assistance to help me safely untangle and delete parts of the old architecture that were tightly coupled. As a student developer handling a complex refactor alone, trying to manually map out every single breaking change across thousands of lines got overwhelming, and I needed the help to get it done cleanly. No regrets it got the job back on track, and the codebase is in a much healthier place. With the cleanup done and main fully synced, I’m now shifting focus toward building out the new deterministic memory vault and refining the short-form CLI commands for AI agents. Show writer shipwrights. Please don’t wreck my project. Hope you like the new direction! Let me know your thoughts or feedback in the comments below.
Devlog#31 - Greeting Everyone ! TL;DR - I spent time strengthening Context Forge’s core memory and retrieval systems, making repository knowledge more reliable and useful. I also improved how the project handles changes, retrieves relevant information, and exposes its capabilities through the CLI. Work - I wanted to move beyond simple analyzing repo and make cf better at remembering, understanding and retrieving repo knowledge. Here what i did : Strengthened how repository information is stored so files, symbols, and relationships remain available even after restarting the application. Improved how Context Forge handles added, modified, and deleted files, keeping stored knowledge aligned with the actual repository and preventing outdated information from lingering. Strengthened the way relevant files, symbols, and relationships are found and ranked, making results more predictable and consistent. Improved the ability to trace retrieved information back to repository evidence and understand why particular results were selected. Added the cf command as a shorter alternative to context-forge , while preserving the existing command and its behavior. Expanded the CLI with commands for inspecting repository status, memory, files, symbols, references, and relationships, making it easier to explore what Context Forge knows. Improved operational error handling, logging, and diagnostics, making failures easier to understand and helping keep the overall experience more predictable. So yeah did so many things It’s been a while since the Great Pivot / I took some time work through these as i also had to check whether there is some code of the things iripped off in the great pivot. the time went here on working through these features properly, strength the exisiting foundationand make cf more relaible and now moving onto the next things. So leave ur thoughts in the comments and plz leave a like
Devlog#32 - Greeting Everyone ! TL;DR - I spent quite some time making Context Forge more reliable under the hood. The focus was on improving repository analysis, CLI usability, and ensuring that the memory system stays consistent with the actual codebase. Work - I wanted to make cf more than js a tool that scans repo once and stores some info. i wanted to make it useful in real dev workflow or like for someone like me who is making many projects and can sometimes lose trace of what will happned to the codebase. HEre’s what i worked on for these 8h spread across some days. Improved repository analysis and persistence so that the stored knowledge remains consistent and can be reused across different runs. Strengthened incremental analysis to handle added, modified, and deleted files more reliably, reducing the chances of outdated information sticking around. Worked on retrieval and relationship handling to make results more predictable and easier to trace back to the actual source code. Improved the CLI experience, making it easier to inspect repository information and understand what Context Forge currently knows. Refined error handling and diagnostics so that failures are easier to investigate instead of leaving me guessing about what went wrong. Expanded the test coverage across the core systems to catch regressions and make sure that improvements in one area don’t quietly break another. One of the trickkier parts was that the stored repo info actually reflected the current codebase. it’s easy to get things on fresh analysis but things get more complicated when files change , disapper or contain info that cannot bre resolved cleanly. I had to spend time thinking abt edge cases to. a lot work was for strengthing the base the foundation , some improvements i made aren’t visibe ut matter when u want cf to behave properly across multiple projects. Yeah so there is more to build and it was a solid step for cf i would say so. Also SD getting ending in 10 days and i have a lot in mind and i need to ship quick so there would be a lots of commits and hrs or the upcoming 2-3 days as i will grind as much as the time i would get . So leave ur thoughts in the comments if u have any and plz like the project (image context : i ran the cf . command on the cf repo itself and this was its answer)
Devlog#33 - Greeting Everyone ! Tl;DR - i spent quite a few hours working on makinf cf understand the repo better , finding th right info and letting the user to inspect a codebase before making changes. like searching for func what it depend on etc. Work : One thing i’ve been thinking abt is that when working on ap project that we can we see what things happend in the repo and where things are and what would i need to look for when changin something etc. . A So lot of work went into connecting some pieces and making sure cf gives reliable info and instead of the sqlite database dat Things done : cf can now check the rpeo and its analysis readiness. this helps bcz it can identify configuration problems instead of discovering them after halfway through. Improved the way cf finds specific symbols in a codebase of a project. the idea was to make it easier to locate and see where a func or a class or other element lies. without having to search everything manually. worked on retrieving relevant source excerpts and checking whether the info is still reliable in the current state of the repo/codebase as there is no use of having old data . added the git navigation capabilities so cf can work with arep changes and git’s context withut modifying the repo code. A MAJOR THING - cf can now bring imp repo info , evidence, other relevant things to help user see the codebase state before making a mistake or making changes to the code. Alongside these made some minor improvements lke more consistent error handling and auditing things etc. and also checking these minor things didnt broke any other things. these kinda things look boing but are nessecary/needed. i dont want cf to be one of the project where u give features without making the existng ones better. i want it to be better and useful for users when working on a large codebase etcetc. Honestly , i’ve had shipped this way earlier if i wasnt slacking off and exams didnt came i my way but we are now in the Last 10 days of Sd. i have a quite things in mind which i need to complete this before shippins so focus on that or some days and the i will ship it. ALso the time on this devlog is small bcz i had accidentally deleted the hackatime config(or file whatevery u want to say) and i didn’t noticed it for quite a few time and then today i relaized when i open my hackatime dashboard. So this is the last time that was logged. I will setup before writing a next devlog . So open to ur thoughts on the cf project and comment ur thoughts. ALso plz leave a like if u like m project !!!!!!!!!!!!...
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My first slack bot! by @vxnny | Stardance
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Title: My first slack bot! by @vxnny | Stardance
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CTBMS - DEMO CRICKET TICKET BOOKING AND MANAGEMENT CTBMS - DEMO CRICKET TICKET BOOKING AND MANAGEMENT SYSTEM by @vxcii911 | Stardance...
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Title: CTBMS - DEMO CRICKET TICKET BOOKING AND MAN Title: CTBMS - DEMO CRICKET TICKET BOOKING AND MANAGEMENT SYSTEM by @vxcii911 | Stardance...
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My awesome macropad! by @vweb | Stardance
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Title: My awesome macropad! by @vweb | Stardance
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My first slack bot! by @vweb | Stardance
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Title: My first slack bot! by @vweb | Stardance
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Untitled by @vweb | Stardance
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Title: Untitled by @vweb | Stardance
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MediaPlayer by @vweb | Stardance
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-16T19:15:30Z", "hours": 19.0, "multiplier": 3.53, "payout": 67, "blessing": "neutral", "text": "I made a music player in Java. Some issues I had were that this is my first time writing an actual GUI application with Java, so I had to ask some help from Claude.", "repo": "https://github.com/goldcoin10/JavaMediaPlayer", "demo": "https://github.com/goldcoin10/JavaMediaPlayer/releases/tag/release"}]...
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[{"post_id": 29683, "ts": "202 [{"post_id": 29683, "ts": "2026-07-16T19:05:02Z", "hours": 0.2781, "text": "just finished README, last last devlog now"}, {"post_id": 29634, "ts": "2026-07-16T18:13:23Z", "hours": 0.8869, "text": "final devlog, project done"}, {"post_id": 29582, "ts": "2026-07-16T16:43:56Z", "hours": 3.0986, "text": "volume slider implemented"}, {"post_id": 29169, "ts": "2026-07-15T21:44:03Z", "hours": 4.6167, "text": "progress bar"}, {"post_id": 28663, "ts": "2026-07-15T01:39:08Z", "hours": 1.2844, "text": "added a back and forward button"}, {"post_id": 28559, "ts": "2026-07-14T21:44:56Z", "hours": 2.3333, "text": "an actual ui ffs"}, {"post_id": 28396, "ts": "2026-07-14T17:06:28Z", "hours": 2.1386, "text": "fixed the error"}, {"post_id": 28092, "ts": "2026-07-14T04:14:46Z", "hours": 0.5286, "text": "play implemented"}, {"post_id": 28085, "ts": "2026-07-14T03:38:23Z", "hours": 0.6503, "text": "javafx time"}, {"post_id": 28057, "ts": "2026-07-14T02:32:40Z", "hours": 3.2875, "text": "finally got a menu working (java is hard)"}]...
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Title: MediaPlayer by @vweb | Stardance
Devlogs:
Title: MediaPlayer by @vweb | Stardance
Devlogs:
finally got a menu working (java is hard)
javafx time
play implemented
fixed the error
an actual ui ffs
added a back and forward button
progress bar
volume slider implemented
final devlog, project done
just finished README, last last devlog now
Ships:
I made a music player in Java. Some issues I had were that this is my first time writing an actual GUI application with Java, so I had to ask some help from Claude....
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vib-bl by @vweb | Stardance
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Title: vib-bl by @vweb | Stardance
Devlogs:
there Title: vib-bl by @vweb | Stardance
Devlogs:
there’s gotta be a cleaner way to make this...
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My awesome macropad! by @vw | Stardance
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Title: My awesome macropad! by @vw | Stardance
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Title: Ion thruster by @vvv | Stardance
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AI Powered Criminal Activity Detection Through Sen AI Powered Criminal Activity Detection Through Sensor-less Sensing by @vvishal0507 | Stardance...
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Title: AI Powered Criminal Activity Detection Thro Title: AI Powered Criminal Activity Detection Through Sensor-less Sensing by @vvishal0507 | Stardance...
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My own site! by @vuyaninhlapo | Stardance
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Title: My own site! by @vuyaninhlapo | Stardance
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My awesome macropad! by @vus | Stardance
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Title: My awesome macropad! by @vus | Stardance
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Untitled project by @vurigekarel | Stardance
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Title: Untitled project by @vurigekarel | Stardanc Title: Untitled project by @vurigekarel | Stardance...
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My very own WebOS by @vuppalahrishikesh16 | Starda My very own WebOS by @vuppalahrishikesh16 | Stardance...
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Title: My very own WebOS by @vuppalahrishikesh16 | Title: My very own WebOS by @vuppalahrishikesh16 | Stardance...
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Amount Checker by @vulcan4378 | Stardance
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[{"post_id": 15236, "ts": "202 [{"post_id": 15236, "ts": "2026-06-24T18:56:57Z", "hours": 0.0, "text": "Started the code space on git hub and started looking on how i wanted to orientate everything no code has been added yet"}]...
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Title: Amount Checker by @vulcan4378 | Stardance
Title: Amount Checker by @vulcan4378 | Stardance
Devlogs:
Started the code space on git hub and started looking on how i wanted to orientate everything no code has been added yet...
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Samsung Dex PC Build by @vulcan4378 | Stardance
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Title: Samsung Dex PC Build by @vulcan4378 | Stard Title: Samsung Dex PC Build by @vulcan4378 | Stardance...
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TinyNAS Jellfin by @vulcan4378 | Stardance
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[]
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[{"post_id": 49223, "ts": "202 [{"post_id": 49223, "ts": "2026-08-17T21:35:49Z", "hours": 0.3833, "text": "I didn’t do much just made it printer ready added one more thing. Over all finding parts and the code to do this has proven difficult and I have spent over 4 hours researching luckily I already fount the SBC I will use that’s how I made the case but over all the code is proving difficult to run a storage drive and Jellyfin on the same storge on a NAS but I think I found a way hopefully the next dev is me saying I know it will work."}, {"post_id": 47598, "ts": "2026-08-15T16:18:15Z", "hours": 0.4836, "text": "Finished the case with decals and some final touches next is to make the plan on what to run on the NAS. Currently I’m thinking file storage and Jellyfin the coolest part with Jellyfin is that I have a laptop running Batocera and I run it on my tv and play so I think I will integrate Jellyfin in to Batocera’s Kodi entertainment center and use the NAS to run Jellyfin and hold the shows and Kodi entertainment center to watch them"}, {"post_id": 47032, "ts": "2026-08-14T17:03:20Z", "hours": 0.65, "text": "I made some changes so it is easier to put together sadly I had to go and cut some things out and remake them to make it modular and easier to put together but it is worth it in the long run. Hopefully this will also make it look better I will add some decals and stuff next."}, {"post_id": 46471, "ts": "2026-08-13T18:23:25Z", "hours": 1.5828, "text": "I started to make the layout for the NAS case it took longer than expected about 1 hour 30 min total to get about 3/4 of it done. I will work to finish the draft then i ill make it look all cool and not like a box."}]...
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Title: TinyNAS Jellfin by @vulcan4378 | Stardance
Title: TinyNAS Jellfin by @vulcan4378 | Stardance
Devlogs:
I started to make the layout for the NAS case it took longer than expected about 1 hour 30 min total to get about 3/4 of it done. I will work to finish the draft then i ill make it look all cool and not like a box.
I made some changes so it is easier to put together sadly I had to go and cut some things out and remake them to make it modular and easier to put together but it is worth it in the long run. Hopefully this will also make it look better I will add some decals and stuff next.
Finished the case with decals and some final touches next is to make the plan on what to run on the NAS. Currently I’m thinking file storage and Jellyfin the coolest part with Jellyfin is that I have a laptop running Batocera and I run it on my tv and play so I think I will integrate Jellyfin in to Batocera’s Kodi entertainment center and use the NAS to run Jellyfin and hold the shows and Kodi entertainment center to watch them
I didn’t do much just made it printer ready added one more thing. Over all finding parts and the code to do this has proven difficult and I have spent over 4 hours researching luckily I already fount the SBC I will use that’s how I made the case but over all the code is proving difficult to run a storage drive and Jellyfin on the same storge on a NAS but I think I found a way hopefully the next dev is me saying I know it will work....
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1792893130.6390042
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1793757130.6390042
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66132
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Chromebook Batocera PC Case by @vulcan4378 | Stard Chromebook Batocera PC Case by @vulcan4378 | Stardance...
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vulcan4378
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0
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1.88
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0
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[]
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[{"post_id": 74192, "ts": "202 [{"post_id": 74192, "ts": "2026-09-26T21:43:15Z", "hours": 0.3339, "text": "Two tiny addons. First addon being the added vents int the back so hot air gets out. Second addon being the shelf For the motherboards sub board this should be close to the finish"}, {"post_id": 74181, "ts": "2026-09-26T21:11:11Z", "hours": 1.5508, "text": "I started making the case and heatsink. I made the heatsink linier so when the fans blow they blow through keeping both the petg plastic and heatsink cool. I also hid the fans so they are not a eye sore and made sure they get air. In the same slot I made a are so that I can add leds so It looks like a steam machine. There will be more handy addons tomorrow. TIMELAPSE LINKS https://lapse.hackclub.com/timelapse/VSEK-76tTF_P https://lapse.hackclub.com/timelapse/fE0kpQJJf6nG"}]...
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Title: Chromebook Batocera PC Case by @vulcan4378 Title: Chromebook Batocera PC Case by @vulcan4378 | Stardance
Devlogs:
I started making the case and heatsink. I made the heatsink linier so when the fans blow they blow through keeping both the petg plastic and heatsink cool. I also hid the fans so they are not a eye sore and made sure they get air. In the same slot I made a are so that I can add leds so It looks like a steam machine. There will be more handy addons tomorrow. TIMELAPSE LINKS https://lapse.hackclub.com/timelapse/VSEK-76tTF_P https://lapse.hackclub.com/timelapse/fE0kpQJJf6nG
Two tiny addons. First addon being the added vents int the back so hot air gets out. Second addon being the shelf For the motherboards sub board this should be close to the finish...
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1793094732.3150153
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1793699532.3150153
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10308
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Metrodisplay by @vuktacic | Stardance
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vuktacic
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0
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7.18
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0
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[]
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[{"post_id": 14463, "ts": "202 [{"post_id": 14463, "ts": "2026-06-23T16:25:27Z", "hours": 7.1828, "text": "An led panel to play tetris! This hackatime time is for all the firmware I wrote for the project. I had to set up the HUB75 display drivers and wrote the logic for a pong game as a proof of concept. I then got to work writing code for the tetris game. It’s currently a work in progress, but right now pieces can fall, be moved left to right, rotate, and have lines cleared. They can also be dropped quickly (hard drop is still wip). I want to eventually add garbage lines so that it can be actual player vs player instead of just two games running at once."}]...
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Title: Metrodisplay by @vuktacic | Stardance
Devl Title: Metrodisplay by @vuktacic | Stardance
Devlogs:
An led panel to play tetris! This hackatime time is for all the firmware I wrote for the project. I had to set up the HUB75 display drivers and wrote the logic for a pong game as a proof of concept. I then got to work writing code for the tetris game. It’s currently a work in progress, but right now pieces can fall, be moved left to right, rotate, and have lines cleared. They can also be dropped quickly (hard drop is still wip). I want to eventually add garbage lines so that it can be actual player vs player instead of just two games running at once....
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1793256531.016682
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1793861331.016682
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21446
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chessler by @vuktacic | Stardance
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vuktacic
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0
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0.0
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0
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[]
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[]
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Title: chessler by @vuktacic | Stardance
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1793174087.2487235
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1793778887.2487235
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58960
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My own site! by @vu1000 | Stardance
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vu1000
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0
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0.0
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0
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[]
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[]
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Title: My own site! by @vu1000 | Stardance
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1792777755.864795
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1793382555.864795
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69467
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My very own WebOS by @vterra | Stardance
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vterra
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0
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0.0
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0
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[]
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[]
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Title: My very own WebOS by @vterra | Stardance
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1792853467.650781
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1793458267.650781
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2787
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Untitled project by @vtellamsetty | Stardance
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vtellamsetty
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0
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0.0
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0
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[]
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Title: Untitled project by @vtellamsetty | Stardan Title: Untitled project by @vtellamsetty | Stardance...
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1792723750.484426
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1793328550.484426
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72097
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vishwa by @vsrupeshoffl | Stardance
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vsrupeshoffl
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0
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0.0
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0
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[]
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[]
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Title: vishwa by @vsrupeshoffl | Stardance
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1793378839.725536
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1793983639.725536
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61900
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Search And Rescue Drone by @vsammeta09 | Stardance
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vsammeta09
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0
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0.0
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Title: Search And Rescue Drone by @vsammeta09 | St Title: Search And Rescue Drone by @vsammeta09 | Stardance...
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1793044049.8377242
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1793648849.8377242
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30910
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Untitled project by @vs | Stardance
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vs
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0
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0.0
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0
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[]
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[]
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Title: Untitled project by @vs | Stardance
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1793184642.0647006
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1793789442.0647006
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30912
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My own site! by @vs | Stardance
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vs
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0
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0.0
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[]
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[]
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Title: My own site! by @vs | Stardance
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1793368571.9276826
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1793973371.9276826
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55409
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My own site! by @vruthvi20 | Stardance
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vruthvi20
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0
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0.0
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0
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[]
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[]
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Title: My own site! by @vruthvi20 | Stardance
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1792918158.1837838
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1793782158.1837838
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58827
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My awesome macropad! by @vruthvi20 | Stardance
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vruthvi20
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @vruthvi20 | Starda Title: My awesome macropad! by @vruthvi20 | Stardance...
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1792770675.8747587
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1793375475.8747587
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9638
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My awesome macropad! by @vrushalpatil | Stardance
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vrushalpatil
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @vrushalpatil | Sta Title: My awesome macropad! by @vrushalpatil | Stardance...
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1792677184.151914
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1793281984.151914
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22295
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My very own WebOS by @vrush | Stardance
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vrush
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0
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0.0
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0
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[]
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[]
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Title: My very own WebOS by @vrush | Stardance
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1793285788.9289079
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1793890588.9289079
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26700
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The Eclipse Lamp by @vrunchil7 | Stardance
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vrunchil7
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0
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22.4
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[]
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[{"post_id": 24399, "ts": "202 [{"post_id": 24399, "ts": "2026-07-07T22:39:36Z", "hours": 1.8203, "text": "Eclipse Lamp Devlog #11 - Finishing the Bottom Lamp Case print and assembling the Servo and Pi to it. Also Finishing the B.O.M. Today was pretty fun since I got to work mostly on the hardware. I started my print at 8 AM (the earliest I’ve woken up this summer) and let the 6-hour print run. I came back at 2:13 to see the final product. Since this was the bottom shell, I needed to print it in a dark color so light wouldn’t shine through. I was itching to use my new red-and-black silk PLA, so I loaded it into my extruder and got started. Next, I was ready to hot glue the servo into the walls I designed, but first I needed to make sure the servo shaft was centered. I grabbed a 150 × 150 mm plate and used a compass and ruler to find the midpoint (shoutout to my geometry teacher). I found that the servo shaft was only 2 mm off-center, which I was totally fine with. After that, I tried fitting the Raspberry Pi into its spot but realized I had made a CAD mistake. When I aligned it with the screw holes, the audio jack stuck out because I hadn’t designed an opening for it. Instead of reprinting the whole part, I grabbed my hot glue gun and burned a hole through the side. It worked perfectly, and the Pi fit right in. I originally wanted to screw the Pi in place, but I didn’t have the right size hardware. I needed 3.5 mm screws and only had 3 mm and 4 mm, so I ended up hot gluing it in instead, and it held perfectly. I also hot glued the camera into its enclosure so it became part of the iris mechanism. After finishing the hardware, I started and finished the BOM and posted it to my GitHub. The next step is printing the top case."}, {"post_id": 23297, "ts": "2026-07-06T05:12:10Z", "hours": 2.3781, "text": "Eclipse Lamp Devlog #10 - Finishing the YOLO and AI Person Detection, starting and finishing the Telegram Push Notification system, and assembling the printed Iris-Camera frame shutter system YOOOOOOOOOOOO!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Today was actually the most productive session ever. First, before I started my recording I finished the iris-camera frame attachment that attaches the camera to the back of the iris mechanism. My main motive for today was getting the Telegram notification setup, but I did so much more. First I decided on using Telegram, downloading the app on my phone and computer for notifications. Then I created a bot through BotFather, got my bot token and chat ID, and went into terminal so the Pi could send messages directly to my Telegram. Within minutes I was getting notifications on both my phone and computer simultaneously — that part was actually easy and satisfying to get done fast. After that I said “third time’s the charm for AI” and it really was. I decided to finally fix the YOLO detection once and for all, and if successful, tie it together with Telegram. I copied everything over to Claude — no more ChatGPT ragebait. I was so desperate I started glazing Claude talking about how ChatGPT is terrible. Honestly though it was the right call. What followed was probably the most painful dependency debugging session of this entire project. The Pi threw everything at me — numpy version conflicts between picamera2 and opencv, OpenCV itself crashing with “Illegal instruction” because pip installed an x86 build on an ARM chip, then PyTorch doing the exact same thing because it installed a CUDA build completely incompatible with the Pi. I had to hunt down and manually delete broken opencv and numpy installs from multiple locations across the filesystem, increase the Pi’s swap space from 512MB to 1024MB so torch wouldn’t get killed mid-download, reinstall PyTorch from the official CPU ARM wheel, and finally export the YOLOv8n model from PyTorch format to ONNX format so it could run through ONNX Runtime instead — which is dramatically more efficient on ARM hardware. Every single fix revealed another problem underneath it, but step by step it all got resolved. The final detect.py runs three fully independent threads — one capturing camera frames at full speed, one running YOLO inference every 2 seconds without ever blocking the stream, and one serving the live feed to the browser via Flask. YOLO only detects people (class 0 out of 80) which makes it faster, and Telegram alerts fire with a 60 second cooldown so it doesn’t spam. The moment it all worked and a notification hit my phone while the bounding box showed up in the browser was genuinely insane. By the end of today I have a fully working computer vision + notification pipeline running on the Pi — live browser stream, YOLO person detection, and real-time Telegram alerts to my phone and computer. The core software of the Eclipse Lamp is done, but this wasn’t it for today. Sometime in the middle of my recording my print finished and I had the frame and extension. The sad part was the extension wasn’t properly designed, the camera was supposed to look through it but I forgot the hole, lol, but it’s okay because its a small and fast part to reprint. The camera fit inside its case perfectly(Which never happens to me) and I wanted to start screwing. All I did was take the screws that came with all of my servos (5) and aligned them with the holes in the iris. I was so proud of myself when the camera was facing the right way and I got the screw alignment correct. The annoying part was it took me 20 fricking minutes to get 5 screws in and my chubby little finger just couldn’t, not to mention my screwdriver was trash as well. IN the end it worked perfectly and I am SOOOOOO happy for today"}, {"post_id": 22643, "ts": "2026-07-05T06:06:10Z", "hours": 3.0853, "text": "Eclipse Lamp Devlog #9 - Posting all the CAD models on my Github and spicing up my ReadMe. Today I probably worked more on my Github than I ever had before. I also learnt some cool new helpful stuff since I’m pretty much a noob to Github. Today I found out that if i press the period button on my computer it will take me to VS code on my computer or the dev version. With this I was able to minimize my commits by a lot and it was really cool to use it for the first time. Later I realized I had to add markdown files for my iris to camera frame CAD and my Iris Face Extension CAD models. While I was doing this I updated my Custom Created CAD models file. After typing everything out on that, I wanted to work on my ReadMe because it was looking pretty sad and boring. First to please my OCD I set my badges in color coded order, added a table for core components and a quick start guide. The biggest and coolest thing I learnt today were ASCII Diagrams. With these I had Claude Generate them for my repo and I was able to change them around a bit. I first had one created of my whole repo layout with files, folders, and everything else. I then had some others created for power consumption, signal and data flow, and the Detection/Alert pipeline with push notifications. In the end I added my resources and credits for the thing I used in this project. Some of these things may not be correct though because I am not fully done with this project. I also want to thank my friend rishith for helping me organize my github, and learning from his ReadMe organization to make my own. Go check him out, he’s working on Prometheus right now, a fire drone: ( @rishithc )."}, {"post_id": 21997, "ts": "2026-07-04T07:05:13Z", "hours": 2.8014, "text": "Eclipse Lamp Devlog #8 - Setting up my CAD models to print and working on my Github Today I lowkey realized I was in sore need of updating my Github, and I also decided to check printing time on some CAD Models. FIrst I took the top shell and put it into my slicer. The time nearly gave me heart attack as it was 9 hours and 56 minutes. After that I decided to do literally anything possible to get the time under 6 hours. I first took the quality from 0.2-0.28mm layer height, then I set the infill at 0%, and increased speed from 90 to 115 mm/s, and wall speed from 57.5 to 80 mm/s. The final thing I did was probably the most important, I turned on Spiralized Outer Contour, or as some call it “Vase Mode” (ty youtube shorts for teaching me this 2 years ago for some reason 🙏). The next thing I did after fixing the printing time was work on my Github as I had not been paying much attention to it lately. I added folders for the first time(I’m a noob) and organized my code and hardware files. I even added a security file for the camera footage and added badges/shields to my readme for the things I used. I also created some new files like the Top Lamp Construction.md file from Devlog #7 and Custom Created Cad Models.md to paste the onshape and tinkercad files I used. The next thing to do is add a B.O.M to it and finally print out the CAD Models."}, {"post_id": 21349, "ts": "2026-07-03T07:30:14Z", "hours": 2.1142, "text": "Eclipse Lamp Devlog #7 - Creating the CAD model for the Top Shell of the Lamp and working on the Mechanical Iris Frame attachment Today was pretty chill in terms of work as I was focused on making the CAD model for the top shell of the Lamp housing. This housing would hold the iris mechanism and the Lamp module. I first built the large hollow frame after researching the thickness I needed to print my walls at. I’m not sure how strong it is going to be because I set it at 2 walls or 0.8mm. For the wires going from the raspberry pi to camera, the raspberry pi to the servo, and the raspberry pi to the lamp I cut 6 long slots into the bottom of the shell. I also cut a hole for the servo gear(I will use a servo attached to a gear and the gear will attach to the shell because the shaft of the servo is too small) for the pan rotation. I then cut another hole for the Iris mechanism to fit. I needed to place the hole strategically because since the Raspberry pi was in the bottom shell, and the camera is in the top, I would have to keep the distance between them short so the ribbon cable could twist and turn. This wasn’t my proudest moment but to be honest I felt sleep-deprived and didn’t care. It still worked as long as I kept It close enough so I just turned the iris mechanism upside down so the camera was closer and that worked. I created a lid for the lamp later but i might not even use it and let the light shine through. Then I created a frame for the camera to attach behind the iris so it could stay in one piece. I will screw it in or hot glue it physically as it should fit to the back of it and align with its 5 holes(the iris mechanism). The next thing I might do is print the small pieces in here or the bottom shell from Devlog #6, i wanna wait a bit before printing the big lamp shell, not sure how that’ll hold up."}, {"post_id": 20546, "ts": "2026-07-02T05:02:11Z", "hours": 2.0503, "text": "Eclipse Lamp Devlog #6 - Creating the CAD model for the Bottom Shell of the Lamp with the Raspberry Pi and Pan Servo Today was an AMAZING break from all the software I’ve done so far. I was focused on making the CAD model for the bottom shell of the Lamp housing. This housing would hold the Raspberry Pi and the Pan servo responsible for rotating the top Lamp shell around. This model was pretty straightforward to make as I used the premade model I had from onshape I made in Devlog #5. It was a bit rocky though because when I got my Raspberry Pi case imported from printables, It didn’t fit properly in the compartment and didn’t leave room for the servo to center. I first when with 100mm x 100mm which I made beforehand, then 120mm x 120mm which still didn’t fit the servo in the center (It was very close), and after that I was extremely fed up so I just said “screw it” and went to 150mm x 150mm. This size gave me a considerate amount of space for everything to place in. Then I reverted to Tinkercad as it was faster for me and after placing the raspberry pi case, I placed wall holders for the servo to glue onto physically (The servo was centered this time). Sadly this model got even more complicated because when I went to slice it to get a gist of the time consumed, it started at 8 hours and 46 minutes, then i removed the back wall to set it at 6 hours and 52 minutes. After that I wanted it faster so I kept removing the unnecessary walls from the raspberry pi case and I was able to get the time down to 6 hours and 4 minutes, which I was very happy with."}, {"post_id": 19727, "ts": "2026-07-01T03:43:30Z", "hours": 2.2361, "text": "Eclipse Lamp Devlog #5 - Developing KiCad Schematics and starting CAD design for the Lamp Shell I was lowkey in need for some asmr after ChatGPT kept rage-baiting me in terminal, so today I worked on a KiCad schematic for my components and I started the CAD design for the Bottom shell of the lamp. My main goal in creating the complete KiCad schematic for all of the project’s components was so I would have a clear wiring guide during construction, even though I won’t be manufacturing a PCB from it. I ran into a dumb few challenges finding symbols for parts like the Raspberry Pi Camera and the lamp, so I created a custom camera symbol in the KiCad Symbol Editor and represented the lamp using an LED and resistor. I literally wasted like 20 minutes trying to find a nonexistent symbol so I just had to make my own. The remaining components, including the servos, power connections, and a USB-A connector for the lamp, were much less of a headache to add. After finishing the schematic earlier than expected, I used the remaining time to begin designing the lamp enclosure in CAD. I was also surprised because my computer froze for maybe 20 minutes during the recording. I pretty much had a heart-attack because I thought I lost the recording working on this when my computer restarted. I started with the bottom section, which will house the Raspberry Pi and the first servo for the pan-tilt mechanism. While the design is still incomplete, I’m pretty happy with how features like the fillets and the extrusions turned out. My next step will likely be finishing the bottom shell, unless I decide to focus on completing more of the AI system first."}, {"post_id": 19051, "ts": "2026-06-30T07:12:01Z", "hours": 1.9814, "text": "Eclipse Lamp Devlog #4 - Finally getting the Person Detection AI to run properly on my Raspberry Pi Camera Today went EXTREMELY WELL in terms of progress. Finally, after what started back in Devlog 1 and Devlog 3, everything has come together and actually worked end-to-end in a way that feels complete. What began as a messy setup with camera errors, broken environments, and YOLO not even running correctly slowly turned into a full Raspberry Pi computer vision system with a working Picamera2 pipeline, a Flask web server streaming live footage to a browser, and YOLO detection successfully running on real-time frames. Along the way, there were a lot of setbacks—camera being “busy,” venv issues breaking imports, OpenCV display problems, dependency conflicts, and even moments where the system felt completely stuck—but step by step those were fixed until the full pipeline finally ran without crashing. By the end, I actually got YOLO detection working properly on live camera input, with bounding boxes showing up and the whole system functioning as intended. The main issue left now is performance: the system works, but it’s still slower than I want, with noticeable lag and lower frame rate than ideal. I went back and rebuilt parts of it trying to make it faster, but I didn’t fully finish optimizing it yet. That final tuning—improving FPS, reducing delay, and making the stream smoother—is something I’ll come back to later. Still, today was a complete success because the full system is alive, functional, and running exactly as planned, and now it’s just a matter of refinement rather than building from scratch."}, {"post_id": 18171, "ts": "2026-06-29T06:27:16Z", "hours": 1.6517, "text": "Eclipse Lamp Devlog #3 - Testing Mechanical Iris Code post 3D-printing and trying to finish Person Detection AI software for Raspberry Pi _________________________________________________________________________ Today I made somewhat strong progress in two areas but as always i sold on the software side lol. First, on the mechanical side, I tested the mechanical iris with an SG90 servo by wiring it to an Elegoo Uno to validate the Arduino code, which successfully controlled the opening and closing after uploading an existing sketch. I then translated the code to Python, wired it to a Raspberry Pi, installed the required libraries, and confirmed the iris worked the same way, completing the mechanical system. Luckily this made me failing on my AI seem easier to deal with. Working on this I genuinely insane and started raging on ChatGPT after making me do the same thing 20 times. I continued the person detection AI setup on the Raspberry Pi camera by confirming libcamera and Picamera2 were working, building a Flask live video stream that displayed real-time footage in the browser, and testing YOLO (Ultralytics), but I kept running into environment and dependency issues like missing modules, virtual environment conflicts, and broken installs that stopped full AI detection from running, and ChatGPT was just so bad at helping, so the next step is fixing the Python environment and system dependencies to properly run YOLO on the live camera feed."}, {"post_id": 18001, "ts": "2026-06-28T23:35:09Z", "hours": 0.6689, "text": "Eclipse Lamp Devlog #2 - Preparing to Code and 3D-Print my Mechanical Iris Design Today gave me a little more hope in actually getting this project done well because i was able to get the perfect Mechanical iris model that could shield my camera. It was much better working with actual hardware and arduino that dealing with terminal commands taking over 30 years. It took me some time to find the right model that was small enough but still extremely functional and versatile, but after some time I found the perfect SG90 Mechanical Iris on thingiverse.com by Lore09. After finding the files I set them up in my slicer to arrange them for 3D-printing later on. The time estimates to be about 3 hours so in the meantime i thought of writing code for the servo motor to test the iris. I also have no idea why my copy and paste wasn’t working but it is kind of expected because my computer is as slow as a snail. For this I used Arduino IDE to write the servo code, here were the comments i made to explain this code better: //This code is too check the physical limits of the SG90 servo when it is used in the iris construction //It will use the range of 0-63 degrees(as previously tested before as the physical constraint angles) angle it will //start at 0 degrees and go to 63, then loop back to get the iris adjustable central opening fully closed and fully opened //Note: My copy does not work today for some reason so i will have to type my arduino code manually resourcing it from claude. //I will test this code in another devlog once the iris is done 3d printing and I have the servo attached. The next thing to do is complete stage 2 and assemble the parts after printing and test the servo code for functionality and I hope like some other times, it does not heat-up and automatically break after my first code upload."}, {"post_id": 17448, "ts": "2026-06-28T07:13:05Z", "hours": 1.6125, "text": "Eclipse Lamp Devlog #1 - Installing Person Detection AI on my Camera Today was the start of this project and I already know this is going to be really annoying later on. It didn’t go totally as planned, but I still made some progress with my AI camera setup on the Raspberry Pi. This was my first attempt at trying to add the AI person detection software on my Raspberry Pi V2 noIR Camera connected to my Raspberry Pi model B. I spent most of the time coding in terminal and also python scripts to implement computer vision. I got the camera V2 working and tested live video output using rpicam, and started building the software side with Flask and OpenCV to eventually stream footage in a browser. I tried to take it further by installing YOLO (ultralytics) for human detection, but I ran into a bunch of errors during setup and the module wouldn’t import properly afterward. Also ChatGPT kept making me download and delete files over and over again. Even though I couldn’t finish the full AI detection today, I’m planning to come back later and switch to a simpler detection model so I can get real-time bounding boxes and continue building the Eclipse Lamp system."}]...
|
Title: The Eclipse Lamp by @vrunchil7 | Stardance
Title: The Eclipse Lamp by @vrunchil7 | Stardance
Devlogs:
Eclipse Lamp Devlog #1 - Installing Person Detection AI on my Camera Today was the start of this project and I already know this is going to be really annoying later on. It didn’t go totally as planned, but I still made some progress with my AI camera setup on the Raspberry Pi. This was my first attempt at trying to add the AI person detection software on my Raspberry Pi V2 noIR Camera connected to my Raspberry Pi model B. I spent most of the time coding in terminal and also python scripts to implement computer vision. I got the camera V2 working and tested live video output using rpicam, and started building the software side with Flask and OpenCV to eventually stream footage in a browser. I tried to take it further by installing YOLO (ultralytics) for human detection, but I ran into a bunch of errors during setup and the module wouldn’t import properly afterward. Also ChatGPT kept making me download and delete files over and over again. Even though I couldn’t finish the full AI detection today, I’m planning to come back later and switch to a simpler detection model so I can get real-time bounding boxes and continue building the Eclipse Lamp system.
Eclipse Lamp Devlog #2 - Preparing to Code and 3D-Print my Mechanical Iris Design Today gave me a little more hope in actually getting this project done well because i was able to get the perfect Mechanical iris model that could shield my camera. It was much better working with actual hardware and arduino that dealing with terminal commands taking over 30 years. It took me some time to find the right model that was small enough but still extremely functional and versatile, but after some time I found the perfect SG90 Mechanical Iris on thingiverse.com by Lore09. After finding the files I set them up in my slicer to arrange them for 3D-printing later on. The time estimates to be about 3 hours so in the meantime i thought of writing code for the servo motor to test the iris. I also have no idea why my copy and paste wasn’t working but it is kind of expected because my computer is as slow as a snail. For this I used Arduino IDE to write the servo code, here were the comments i made to explain this code better: //This code is too check the physical limits of the SG90 servo when it is used in the iris construction //It will use the range of 0-63 degrees(as previously tested before as the physical constraint angles) angle it will //start at 0 degrees and go to 63, then loop back to get the iris adjustable central opening fully closed and fully opened //Note: My copy does not work today for some reason so i will have to type my arduino code manually resourcing it from claude. //I will test this code in another devlog once the iris is done 3d printing and I have the servo attached. The next thing to do is complete stage 2 and assemble the parts after printing and test the servo code for functionality and I hope like some other times, it does not heat-up and automatically break after my first code upload.
Eclipse Lamp Devlog #3 - Testing Mechanical Iris Code post 3D-printing and trying to finish Person Detection AI software for Raspberry Pi _________________________________________________________________________ Today I made somewhat strong progress in two areas but as always i sold on the software side lol. First, on the mechanical side, I tested the mechanical iris with an SG90 servo by wiring it to an Elegoo Uno to validate the Arduino code, which successfully controlled the opening and closing after uploading an existing sketch. I then translated the code to Python, wired it to a Raspberry Pi, installed the required libraries, and confirmed the iris worked the same way, completing the mechanical system. Luckily this made me failing on my AI seem easier to deal with. Working on this I genuinely insane and started raging on ChatGPT after making me do the same thing 20 times. I continued the person detection AI setup on the Raspberry Pi camera by confirming libcamera and Picamera2 were working, building a Flask live video stream that displayed real-time footage in the browser, and testing YOLO (Ultralytics), but I kept running into environment and dependency issues like missing modules, virtual environment conflicts, and broken installs that stopped full AI detection from running, and ChatGPT was just so bad at helping, so the next step is fixing the Python environment and system dependencies to properly run YOLO on the live camera feed.
Eclipse Lamp Devlog #4 - Finally getting the Person Detection AI to run properly on my Raspberry Pi Camera Today went EXTREMELY WELL in terms of progress. Finally, after what started back in Devlog 1 and Devlog 3, everything has come together and actually worked end-to-end in a way that feels complete. What began as a messy setup with camera errors, broken environments, and YOLO not even running correctly slowly turned into a full Raspberry Pi computer vision system with a working Picamera2 pipeline, a Flask web server streaming live footage to a browser, and YOLO detection successfully running on real-time frames. Along the way, there were a lot of setbacks—camera being “busy,” venv issues breaking imports, OpenCV display problems, dependency conflicts, and even moments where the system felt completely stuck—but step by step those were fixed until the full pipeline finally ran without crashing. By the end, I actually got YOLO detection working properly on live camera input, with bounding boxes showing up and the whole system functioning as intended. The main issue left now is performance: the system works, but it’s still slower than I want, with noticeable lag and lower frame rate than ideal. I went back and rebuilt parts of it trying to make it faster, but I didn’t fully finish optimizing it yet. That final tuning—improving FPS, reducing delay, and making the stream smoother—is something I’ll come back to later. Still, today was a complete success because the full system is alive, functional, and running exactly as planned, and now it’s just a matter of refinement rather than building from scratch.
Eclipse Lamp Devlog #5 - Developing KiCad Schematics and starting CAD design for the Lamp Shell I was lowkey in need for some asmr after ChatGPT kept rage-baiting me in terminal, so today I worked on a KiCad schematic for my components and I started the CAD design for the Bottom shell of the lamp. My main goal in creating the complete KiCad schematic for all of the project’s components was so I would have a clear wiring guide during construction, even though I won’t be manufacturing a PCB from it. I ran into a dumb few challenges finding symbols for parts like the Raspberry Pi Camera and the lamp, so I created a custom camera symbol in the KiCad Symbol Editor and represented the lamp using an LED and resistor. I literally wasted like 20 minutes trying to find a nonexistent symbol so I just had to make my own. The remaining components, including the servos, power connections, and a USB-A connector for the lamp, were much less of a headache to add. After finishing the schematic earlier than expected, I used the remaining time to begin designing the lamp enclosure in CAD. I was also surprised because my computer froze for maybe 20 minutes during the recording. I pretty much had a heart-attack because I thought I lost the recording working on this when my computer restarted. I started with the bottom section, which will house the Raspberry Pi and the first servo for the pan-tilt mechanism. While the design is still incomplete, I’m pretty happy with how features like the fillets and the extrusions turned out. My next step will likely be finishing the bottom shell, unless I decide to focus on completing more of the AI system first.
Eclipse Lamp Devlog #6 - Creating the CAD model for the Bottom Shell of the Lamp with the Raspberry Pi and Pan Servo Today was an AMAZING break from all the software I’ve done so far. I was focused on making the CAD model for the bottom shell of the Lamp housing. This housing would hold the Raspberry Pi and the Pan servo responsible for rotating the top Lamp shell around. This model was pretty straightforward to make as I used the premade model I had from onshape I made in Devlog #5. It was a bit rocky though because when I got my Raspberry Pi case imported from printables, It didn’t fit properly in the compartment and didn’t leave room for the servo to center. I first when with 100mm x 100mm which I made beforehand, then 120mm x 120mm which still didn’t fit the servo in the center (It was very close), and after that I was extremely fed up so I just said “screw it” and went to 150mm x 150mm. This size gave me a considerate amount of space for everything to place in. Then I reverted to Tinkercad as it was faster for me and after placing the raspberry pi case, I placed wall holders for the servo to glue onto physically (The servo was centered this time). Sadly this model got even more complicated because when I went to slice it to get a gist of the time consumed, it started at 8 hours and 46 minutes, then i removed the back wall to set it at 6 hours and 52 minutes. After that I wanted it faster so I kept removing the unnecessary walls from the raspberry pi case and I was able to get the time down to 6 hours and 4 minutes, which I was very happy with.
Eclipse Lamp Devlog #7 - Creating the CAD model for the Top Shell of the Lamp and working on the Mechanical Iris Frame attachment Today was pretty chill in terms of work as I was focused on making the CAD model for the top shell of the Lamp housing. This housing would hold the iris mechanism and the Lamp module. I first built the large hollow frame after researching the thickness I needed to print my walls at. I’m not sure how strong it is going to be because I set it at 2 walls or 0.8mm. For the wires going from the raspberry pi to camera, the raspberry pi to the servo, and the raspberry pi to the lamp I cut 6 long slots into the bottom of the shell. I also cut a hole for the servo gear(I will use a servo attached to a gear and the gear will attach to the shell because the shaft of the servo is too small) for the pan rotation. I then cut another hole for the Iris mechanism to fit. I needed to place the hole strategically because since the Raspberry pi was in the bottom shell, and the camera is in the top, I would have to keep the distance between them short so the ribbon cable could twist and turn. This wasn’t my proudest moment but to be honest I felt sleep-deprived and didn’t care. It still worked as long as I kept It close enough so I just turned the iris mechanism upside down so the camera was closer and that worked. I created a lid for the lamp later but i might not even use it and let the light shine through. Then I created a frame for the camera to attach behind the iris so it could stay in one piece. I will screw it in or hot glue it physically as it should fit to the back of it and align with its 5 holes(the iris mechanism). The next thing I might do is print the small pieces in here or the bottom shell from Devlog #6, i wanna wait a bit before printing the big lamp shell, not sure how that’ll hold up.
Eclipse Lamp Devlog #8 - Setting up my CAD models to print and working on my Github Today I lowkey realized I was in sore need of updating my Github, and I also decided to check printing time on some CAD Models. FIrst I took the top shell and put it into my slicer. The time nearly gave me heart attack as it was 9 hours and 56 minutes. After that I decided to do literally anything possible to get the time under 6 hours. I first took the quality from 0.2-0.28mm layer height, then I set the infill at 0%, and increased speed from 90 to 115 mm/s, and wall speed from 57.5 to 80 mm/s. The final thing I did was probably the most important, I turned on Spiralized Outer Contour, or as some call it “Vase Mode” (ty youtube shorts for teaching me this 2 years ago for some reason 🙏). The next thing I did after fixing the printing time was work on my Github as I had not been paying much attention to it lately. I added folders for the first time(I’m a noob) and organized my code and hardware files. I even added a security file for the camera footage and added badges/shields to my readme for the things I used. I also created some new files like the Top Lamp Construction.md file from Devlog #7 and Custom Created Cad Models.md to paste the onshape and tinkercad files I used. The next thing to do is add a B.O.M to it and finally print out the CAD Models.
Eclipse Lamp Devlog #9 - Posting all the CAD models on my Github and spicing up my ReadMe. Today I probably worked more on my Github than I ever had before. I also learnt some cool new helpful stuff since I’m pretty much a noob to Github. Today I found out that if i press the period button on my computer it will take me to VS code on my computer or the dev version. With this I was able to minimize my commits by a lot and it was really cool to use it for the first time. Later I realized I had to add markdown files for my iris to camera frame CAD and my Iris Face Extension CAD models. While I was doing this I updated my Custom Created CAD models file. After typing everything out on that, I wanted to work on my ReadMe because it was looking pretty sad and boring. First to please my OCD I set my badges in color coded order, added a table for core components and a quick start guide. The biggest and coolest thing I learnt today were ASCII Diagrams. With these I had Claude Generate them for my repo and I was able to change them around a bit. I first had one created of my whole repo layout with files, folders, and everything else. I then had some others created for power consumption, signal and data flow, and the Detection/Alert pipeline with push notifications. In the end I added my resources and credits for the thing I used in this project. Some of these things may not be correct though because I am not fully done with this project. I also want to thank my friend rishith for helping me organize my github, and learning from his ReadMe organization to make my own. Go check him out, he’s working on Prometheus right now, a fire drone: ( @rishithc ).
Eclipse Lamp Devlog #10 - Finishing the YOLO and AI Person Detection, starting and finishing the Telegram Push Notification system, and assembling the printed Iris-Camera frame shutter system YOOOOOOOOOOOO!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Today was actually the most productive session ever. First, before I started my recording I finished the iris-camera frame attachment that attaches the camera to the back of the iris mechanism. My main motive for today was getting the Telegram notification setup, but I did so much more. First I decided on using Telegram, downloading the app on my phone and computer for notifications. Then I created a bot through BotFather, got my bot token and chat ID, and went into terminal so the Pi could send messages directly to my Telegram. Within minutes I was getting notifications on both my phone and computer simultaneously — that part was actually easy and satisfying to get done fast. After that I said “third time’s the charm for AI” and it really was. I decided to finally fix the YOLO detection once and for all, and if successful, tie it together with Telegram. I copied everything over to Claude — no more ChatGPT ragebait. I was so desperate I started glazing Claude talking about how ChatGPT is terrible. Honestly though it was the right call. What followed was probably the most painful dependency debugging session of this entire project. The Pi threw everything at me — numpy version conflicts between picamera2 and opencv, OpenCV itself crashing with “Illegal instruction” because pip installed an x86 build on an ARM chip, then PyTorch doing the exact same thing because it installed a CUDA build completely incompatible with the Pi. I had to hunt down and manually delete broken opencv and numpy installs from multiple locations across the filesystem, increase the Pi’s swap space from 512MB to 1024MB so torch wouldn’t get killed mid-download, reinstall PyTorch from the official CPU ARM wheel, and finally export the YOLOv8n model from PyTorch format to ONNX format so it could run through ONNX Runtime instead — which is dramatically more efficient on ARM hardware. Every single fix revealed another problem underneath it, but step by step it all got resolved. The final detect.py runs three fully independent threads — one capturing camera frames at full speed, one running YOLO inference every 2 seconds without ever blocking the stream, and one serving the live feed to the browser via Flask. YOLO only detects people (class 0 out of 80) which makes it faster, and Telegram alerts fire with a 60 second cooldown so it doesn’t spam. The moment it all worked and a notification hit my phone while the bounding box showed up in the browser was genuinely insane. By the end of today I have a fully working computer vision + notification pipeline running on the Pi — live browser stream, YOLO person detection, and real-time Telegram alerts to my phone and computer. The core software of the Eclipse Lamp is done, but this wasn’t it for today. Sometime in the middle of my recording my print finished and I had the frame and extension. The sad part was the extension wasn’t properly designed, the camera was supposed to look through it but I forgot the hole, lol, but it’s okay because its a small and fast part to reprint. The camera fit inside its case perfectly(Which never happens to me) and I wanted to start screwing. All I did was take the screws that came with all of my servos (5) and aligned them with the holes in the iris. I was so proud of myself when the camera was facing the right way and I got the screw alignment correct. The annoying part was it took me 20 fricking minutes to get 5 screws in and my chubby little finger just couldn’t, not to mention my screwdriver was trash as well. IN the end it worked perfectly and I am SOOOOOO happy for today
Eclipse Lamp Devlog #11 - Finishing the Bottom Lamp Case print and assembling the Servo and Pi to it. Also Finishing the B.O.M. Today was pretty fun since I got to work mostly on the hardware. I started my print at 8 AM (the earliest I’ve woken up this summer) and let the 6-hour print run. I came back at 2:13 to see the final product. Since this was the bottom shell, I needed to print it in a dark color so light wouldn’t shine through. I was itching to use my new red-and-black silk PLA, so I loaded it into my extruder and got started. Next, I was ready to hot glue the servo into the walls I designed, but first I needed to make sure the servo shaft was centered. I grabbed a 150 × 150 mm plate and used a compass and ruler to find the midpoint (shoutout to my geometry teacher). I found that the servo shaft was only 2 mm off-center, which I was totally fine with. After that, I tried fitting the Raspberry Pi into its spot but realized I had made a CAD mistake. When I aligned it with the screw holes, the audio jack stuck out because I hadn’t designed an opening for it. Instead of reprinting the whole part, I grabbed my hot glue gun and burned a hole through the side. It worked perfectly, and the Pi fit right in. I originally wanted to screw the Pi in place, but I didn’t have the right size hardware. I needed 3.5 mm screws and only had 3 mm and 4 mm, so I ended up hot gluing it in instead, and it held perfectly. I also hot glued the camera into its enclosure so it became part of the iris mechanism. After finishing the hardware, I started and finished the BOM and posted it to my GitHub. The next step is printing the top case....
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1792713089.836152
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1793317889.836152
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41398
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My own site! by @vrunchil7 | Stardance
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vrunchil7
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0
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0.0
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0
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[]
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[]
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Title: My own site! by @vrunchil7 | Stardance
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1792802954.067622
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1793407754.067622
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17706
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NobleOS by @vrplays | Stardance
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vrplays
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2
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8.0
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-25T13:56:50Z", "hours": 2.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I’ve added a lot more to NobleOS than before. So much in fact it doesn’t even look like the original anymore! It now features a terminal, a file system, and a wallpaper picker! Check the screenshot for yourself (or devlog 4 if it doesn’t load). Doesn’t it look much more different now?", "repo": "https://github.com/VR2011/NobleOS", "demo": "https://noble-os-omega.vercel.app/"}, {"ship_num": 2, "ts": "2026-06-15T23:03:28Z", "hours": 6.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "NobleOS is a simple web-based operating system with multiple features built into it. There’s a couple apps you can tinker around with, and a cool theming menu where you can try different themes and see how they look!", "repo": "https://github.com/VR2011/NobleOS", "demo": "https://noble-os-omega.vercel.app/"}]...
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[{"post_id": 15663, "ts": "202 [{"post_id": 15663, "ts": "2026-06-25T13:55:11Z", "hours": 2.0344, "text": "NobleOS - Devlop 4 It’s been quite a while, but now that WebOS 2 is out, I’ve decided to come back and add new features. There is now a terminal, a simple file system, and a wallpaper picker in the theming app! Those are the three new features I’ve added that weren’t in WebOS 1. Check it out here !"}, {"post_id": 9537, "ts": "2026-06-15T22:16:07Z", "hours": 3.0931, "text": "NobleOS - Devlog 3 This is a big jump from before. I have now added a start menu that lets you launch apps from there as well. It also shows the time. Also, there is now a browser (which unfortunately doesn’t work for most websites…)! It’s pretty simple. You can press enter/return to go to the site, and use the back and forward arrow keys to well, go back and forward. Finally, theming! You probably already saw this from glancing at the screenshot provided, but now there are 5 different themes to choose from while using the OS - Classic, Blue, Pink, Dark, and Light. Enjoy!"}, {"post_id": 8765, "ts": "2026-06-14T16:02:08Z", "hours": 1.2656, "text": "NobleOS - Devlog 2 Added the calculator app. In addition, there are a few window tweaks that got fixed/added. I never linked the website here, so here’s the site if you want to check it out! https://noble-os-omega.vercel.app/"}, {"post_id": 8455, "ts": "2026-06-14T01:54:28Z", "hours": 1.6056, "text": "NobleOS - Devlog 1 First devlog. Nothing much on the actual project, besides a simple about button. I’ll probably add a calculator next."}]...
|
Title: NobleOS by @vrplays | Stardance
Devlogs:
N Title: NobleOS by @vrplays | Stardance
Devlogs:
NobleOS - Devlog 1 First devlog. Nothing much on the actual project, besides a simple about button. I’ll probably add a calculator next.
NobleOS - Devlog 2 Added the calculator app. In addition, there are a few window tweaks that got fixed/added. I never linked the website here, so here’s the site if you want to check it out! https://noble-os-omega.vercel.app/
NobleOS - Devlog 3 This is a big jump from before. I have now added a start menu that lets you launch apps from there as well. It also shows the time. Also, there is now a browser (which unfortunately doesn’t work for most websites…)! It’s pretty simple. You can press enter/return to go to the site, and use the back and forward arrow keys to well, go back and forward. Finally, theming! You probably already saw this from glancing at the screenshot provided, but now there are 5 different themes to choose from while using the OS - Classic, Blue, Pink, Dark, and Light. Enjoy!
NobleOS - Devlop 4 It’s been quite a while, but now that WebOS 2 is out, I’ve decided to come back and add new features. There is now a terminal, a simple file system, and a wallpaper picker in the theming app! Those are the three new features I’ve added that weren’t in WebOS 1. Check it out here !
Ships:
NobleOS is a simple web-based operating system with multiple features built into it. There’s a couple apps you can tinker around with, and a cool theming menu where you can try different themes and see how they look!
I’ve added a lot more to NobleOS than before. So much in fact it doesn’t even look like the original anymore! It now features a terminal, a file system, and a wallpaper picker! Check the screenshot for yourself (or devlog 4 if it doesn’t load). Doesn’t it look much more different now?...
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1793317794.2286959
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1793404194.2286959
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18323
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Appick by @vrplays | Stardance
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vrplays
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1
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4.0
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-23T16:05:13Z", "hours": 4.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "Appick is a four key macropad that can launch apps for you instantly. Currently, it can open Brave, Discord, Steam, and Spotify, but with some modifications it can open any app! This took a long time to create, but eventually I was able to finish this and created a good product.", "repo": "https://github.com/VR2011/Appick", "demo": ""}]...
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[{"post_id": 14448, "ts": "202 [{"post_id": 14448, "ts": "2026-06-23T16:02:02Z", "hours": 0.3356, "text": "Devlog #3 - Firmware complete! With that done, my Hackpad is finally complete! I thought that I wouldn’t even be able to complete this, but with lots of perseverance (nasa reference lol) I was able to create full projects in applications I’ve NEVER used before. Seriously, I’ve never used Fusion 360 or KiCad before, but with help from a lot of resources (and a little bit of AI), I’ve created working projects. Hopefully this is everything I need to do, because this took a very long time."}, {"post_id": 13939, "ts": "2026-06-22T21:33:52Z", "hours": 2.5164, "text": "Devlog #2 - CAD and PCB FINISHED! This took way too long to complete. I had to remake the CAD project maybe 4 times because of random issues, and had to rewire my PCB many, many times thanks to the fact that the wires wouldn’t move with the objects. Anyway, I also added the components to my PCB and made a final, full CAD project. IF ANYONE IS SEEING THIS, PLEASE GIVE ME FEEDBACK!!!!!!"}, {"post_id": 13520, "ts": "2026-06-22T04:00:44Z", "hours": 0.9594, "text": "Devlog #1 - CAD and PCB Took a bit of time (unfortunately I didn’t log some of the time I spent on the CAD,) but I finished the base of the CAD, along with the PCB. What do you guys think?"}]...
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Title: Appick by @vrplays | Stardance
Devlogs:
De Title: Appick by @vrplays | Stardance
Devlogs:
Devlog #1 - CAD and PCB Took a bit of time (unfortunately I didn’t log some of the time I spent on the CAD,) but I finished the base of the CAD, along with the PCB. What do you guys think?
Devlog #2 - CAD and PCB FINISHED! This took way too long to complete. I had to remake the CAD project maybe 4 times because of random issues, and had to rewire my PCB many, many times thanks to the fact that the wires wouldn’t move with the objects. Anyway, I also added the components to my PCB and made a final, full CAD project. IF ANYONE IS SEEING THIS, PLEASE GIVE ME FEEDBACK!!!!!!
Devlog #3 - Firmware complete! With that done, my Hackpad is finally complete! I thought that I wouldn’t even be able to complete this, but with lots of perseverance (nasa reference lol) I was able to create full projects in applications I’ve NEVER used before. Seriously, I’ve never used Fusion 360 or KiCad before, but with help from a lot of resources (and a little bit of AI), I’ve created working projects. Hopefully this is everything I need to do, because this took a very long time.
Ships:
Appick is a four key macropad that can launch apps for you instantly. Currently, it can open Brave, Discord, Steam, and Spotify, but with some modifications it can open any app! This took a long time to create, but eventually I was able to finish this and created a good product....
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1793332118.5727532
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1793418518.5727532
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24885
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Minepad by @vrplays | Stardance
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vrplays
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0
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3.48
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0
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[]
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[{"post_id": 20334, "ts": "202 [{"post_id": 20334, "ts": "2026-07-01T22:14:05Z", "hours": 0.3006, "text": "Minepad - Devlog #3 I realized that you needed three or more devlogs to ship a project, and I only had two devlogs because I combined my firmware and CAD logs into one. So, I decided to spend some time looking at my firmware to make sure everything’s alright! It seems good to me, so I’ll make this devlog and ship. …or not. I guess you can’t ship hardware projects?? Whatever, I’ll still log this time!"}, {"post_id": 19303, "ts": "2026-06-30T15:57:01Z", "hours": 2.4306, "text": "Minepad - Devlog #2 The second devlog of this project. Yeah, it’s a hackpad, however I have already made a hackpad so this will technically be a hardware project since I can make multiple of those. Anyway, I finished with the CAD project and also made the firmware for the macropad. Time to ship this! (Well, I have to make a BOM first lol)"}, {"post_id": 18737, "ts": "2026-06-29T22:29:18Z", "hours": 0.7528, "text": "Minepad - Devlog #1 First devlog of this hardware project. I wanted to create this for my hackpad but I was already done with my original hackpad when I got the idea for this. Minepad is going to have a couple buttons that’ll let the user interact with the game. Here’s what I have in mind. WASD keys for movement Esc and F3 menus E, Q, T for inventory, drop an item, and text respectively Space and tab keys So far, I’ve finished designing my PCB. What do you guys think?"}]...
|
Title: Minepad by @vrplays | Stardance
Devlogs:
M Title: Minepad by @vrplays | Stardance
Devlogs:
Minepad - Devlog #1 First devlog of this hardware project. I wanted to create this for my hackpad but I was already done with my original hackpad when I got the idea for this. Minepad is going to have a couple buttons that’ll let the user interact with the game. Here’s what I have in mind. WASD keys for movement Esc and F3 menus E, Q, T for inventory, drop an item, and text respectively Space and tab keys So far, I’ve finished designing my PCB. What do you guys think?
Minepad - Devlog #2 The second devlog of this project. Yeah, it’s a hackpad, however I have already made a hackpad so this will technically be a hardware project since I can make multiple of those. Anyway, I finished with the CAD project and also made the firmware for the macropad. Time to ship this! (Well, I have to make a BOM first lol)
Minepad - Devlog #3 I realized that you needed three or more devlogs to ship a project, and I only had two devlogs because I combined my firmware and CAD logs into one. So, I decided to spend some time looking at my firmware to make sure everything’s alright! It seems good to me, so I’ll make this devlog and ship. …or not. I guess you can’t ship hardware projects?? Whatever, I’ll still log this time!...
|
1793346922.8548331
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1793951722.8548331
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29373
|
Solarium by @vrplays | Stardance
|
vrplays
|
1
|
26.9
|
131
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-10T22:08:23Z", "hours": 13.0, "multiplier": 9.86, "payout": 131, "blessing": "neutral", "text": "Solarium is an operating system built from scratch. This means it isn’t built off ANYTHING. Not Linux, not anything like that, just code. Currently, it’s in an early phase, but as time goes on, more content will be added. Please give this a good rating! I spent a long time getting this to work without bugs. Currently, Solarium features several terminal commands that you can use. It mainly serves to show what the OS is capable of right now. There’s also a couple visual features, like a boot logo and multiple fonts! Please realize that despite the lack of content, I still spent so much time working on this project! As of shipping this, 13 hours of time! There will be more ships in the future, but in the meantime, this is what I have as of right now. Enjoy!", "repo": "https://github.com/VR2011/Solarium/", "demo": "https://github.com/VR2011/Solarium/releases"}]...
|
[{"post_id": 37978, "ts": "202 [{"post_id": 37978, "ts": "2026-07-31T01:55:34Z", "hours": 9.27, "text": "Not an update, but just a devlog. You guys might’ve wondered where I’ve been. I’ve been pretty busy over the past few weeks, having travelled to other states multiple times recently. I wasn’t able to get time to work on the OS, but whenever I do, I spent most of the time getting it to work on my Mac. I’ve spent way too long on this, and I hope it’s over soon. I’ll likely publish an update once I get this fixed. But for now, know that I am still working on this! (However I’ll be gone again in a few weeks once again…) I’m either gonna finish up some terminal features, or move on to a GUI. I’m gonna plan to stay away from hardware support for a bit. In the meantime, enjoy what I have so far! (If you notice, you’ll see that this is the same image as my banner. For some reason my ship got declined because of a new rule(?) where the banner must be the project and not a logo…)"}, {"post_id": 27736, "ts": "2026-07-13T15:42:26Z", "hours": 4.6336, "text": "Version 2.0 I’m back. Seems that my project still hasn’t been shipped yet, but that’s alright. Solarium has gotten a lot of bug fixes, and the fonts now look more polished. I also changed the video display so the output looks much better now! In addition to minor changes, Solarium now works on real hardware! You can help contribute to the OS Support list by going to the repo, and opening a PR with your changes. You can also just ping me in Slack or leave a comment here with the same details, and I can add it. I also added a screenshot showing the OS working on my Chromebook!"}, {"post_id": 26121, "ts": "2026-07-10T18:38:50Z", "hours": 5.4814, "text": "Devlog 1.2 Much longer than the devlogs I’ve sent here. I added a lot more stuff compared to the previous devlog, which was more bugfixes than actual content. There’s now a boot logo that appears for a few seconds before going back to the terminal! In addition, there’s now fonts! You can use the help command for more info. Alongside the actual OS, I’m going to start trying to implement support for actual hardware. It only works on VMs, so real hardware is going to be interesting."}, {"post_id": 24176, "ts": "2026-07-07T16:05:17Z", "hours": 3.9842, "text": "Devlog 1.1 Not gonna lie, this sucked. I spent a long time getting arrow keys to work. Luckily, I was finally able to figure it out. I also changed some stuff backend, but a few things on the front end. Also added this cool thing; the first instance of color! Isn’t that cool? Anyway, I’ll work on new stuff later, maybe some more commands."}, {"post_id": 20397, "ts": "2026-07-01T23:58:11Z", "hours": 3.8125, "text": "Devlog 1.0 Well, this is going to be something. Solarium is an operating system. From scratch. It is not Linux, it is not based off anything else. Right now, it’s just a terminal that has a few commands, and well, that’s pretty much it. What do you expect from a first version? What do you think of this?"}]...
|
Title: Solarium by @vrplays | Stardance
Devlogs:
Title: Solarium by @vrplays | Stardance
Devlogs:
Devlog 1.0 Well, this is going to be something. Solarium is an operating system. From scratch. It is not Linux, it is not based off anything else. Right now, it’s just a terminal that has a few commands, and well, that’s pretty much it. What do you expect from a first version? What do you think of this?
Devlog 1.1 Not gonna lie, this sucked. I spent a long time getting arrow keys to work. Luckily, I was finally able to figure it out. I also changed some stuff backend, but a few things on the front end. Also added this cool thing; the first instance of color! Isn’t that cool? Anyway, I’ll work on new stuff later, maybe some more commands.
Devlog 1.2 Much longer than the devlogs I’ve sent here. I added a lot more stuff compared to the previous devlog, which was more bugfixes than actual content. There’s now a boot logo that appears for a few seconds before going back to the terminal! In addition, there’s now fonts! You can use the help command for more info. Alongside the actual OS, I’m going to start trying to implement support for actual hardware. It only works on VMs, so real hardware is going to be interesting.
Version 2.0 I’m back. Seems that my project still hasn’t been shipped yet, but that’s alright. Solarium has gotten a lot of bug fixes, and the fonts now look more polished. I also changed the video display so the output looks much better now! In addition to minor changes, Solarium now works on real hardware! You can help contribute to the OS Support list by going to the repo, and opening a PR with your changes. You can also just ping me in Slack or leave a comment here with the same details, and I can add it. I also added a screenshot showing the OS working on my Chromebook!
Not an update, but just a devlog. You guys might’ve wondered where I’ve been. I’ve been pretty busy over the past few weeks, having travelled to other states multiple times recently. I wasn’t able to get time to work on the OS, but whenever I do, I spent most of the time getting it to work on my Mac. I’ve spent way too long on this, and I hope it’s over soon. I’ll likely publish an update once I get this fixed. But for now, know that I am still working on this! (However I’ll be gone again in a few weeks once again…) I’m either gonna finish up some terminal features, or move on to a GUI. I’m gonna plan to stay away from hardware support for a bit. In the meantime, enjoy what I have so far! (If you notice, you’ll see that this is the same image as my banner. For some reason my ship got declined because of a new rule(?) where the banner must be the project and not a logo…)
Ships:
Solarium is an operating system built from scratch. This means it isn’t built off ANYTHING. Not Linux, not anything like that, just code. Currently, it’s in an early phase, but as time goes on, more content will be added. Please give this a good rating! I spent a long time getting this to work without bugs. Currently, Solarium features several terminal commands that you can use. It mainly serves to show what the OS is capable of right now. There’s also a couple visual features, like a boot logo and multiple fonts! Please realize that despite the lack of content, I still spent so much time working on this project! As of shipping this, 13 hours of time! There will be more ships in the future, but in the meantime, this is what I have as of right now. Enjoy!...
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1793252950.4308138
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1793339350.4308138
|
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38679
|
Magpie by @vrplays | Stardance
|
vrplays
|
0
|
1.26
|
0
|
[]
|
[{"post_id": 33826, "ts": "202 [{"post_id": 33826, "ts": "2026-07-24T02:06:46Z", "hours": 1.2583, "text": "Magpie - The Start Hello once again! This is the fifth project I’ve started working on in Stardance, and what I consider my second “grand” project. My idea for Magpie is pretty big; it’s a keyboard with no physical keys; everything is on a single display. The display itself is touchscreen, and underneath are motors that vibrate to simulate the feel of a click. There will also be speakers so that each click can sound like a real one too, further making the experience feel better. In addition to also being a keyboard, I have the plan to also allow for different layouts, like different keyboard inputs, a drawing tablet, or maybe even audio plugins! Right now, there really isn’t much to say about what’s in the project right now. I started working on the software part of it. Right now, its a Qt-based application that only shows a few keys that show a simple animation when clicked. My plan is to have the keyboard itself act as some sort of mini-computer, with everything being run on a Raspberry Pi. What do you guys think?"}]...
|
Title: Magpie by @vrplays | Stardance
Devlogs:
Ma Title: Magpie by @vrplays | Stardance
Devlogs:
Magpie - The Start Hello once again! This is the fifth project I’ve started working on in Stardance, and what I consider my second “grand” project. My idea for Magpie is pretty big; it’s a keyboard with no physical keys; everything is on a single display. The display itself is touchscreen, and underneath are motors that vibrate to simulate the feel of a click. There will also be speakers so that each click can sound like a real one too, further making the experience feel better. In addition to also being a keyboard, I have the plan to also allow for different layouts, like different keyboard inputs, a drawing tablet, or maybe even audio plugins! Right now, there really isn’t much to say about what’s in the project right now. I started working on the software part of it. Right now, its a Qt-based application that only shows a few keys that show a simple animation when clicked. My plan is to have the keyboard itself act as some sort of mini-computer, with everything being run on a Raspberry Pi. What do you guys think?...
|
1792792352.330637
|
1793397152.330637
|
|
40019
|
WarioWare Game by @vro | Stardance
|
vro
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0
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0.0
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0
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[]
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[]
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Title: WarioWare Game by @vro | Stardance
|
1793353859.2835858
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1793958659.2835858
|
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16306
|
Untitled project by @vrishti_patidar_13 | Stardanc Untitled project by @vrishti_patidar_13 | Stardance...
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vrishti_patidar_13
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0
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0
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[]
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[]
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Title: Untitled project by @vrishti_patidar_13 | S Title: Untitled project by @vrishti_patidar_13 | Stardance...
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1793278351.8357198
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1793883151.8357198
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21454
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Untitled by @vrishti_patidar_13 | Stardance
|
vrishti_patidar_13
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0
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0.0
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0
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[]
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[]
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Title: Untitled by @vrishti_patidar_13 | Stardance
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1793195309.970662
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14067
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My very own WebOS by @vrishitha_siv | Stardance
|
vrishitha_siv
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0
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0.0
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0
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[]
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[]
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Title: My very own WebOS by @vrishitha_siv | Stard Title: My very own WebOS by @vrishitha_siv | Stardance...
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1792673491.6982417
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1793278291.6982417
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20443
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My very own WebOS by @vrishi | Stardance
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vrishi
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0
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0.0
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0
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[]
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[]
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Title: My very own WebOS by @vrishi | Stardance
|
1792918435.1015224
|
1793782435.1015224
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