@L0stsky

So I Spent like 2 Hours Getting a basic Simulation to work, then I Binged like 2-3 YT vids about Anamoly detection models and made a Pretty small one to train.

After like 3-4 Hours of training, the Model didnt Make any progress its still a Baseline random Model. Now Since this was a very small model which had to somehow find anamolies in a Time Series Data that too in Multiple variables I just figured its way too small.

So Heres my Plan:
Complete the Entire Simulation code.
Binge more Videos
Build and train a Better Model.
Also in the Future Make a Gui to see the Simulation Interactively.

I Don’t have much to show rn except some cool lil pic I Took of the rain.

So I noticed that I had put the AI usage to None in the beginning but later i used it to find some bugs etc and make the startup scripts so heres my AI usage if you wanna know

So I Broke it Again , the Models were Broken So i Just Updated the Models and Increased The Number of API Tries to 15

So I Found out that One of the Model I was Using Was Not Capable of the Task 🥀🥀, So I Updated the code to Use New Capable Models and also Retry If the Model Could not Extract the Data. And Now I gotta Wait Till Tommorrow Till I can ReMake the Windows Exe File (I use Linux soooo) 😭😭😭

So I was Finally Able to get Pyrunner Working and Make the Godamm executables for Linux and Windows.
Well Finally after 22 Hours of Working and a dead Pen Drive (Idk why tf its Firmware Got erased) I finally Completed Cue

Virtual ENV Data Extraction Stage Complete

So I Spent 2 Hours Collecting Data Regarding the Indian Climate from the IMD website and Used AI to Compile it Into a Useable Form.

So Basically In a Nutshell here’s what Im Planning :
1) I collect the Data regarding the Rain, and Human Water Usage W.R.T to India (Could have been any country but I thought India Would Be easier to verify cuz I live in India). –> This is Done.
2) I use this Data To Make a Virtual Env which Simulate the Water Entering the Drainage Pipes. Basically the Data Collected is Used to Realistically Generate a Day and How Much chances that Rain can occur and how much rain and How much water Used by Humans etc. in that day
3) Since the activity of the Env Is based on The same Background Info, the Anomaly Detection Model learns How the Water Level in the Drain Pipe Works in the env. Then I introduce a Blockage in Pipes, Then Use this to Test the Model.

Also, If you have read this far, thank you 😉

DevLog_6
So My dum Brain found out that Python Envs cannot just be “Packaged “ and Used on another Computer Sooooo I Updated the Startup Scripts to Make One On startup.
Also IDK why but my dummahh tried to Retrain a local 2B pretrained Model but after getting 1 Epoch in 2 HOURS I just Lost Hope and Dumped the Idea.

Virtual ENV Data Extraction Stage Complete

So I Spent 2 Hours Collecting Data Regarding the Indian Climate from the IMD website and Used AI to Compile it Into a Useable Form.

So Basically In a Nutshell here’s what Im Planning :
1) I collect the Data regarding the Rain, and Human Water Usage W.R.T to India (Could have been any country but I thought India Would Be easier to verify cuz I live in India). –> This is Done.
2) I use this Data To Make a Virtual Env which Simulate the Water Entering the Drainage Pipes. Basically the Data Collected is Used to Realistically Generate a Day and How Much chances that Rain can occur and how much rain and How much water Used by Humans etc. in that day
3) Since the activity of the Env Is based on The same Background Info, the Anomaly Detection Model learns How the Water Level in the Drain Pipe Works in the env. Then I introduce a Blockage in Pipes, Then Use this to Test the Model.

Also, If you have read this far, thank you 😉

Y’all Ready for This??
So here is what Sentinel is about :

So basically as you know we have drainage pipes which with time develop blockages due to various reasons. These blockages right now have NO way of being detected until they cause waterlogging and cause infrastructural damage and are costly to repair. But these blockages are actually NOT UNDETECTABLE.
So here is the thing -> when the blockages start forming, the water level in the drains acts abnormally. These abnormalities can be detected by using an Anomaly Detection Model .So my entire project is based on this idea.

Here is a 3D animation I spent way too much time on.

Y’all Ready for This??
So here is what Sentinel is about :

So basically as you know we have drainage pipes which with time develop blockages due to various reasons. These blockages right now have NO way of being detected until they cause waterlogging and cause infrastructural damage and are costly to repair. But these blockages are actually NOT UNDETECTABLE.
So here is the thing -> when the blockages start forming, the water level in the drains acts abnormally. These abnormalities can be detected by using an Anomaly Detection Model .So my entire project is based on this idea.

Here is a 3D animation I spent way too much time on.

DevLog_6
So My dum Brain found out that Python Envs cannot just be “Packaged “ and Used on another Computer Sooooo I Updated the Startup Scripts to Make One On startup.
Also IDK why but my dummahh tried to Retrain a local 2B pretrained Model but after getting 1 Epoch in 2 HOURS I just Lost Hope and Dumped the Idea.

Devlog 5:
SO If you don’t Remember, Im Working on CUE -> A Easy af To use Tool to Make Easy to Follow Guides which Is simple as clicking to Run a Script and Then Doing Whatever Task You want. The Script AutoMatically saves Your actions and After You are done, these are Compiled into a Text Based or Both text and Image Based Guide of Your Chosing!!!

Here’s What Im Working On:
Made a Single Click Startup Script.
Added a API key Verification.
So I Fixed Some Major Cross Platform Code Errors.
Packaged a Python Env With the Things for Ease of Use.
Tried and Tested On Linux and Windows Thought I couldnt On Mac Since I dont Use that.

Now I plan to Use the Tool to Make Guides Regarding How to use it!!!!

DevLog_4:

Finally Got the Fricking Images in the Guide to Work and The Sudo Permission to Work Correctly.

First I tried to Embed them Directly But that didnt Work so i Just Put the Images Along with the Guide and Used Paths to render them.

Then I made Improvements to my Screenshot and the Backend Code Like Gracefully exiting Rathar then the Forced Exit I was Doing Earlier.

Added a “NOTE to the AI” Feature and Introduced a Smarter Model for Compiling the Data into a Guide.

Now I plan to Use Pyinstaller to Make it a Executable and Make the Model Format the Guide a Little More Beautifully.

DevLog_3

I have Attached a Demo Video of the Current Project.
In the Video You Can see that the Output File is Not Properly Formatted because I opened it in Notepad But in The Actual Docs Viewer it Looks Fine. Also the |Image| Tags is a Beta Feature and Is not Fully Implemented.
Also If you are Wondering, it Took the Script like 2 Minutes to Process the Screenshots (I have Cropped the Video).

So I Finally Completed The Scripts for Running the Project.
I made 2 scripts -> For the GUI version and the CLI version.
I was able to make a minimal GUI Setup for the Project though its still a little buggy which I’ll Fix Later.

Now I am Working on Fixing Some Issues with the API, Fully Implementing the images in the Guide Feature and Trying to turn it into a Application Rather than running it via Scripts.

DevLog_2
So I Finally Was Able to Complete the AI Backend Part of the Project and let me tell you - IT WAS A NIGHTMARE.
For the First 4 Hours I Tried to get a Local VLM to Work but Due to my Low end Pc it wouldnt Work so I just Gave up and Switched to Free Openrouter Models.

So Here is What I’ve Made :
I Made the Python File Which would Load in all the Screenshots from the Main Script.
These Screenshots are then sent to an API which Describes What the User is Doing by Using the Cursor Locations.
All these Observations are then Compiled by a Smarter Model To make a Comprehensive Guide.

Now I plan to Try to Make a Simplistic IN-Python UI and a Script to Do all the Tasks and Package it.

I’m building CUE—an AI-powered guide generator to solve the headache of manually making step-by-step instructions. The goal is to have a seamless tool that just works across all OSs.

What’s done so far
Finished the main code and the specific OS capture handlers.

Every time you click anywhere on the screen, it automatically grabs a screenshot and dumps it into a local folder.

The Wayland Pain: Wayland’s OS security made capturing clicks a nightmare compared to every other platform. I basically had to put Gemini’s black cap on to help me hack around Wayland security and get those screen captures working.

Integrated An ACTUAL Database Storage Using the Upstash API.
Added a Quiz Feature, It uses the Gemini API Key to which the AI responds to in a Format which is then Unpacked and Filled in Modular CodeBlocks on run.
Made Persistent InBrowser Memory -> Your Name or Bingo Game Dont get Lost when you refresh.

Finally Got the Website Hosted on Vercel .
After some Not so critical Thinking i figured i might as well make some other fun games because why not.

So I guess more Games after Shipping!