Serverless projects on Yandex Cloud
Serverless technologies allow you to launch projects without a separate server, which means almost free of charge instead of paying for hosting.
I made a Telegram bot on Yandex Cloud with their built-in database. The bot is holding a quiz about the platform's capabilities. It still works! Try it yourself: @ycloud_quiz_bot
ChatGPT API
This technology allows applications to interact with ChatGPT: send requests and receive responses.
Now I can add ChatGPT capabilities to my projects:
• Create smart bots that understand complex queries.
• Make assistants that analyze text and generate ideas.
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Figured out cloud databases
A task appeared in the new bot (which is currently under development) to link data with data from the old bot. I settled on a service with cloud Postgres, since I studied it already at the university. I struggled a bit with the migration Sqlite -> Postgres, but now everything works.
A task appeared in the new bot (which is currently under development) to link data with data from the old bot. I settled on a service with cloud Postgres, since I studied it already at the university. I struggled a bit with the migration Sqlite -> Postgres, but now everything works.
Another new bot @evogenesis_bot is an AI assistant with GPT, which is still in beta. The bot can chat, remembering the history of correspondence, generate texts, pictures and a separate function of a personal trainer, which helps to select a diet and training according to your physical parameters and goals, as well as track the dynamics of indicators every month.
🔍 Neuro-Lawyer based on RAG and YandexGPT is my new project, in which I implemented an intelligent assistant for housing law in Russia.
It understands questions, finds articles of the Housing Code of the Russian Federation and gives discreet, legally accurate answers.
I used LlamaIndex, YandexGPT, a query reformulation system, filtering and tracing through Phoenix. Everything works right in Google Colab.
🐱 Repository with code and examples: github.com/SC1DR-OFFICIAL/Real-Estate-Legal-Advisor-AI
It understands questions, finds articles of the Housing Code of the Russian Federation and gives discreet, legally accurate answers.
I used LlamaIndex, YandexGPT, a query reformulation system, filtering and tracing through Phoenix. Everything works right in Google Colab.
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🖼 Watermark Autoencoder AI: an autoencoder that reconstructs images distorted by watermarks.
The neural network is trained to detect overlaid text and reconstruct the original image.
I implemented synthetic watermark generation, 5+ augmentation techniques, and stepwise training with memory control — all adapted for Google Colab.
📊 Visual outputs include: watermarked input, prediction, original image, and noise map.
🐱 Repository with code and runnable example:
github.com/SC1DR-OFFICIAL/WatermarkAutoencoder-AI
The neural network is trained to detect overlaid text and reconstruct the original image.
I implemented synthetic watermark generation, 5+ augmentation techniques, and stepwise training with memory control — all adapted for Google Colab.
📊 Visual outputs include: watermarked input, prediction, original image, and noise map.
github.com/SC1DR-OFFICIAL/WatermarkAutoencoder-AI
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🏠 Cian Parser: my fork of the cianparser library to parse Cian listings.
I needed a Cian parser, found a great lib by lenarsaitov, but Cian blocked it on my side.
Had to dive into the code, tweak it, and now it works fine.
Feels nice — my first small step in open source.
🐱 Repo:
github.com/SC1DR-OFFICIAL/cianparser-with-headers
I needed a Cian parser, found a great lib by lenarsaitov, but Cian blocked it on my side.
Had to dive into the code, tweak it, and now it works fine.
Feels nice — my first small step in open source.
github.com/SC1DR-OFFICIAL/cianparser-with-headers
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👗 GAN-MNIST-Fashion: DCGAN for generating clothing images from Fashion‑MNIST.
Compared classic vs improved DCGAN: the classic trains faster, the improved captures finer details.
Implemented a custom GradientTape loop, added augmentations, and visualized loss dynamics.
📊 Results include epoch comparisons and generated samples.
🐱 Repo with code:
github.com/SC1DR-OFFICIAL/GAN-MNIST-Fashion
Compared classic vs improved DCGAN: the classic trains faster, the improved captures finer details.
Implemented a custom GradientTape loop, added augmentations, and visualized loss dynamics.
📊 Results include epoch comparisons and generated samples.
github.com/SC1DR-OFFICIAL/GAN-MNIST-Fashion
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💫 Telegram Stars Invoice Bot: issue invoices in Telegram Stars with a single command.
I often get orders from abroad and noticed that many clients find crypto payments inconvenient.
I looked for an alternative and found a perfect one — Telegram Stars, which are easy to buy right inside Telegram anywhere in the world.
But Stars (now) can’t be directly transferred to another person.
So I wrote a bot that lets you instantly issue an invoice to a client in Telegram Stars.
Thought this tool could be useful for others too, so I released the source code on GitHub under an open license.
🐱 GitHub repo:
https://github.com/SC1DR-OFFICIAL/TG-Star-Invoice-Bot
I often get orders from abroad and noticed that many clients find crypto payments inconvenient.
I looked for an alternative and found a perfect one — Telegram Stars, which are easy to buy right inside Telegram anywhere in the world.
But Stars (now) can’t be directly transferred to another person.
So I wrote a bot that lets you instantly issue an invoice to a client in Telegram Stars.
Thought this tool could be useful for others too, so I released the source code on GitHub under an open license.
https://github.com/SC1DR-OFFICIAL/TG-Star-Invoice-Bot
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https://github.com/SC1DR-OFFICIAL/Simple-RL-for-Atari-MsPacman
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🌪 The project also explores performance under uncertainty — when observations and actions are affected by noise
https://github.com/SC1DR-OFFICIAL/ppo-panda-uncertainty
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• Secure two-step authentication (API key + PIN)
• Support for OpenRouter and VseGPT keys
• Local storage of history and analytics
• Token and spending tracking
https://github.com/SC1DR-OFFICIAL/AIChatFlutter/tree/main
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I’d like to share a few highlights from the past week.
First of all, I finally completed the “Neural Network Developer” course. Over the past year, I invested more than 200 hours into it, and successfully passed the final assessment — a big and meaningful milestone for me.
Secondly, I took part in a hackathon for the first time, where we had to build a RAG system. Although we didn’t make it to the finals, my team still ranked 32nd out of 180 teams — a solid result for a first attempt. Most importantly, I met some great, intelligent people and significantly improved my understanding of RAG architectures.
Now that I have more free time, I’m planning to dive deeper into work and new projects!
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For one of my projects: a bot for selling real estate in Tashkent the customer asked to add auto-publishing of ads on OLX.
The task turned out to be more difficult than it seemed. OLX does not have an API for working with an account, so I had to use browser control. But OLX has protection against bots: it recognizes work on the server (no screen) and blocks.
I figured out how to bypass the protection and even created an AI to pass the captcha if it appears.
Now ads from the bot are automatically published on OLX without manual intervention.
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I build custom CRMs inside Telegram — with any functions you need, including AI (summaries, auto-tagging, lead scoring, etc.). For a real estate client I made a bot: client leads, exclusive listings with photos and listing IDs from the ads board, search by CRM or ad board ID, comments, and notifications to the team. No separate site, no Bitrix.
Want a CRM that fits your process and can use AI? I can do the same for you.
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For the past six months, I've been working primarily on large projects, including large commercial services, as well as research at the intersection of botany and artificial intelligence. I'm now approaching the final stages of each of them, and I've decided that writing about the intermediate stages wouldn't be as interesting, so I'll be covering them in detail soon.
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Bot link
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The bot is currently in open testing, and any potential issues will be debugged. There are also plans to expand the service by adding books, movies, and TV series, and to create a website.
Telegram Bot · Status · Support
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SC1DR
Firstly, downloading videos by timecode. If you enable this setting, you'll be prompted to select a timecode when downloading a long video. For example, you can select just a few minutes from a multi-hour video without waiting for it to download completely. Incidentally, this works not only with YouTube but also with other platforms with long videos. It's convenient for content creators.
Secondly, downloading posts from public Telegram channels and chats. Images, photos, documents, and text are extracted from posts,
Try: @CmdSaveBot
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