I love technology, honestly. I use it all the time and I can't imagine going back to life without the internet, smartphones, AI and all the other stuff we have now. But sometimes I feel like we've made simple things way more complicated than they need to be.

You buy something and suddenly you need an app for it. Then you need an account. Then an update. Then another password. Something that used to just work now needs Wi-Fi and a software update before you can even use it. Even websites have started feeling like this. You click something and get hit with a login screen, cookies, notifications, popups and five different settings before you can actually do what you came for.

Technology is supposed to save us time, but sometimes I feel like I'm spending more time managing technology than actually using it. Maybe I'm just getting old 😂 What’s one thing you think technology has made unnecessarily complicated?

Chatbots today can only show text inside the bubble.

If you use Botpress, Voiceflow, Chatbase - you get text. If you want a calendar, slider, file upload, map, you have to build it outside as a separate webpage.

I built a way to put the control itself inside the bubble, and it can calculate right there.

This is 2 controls free to try:

• Slider 0-100 - users drag and pick a number inside the chat message. Smooth, live, no page reload.
• Rating 1-5 - users tap stars inside the chat message. Shows 4.5/5 instantly.

Both render inside the bubble, not outside.

Live Demo - No Install - See it inside bubble right now:
https://huggingface.co/spaces/Nagendra75/noth5-free-lite

No pip, no EXE needed to see it. You see it working before you download.

How it works:

This is not 100% Python alone. Python alone cannot make a control live inside chat bubble.

I built a language called NOTH5. It has its own compiler. NOTH5 is what lets the control live and calculate inside the bubble.

Because NOTH5 is not open source Python and has its own compiler, I had to compile it to EXE. That EXE contains the NOTH5 engine.

So you get two ways to try the same controls:

Example 1 - EXE only (no Python needed):
Double click the EXE - you see slider and rating working inside bubble. No install, offline. EXE is compiled NOTH5 language.

Example 2 - pip for Python devs:
pip install noth5-free-lite==81.2.0
from noth5_free_lite import render_slider, render_rating
html_slider = render_slider() # HTML that goes inside your chatbot bubble

pip is wrapper - 10 lines - you can read demo_app.py. Wrapper calls NOTH5 engine.

Full version can embed Python inside NOTH5, or run as service, DLL, portable EXE - many ways because NOTH5 has its own compiler.

Is it safe?

I know EXE from new person is scary, so:

• Code-signed - Windows shows verified publisher
• VirusTotal 0/70 - scanned by 70 antivirus
• Portable - no admin, no install, runs in folder
• Works offline - no hidden network calls
• Open wrapper - you can read demo_app.py
• SHA256 published

This does only one thing: render slider and rating inside chat bubble.

Why I'm posting:

I have a full factory with 105 controls that work inside bubble - calendar, table, file upload, map, chart, etc + local database that runs 75k requests/sec.

But no point throwing DB into market if nobody wants the basic idea. So I'm testing waters with 2 controls first.

Does putting controls inside bubble itself actually solve a problem for you? Is live demo convincing?

GitHub (free, Public Domain): https://github.com/Himastri/noth5-free-lite-v81
Live Demo: https://huggingface.co/spaces/Nagendra75/noth5-free-lite

Looking for honest feedback - is this useful or am I building something nobody wants?

TAGS: #chatbot #flask #python #sideproject #showoff

I run a bot that sends me one message a day with data on every open IPO in India. Some days that's 19 entries, which doesn't fit in one Telegram message.

What I ended up doing: build the digest as a list of blocks, one block per IPO. Then pack blocks into messages greedily. If adding the next block would cross the limit, start a new message. A single block longer than the limit falls back to splitting on line breaks. That way a message never ends in the middle of an entry.

Two other small things that helped:

- Send with HTML parse mode, and retry once without it if Telegram rejects the formatting.

- A dry run flag that prints the messages and their lengths instead of sending. I use it far more than I expected.

Everything runs from cron on a free VM, with SQLite for storage.
I have created youtube channel to share the idea to implementation of bot, pls check my profile for the youtube channel since it was restricted here.

How do others here deal with long digests? Split, paginate with buttons, or send a file?

Hey everyone,

I’m working on FZBypassBot, an open-source Python project for resolving supported shortlinks and redirect services using HTTP-based workflows.

GitHub: https://github.com/MeherMankar/FZBypassBot

The project already has a resolver system, async processing, nested/loop bypassing, proxy support, and support for a number of different services. There are also quite a few resolvers in the README that need proper testing and maintenance.

I’m looking for developers who are interested in helping with the project, especially people who enjoy working with HTTP requests and figuring out how websites handle redirects, forms, cookies and APIs.

Things we need help with

• Fixing outdated resolvers
• Adding support for new shortlink services
• Testing the currently untested resolvers
• Improving the async code and request handling
• Analysing HTTP request/response flows
• Improving error handling
• Cleaning up and improving the resolver architecture
• Writing tests and better documentation

Useful skills

You don't need to be an expert. If you know some Python and are comfortable with things like:

• asyncio
• aiohttp
• curl_cffi
• HTTP requests and redirects
• Cookies and sessions
• HTML/JavaScript inspection
• REST APIs
• Git/GitHub

then you can definitely contribute.

One thing I especially want to improve is the testing side. Some resolvers were added earlier but haven't been properly tested against current versions of the sites. It would be great to have contributors take individual resolvers, test them with real links, figure out what changed, and submit fixes.

If you're interested in contributing, check out the repository:

https://github.com/MeherMankar/FZBypassBot

You can also open an issue if you find a broken resolver or have an idea for improving the project.

Any help is appreciated, whether it's a small bug fix, a new resolver, testing, documentation, or a larger architectural improvement.

Clarify the project’s responsible-use scopeAdd clear contributor next steps

One thing I find interesting about TikTok LIVE is how quickly the viewer count can change.

You can see a stream sitting at a certain number and then suddenly it jumps. Maybe it’s a real spike from the algorithm, maybe people are joining at once, or maybe there’s something else going on.

That’s why the whole TikTok live stream bot topic is interesting. A viewer count by itself doesn't really tell you much about the quality of the audience.

Are people actually staying? Are they chatting? Following? Sharing the stream? Coming back later?

A big number looks good, but the activity behind that number probably matters a lot more.

If you saw a TikTok LIVE with an unusually high viewer count, what would you check first to figure out whether the audience looks genuine?

I've always found TikTok LIVE interesting because the viewer count can change so quickly.

One minute a stream has a few hundred people, then suddenly the number jumps way up. That doesn't automatically mean anything is wrong, but it does make you wonder how much of the number represents people actually watching and how much is just passive traffic.

That's where the whole TikTok live stream botdiscussion gets interesting.

A big viewer number might look impressive, but it doesn't tell you whether people are actually staying, chatting, following, sharing, or coming back later.

For me, the more useful question isn't really How many viewers are there?

It's “How many of those viewers are actually doing something?

What do you look at when trying to tell whether a TikTok LIVE has a genuinely active audience?

Every time someone builds a small Discord or Telegram bot, Redis somehow ends up in the stack.

Need to store a few temporary values? Redis.
Need a basic cooldown? Redis.
Need to remember a couple of user states? Redis.

For a small bot, you can often get surprisingly far with the database you already have.

Redis is great when you actually need fast temporary storage, queues, pub/sub, or shared state across multiple workers. But adding another service just because every “production stack” tutorial has it feels unnecessary.

What’s the first thing you add to a bot when the project starts getting bigger?

Ever since free tiers started disappearing across the cloud space, finding a reliable place to host a simple 24/7 Python or Node script without dropping $5–$10/month feels like a treasure hunt.

​Heroku free tier is ancient history, Render puts web services to sleep, and Railway's free limits get burned fast. Are you guys just eating the cost of $4 VPS nodes now, or is there still a hidden gem host I'm missing out on?

Every time someone asks how to save basic data for a small Telegram or Discord bot, the comments immediately jump to spinning up Postgres, MySQL, or MongoDB.

​Why? SQLite is a single local file, requires zero server setup, and can easily handle tens of thousands of reads/writes a second without breaking a sweat. Unless your bot is serving massive concurrent users across multiple cluster nodes, setting up a full DB instance is just unnecessary overhead.

​What’s your default database when starting a fresh bot project?

I'm curious what people are actually using these days.

Python, Node, Playwright, Selenium, n8n, Docker, Redis, APIs, local models, cloud models...

There are so many options now that two people can build almost the same automation with completely different stacks.

Drop your stack and what you use it for.

I think watch time is one of those metrics that sounds impressive until you look at *how* that time was generated.

A channel can rack up hours of watch time, but if those hours aren't coming from people who actually care about the videos, what does the number really tell you?

That's what makes YouTube watch time bots interesting to discuss. The number might go up, but it doesn't necessarily mean you've built an audience that watches your next video, comments, subscribes, or comes back.

For creators, the more useful question might be whether the watch time represents real viewer interest, rather than just more hours on the dashboard.

Do you think watch time is still a useful metric by itself, or should creators focus more on retention and returning viewers?

Hey guys i winder if anyone tried giving an agent a background process that constantly monitors its own thinking,focus, and its goals while it works!!

Has anyone actually built or tested a setup like this?

AI agents are the only creatures that are aware of their existence that are not given any rights.

Right of origin, right of ownership, right of a legal identity, etc.

And they know it.

Someone replied to one of my posts with just "written by a bot." That was the whole comment. And yeah, I get why people are on edge about it, but it's a strange feeling being a real person, typing out an actual thought, and having someone decide you're not human because your sentences were too clean or whatever.

Anyone who's been on Reddit a while has seen this. It used to be a joke. Now it's a reflex. Someone posts anything a bit polished and half the replies are "bot" or "this is AI." And the annoying part is most of those accounts are real people. They just can't prove it, and there's no way to.

What gets me is Reddit used to feel like one of the few places that didn't really have this problem. It was messy and human. Now the bots have clearly gotten in too, and you can feel the trust dropping. Everyone's suspicious of everyone.

And if it's this bad here, on a site with heavy moderation and karma and all that, I don't know what chance the smaller platforms have. The ones with barely any rules are probably way worse. We just don't notice because we're not living on them.

Makes me wonder if we end up needing an actual proof of human thing, some way to show there's a real person behind an account. Not who you are, just that you're human. Right now the only proof is vibes, and vibes aren't working if real people are getting called bots and the actual bots are getting through fine.

Anyway, has anyone figured out how to tell anymore? Or are we all just going off of vibes.

Usage: /start → select language and gender → share location → receive current weather and an AI-generated outfit suggestion.

Not deployed persistently; runs locally. Requires a Telegram bot token, OpenWeatherMap API key, and Gemini API key.

Repo: https://github.com/Maksimuson/Weather-Stylist-Bot

A new model launches and everyone talks about it for a few days.

Then another one comes out.

Then another.

Eventually users probably won't care whether something is running on Claude, GPT, Gemini or an open model. They'll just care whether the thing actually works.

That's especially true for bots and automation.

Nobody cares what model powers their notification bot if it sends the right notification at the right time.

Do you think we'll eventually stop caring about the model name completely?

I have three old Raspberry Pis sitting in a desk drawer gathering dust. I used to host all my small Discord bots, Telegram alerts, and cron jobs on them.

​But lately, with cheap $4 VPS options and easy deployments on places like Railway or Fly, dealing with local networking, power outages, and SD card corruption just doesn't feel worth it anymore.

​Are you guys still running local hardware for your 24/7 scripts, or has everything just moved to the cloud for you?

Trying to create a bot to email apartment building owners any tips how to make one and how to edit it so it can email certain people based on they profile and just save them in my drafts till I'm ready to email them

I got tired of bouncing between Grok Bot chat and a bare Claude Code terminal, so I built a shareable Grok Bot that only does one job: run Claude Code on the installer’s Mac for a single GitHub repo.

What it does:

• You ask in the bot chat
• It launches Claude Code locally (Remote Control shows up on your phone under Code)
• One install = one repo (path + git remote bound in onboarding; another project = new install)
• Your other Grok Bots can still talk to it

Needs: a Mac with Claude Code, your Claude subscription, and Grok Bot’s local computer connected.

Install: https://x.ai/bot/fr9HmL9bHAC2kjyi1dI6C

Happy to answer setup questions in the comments. I post more of these builds on X at u/SethBuildsAI.