LLM Helpers: AI chat in Telegram

One neural network answers quickly, another reasons better, a third draws pictures. Juggling several accounts for that is a hassle. LLM Helpers brings several models into one mini app inside Telegram. 🤖

The project's motto is "AI for everyone," and it has its own community for questions and news.

Which model should answer your question

The description splits the choice into tiers, which makes sense: not every question needs the most powerful model.

• Fast model: short answers, rewriting text, simple questions. 🚀
• Mid-range model: heavier tasks like a letter, summary or plan.
• Most advanced model: tricky reasoning, calculations, code review. 🧠

The stronger the model, the slower it tends to be. Take the light one for quick lookups and switch to the heavy one for a hard task.

Pictures from a text description

The app includes an image generation model. You describe a scene in words and it draws the result. 🖼

The more specific you are, the better: style, colors, angle, mood. A bare "cat" gives a random result, while "ginger cat on a windowsill, watercolor, morning light" gets close to what you imagined.

A Chinese model in two versions

Besides the Western models, the app offers a Chinese neural network in both of its versions. It is handy if you want to compare answers to the same question.

Send one prompt to two models and see which reply is fuller. On different topics, different models often win.

Getting a good answer out of a neural network

1. Name a role: "you are an editor" or "you are a physics tutor".
2. Describe the task and the answer format: a list, a table, three paragraphs.
3. Add source data or an example.
4. Say what to fix if the first draft misses.

Where a neural network really saves time

These assistants do best with routine text work. Ask for a shorter email, headline options, a plain-language explanation of a term, or a weekend trip plan.

• Study: explanations with examples and quiz questions.
• Work: email drafts, meeting summaries, document templates.
• Code: reading an error and a sample function.
• Home: a weekly menu, a shopping list, gift ideas.

Always polish the result by hand: the network gives a base, not a finished product. ✍️

Privacy and accuracy to keep in mind

Neural networks sometimes state wrong facts with confidence. Check numbers, dates, cited sources and any medical or legal advice.

• Do not send passwords, card numbers or passport data.
• Do not upload other people's personal photos without consent.
• Save important answers yourself, since history may not be kept.

Check payment terms and request limits inside the app. If something is unclear, ask in the project community. 💬