u/Mlnchlc

Hello everyone! 

I'd like to share another n8n project I built: a personal AI assistant for Telegram.

What Makes It Different

• Persistent memory. The assistant remembers your preferences across conversations using a vector store. For example, if you tell it you like burgers, it'll remember that in future chats.
• Google Workspace integration. It can interact with Google Tasks, Google Calendar, and Gmail to help manage your daily workflow.
• Memory controls.
  • /new starts a new conversation by clearing the current chat history while keeping your saved preferences.
  • /clear permanently deletes all stored preferences without affecting the current conversation.

The idea was to create an AI assistant that combines long-term memory with everyday productivity tools. By remembering user preferences and integrating with Google services, conversations become more personalized and practical over time.

I'd really appreciate any feedback or suggestions for improvements. This project will be part of my portfolio.

If you're looking to automate your own workflows or business processes, feel free to reach out:
https://zhrssh.github.io/contact/

Hello! I just want to share a project I've been working on: an AI chatbot for Facebook Messenger.

Most AI chatbots search for information once and immediately reply. If they can't find the right information, they often guess, which can lead to inaccurate answers.

I wanted to build something more reliable.

Here's how it works:

• It understands what the customer is asking.
• It remembers previous messages so conversations feel natural.
• It searches your knowledge base for the most relevant information.
• If the question is complex, it breaks it into smaller parts to find better answers.
• It generates a response based only on the information it found.
• Before sending the reply, it checks whether the answer is actually supported by the available information.
• If it's not confident, it either tries again or asks the customer for more details instead of making something up.

The goal is simple: provide accurate, consistent responses while reducing the time spent answering repetitive questions.

This was a fun project to build, and there's still plenty of room to improve the bot.

If you're looking to have a similar setup, feel free to reach out to me here: https://zhrssh.github.io/contact/

Hello everyone!

I'd like to share a project I built for our church.

Every week, we receive a PDF containing the songs for the upcoming service. Someone then has to manually copy, split, and format each song into ProPresenter. The process was repetitive, time-consuming, and often resulted in formatting inconsistencies.

To solve this, I built a workflow that automates most of the process.

What it does:

• Accepts PDF or TXT lyric files
• Uses AI to identify verses, choruses, bridges, and other song sections
• Splits lyrics into presentation-friendly slides (typically 2-3 lines per slide)
• Generates a ZIP file containing ProPresenter-compatible .txt files that can be imported directly

Current limitation:

• Users must choose whether they're uploading:
  • Multiple files containing one song per file, or
  • A single PDF containing one song per page

Even with this limitation, it has saved us a significant amount of time compared to formatting every song manually before each service.

I'd love to hear any suggestions or feedback, especially from people who use ProPresenter or other church presentation software.

More about the project:
https://zhrssh.github.io/projects/propresenter-lyrics-formatter/

GitHub:
https://github.com/zhrssh/n8n-propresenter-lyrics-formatter

Hello everyone!

I built a simple AI agent that helps me find n8n-related Reddit posts where people are asking for help or need assistance.

There are two workflows involved:

Workflow 1

• A scheduled trigger runs an Apify actor to scrape recent Reddit posts from selected n8n communities.
• The scraped posts are then embedded and stored in a vector database (I'm using PostgreSQL with pgvector).

Workflow 2

• A Telegram Trigger listens for new messages from a specific chat.
• The message is passed to an AI agent with access to the vector store.
• The AI agent retrieves the most relevant Reddit posts using semantic search and sends the results back to me via Telegram.

The AI agent is powered by Gemini Flash 3.1 Lite because it has a high limit for free tiers.

This project gave me a much better understanding of how Retrieval-Augmented Generation (RAG) works and why it's so useful. Instead of relying only on the LLM's built-in knowledge, the model retrieves semantically similar posts from the vector store, giving it relevant context before generating a response.

GitHub: https://github.com/zhrssh/n8n-reddit-rag.git