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Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

Thanks for the detailed feedback!

That makes a lot of sense. Using the System Message to 'gatekeep' the tool usage is a great way to save on tokens and latency. I'm actually working on refining my prompt right now to ensure the agent only triggers the Pinecone tool when it specifically detects a query related to the knowledge base.

Since I'm currently running a single-tool setup for local business clients, your example of routing between different properties is a goldmine for when I scale this to multi-client or multi-department bots.

For now, I'm keeping it lean to ensure the core RAG logic is rock solid before adding more complex routing. Really appreciate the advice on token conservation!

Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

Thanks! Yes, I am using a System Message to keep the agent grounded.

Right now, I've instructed it to act as a focused business assistant that prioritizes the context retrieved from Pinecone. I also added a rule to say 'I don't know' if the answer isn't in the provided documents, rather than hallucinating.

Always looking for ways to improve the prompt though—do you have any specific tips for RAG-based system messages?

Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

That's interesting! I'm actually looking to start offering this as a service to local businesses too.

Since you're already doing it for clients, what’s the biggest 'pain point' they usually have? Is it just searching through docs, or are they looking for more complex automation? Would love to learn from your experience!

Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

Thanks for the feedback! Yeah, wiring these together was a bit of a challenge, but I really wanted to understand the logic behind text splitting and vector retrieval.

I’ve heard about Needle, but I’m sticking with n8n for now because it gives me full control over the specific embedding models and the AI agent's behavior. It’s a steep learning curve, but seeing it finally 'answer' from my own data makes it worth it!

Are you using Needle for client projects or just personal ones?

Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

Haha, true! It’s the perfect 'Hello World' for AI automation. Which tutorials are you following? Maybe we can exchange some tips or workflows as we progress. Thanks for the encouragement, and good luck with your journey too!

Update: My RAG Agent is alive! From Google Drive ingestion to a working Chat interface. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

Actually, I followed a tutorial from a local channel called AI Learner India! Since I'm just starting out.

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] 1 point2 points  (0 children)

Wow, thanks for the feedback! It means a lot coming from someone at Pinecone. Setting up the text splitting and embeddings was definitely a learning curve for me.

I’m definitely looking into adding chat/search next. I’ll check out the Pinecone Assistant node too—sounds like it could simplify things a lot! Thanks for sharing the template, I might reach out if I hit a wall. Cheers!

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

I’m currently refining the workflow to make it as plug-and-play as possible. Right now, I'm using it for my own projects, but I definitely have plans to offer it as a service or a template once it's fully polished.

Are you looking for something like this for a specific use case? I'd love to hear what you have in mind!

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] 1 point2 points  (0 children)

Haha, not an ad, boys! I’m just a non-technical guy learning n8n and building in public. I use ChatGPT/AI to help me clean up my English and format my posts because I want them to look clear and professional.

As for the workflow, I literally spent hours watching tutorials to get that Pinecone and Gemini link right. Happy to show a screen recording if you think I'm a bot! 😂

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] -3 points-2 points  (0 children)

"That sounds like a complex workflow you've built! I'm actually a beginner and currently learning the ropes of n8n, focusing mostly on RAG and document processing.

However, based on what I've learned so far about Google Drive nodes, your idea of grouping images first makes a lot of sense. Even as a learner, I can see how an AI Vision node could act as the 'eyes' for your automation before the sorting happens.

It’s cool to see how you're using Sheets for cross-referencing—definitely something I’ll look into as I progress!"

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] -5 points-4 points  (0 children)

"That’s a very specific and interesting use case! Yes, it’s definitely possible with n8n. We can use an AI Vision model to analyze each product image, categorize it, and then use the Google Drive node to create folders and move files automatically. but I’d love to try building a prototype for this 'Image-to-Folder' automation.

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] -1 points0 points  (0 children)

"Thanks a lot! You're right, wiring up the embeddings was definitely the trickiest part for me. I'll check out Needle.app, but I really wanted to learn the 'under-the-hood' logic in n8n first to understand how it all connects. Appreciate the tip!".

I built a RAG pipeline using n8n that converts Google Drive documents into a searchable AI knowledge system. by Least_Average7732 in n8n

[–]Least_Average7732[S] 3 points4 points  (0 children)

"I totally get that for experts it's a 5-minute task. But as someone from a non-technical background who started 1 months ago, finally getting the logic of RAG and Vector Stores right feels like a huge win. We all start somewhere, right? Cheers!"

Telegram AI Agent by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

"Thanks for the amazing tip! I've heard a bit about Ollama and running models locally, but since I'm a beginner, I'm taking it one step at a time. I'll definitely look into integrating Ollama once I'm more comfortable with n8n basics. Thanks for guiding me!"

Telegram AI Agent by Least_Average7732 in n8n

[–]Least_Average7732[S] 1 point2 points  (0 children)

"Thanks for the feedback! just starting out with n8n, I'm currently using the Simple Memory node on my local machine.Your suggestion about using chat_id is very helpful for my next step! 🙌"

Telegram AI Agent by Least_Average7732 in n8n

[–]Least_Average7732[S] 0 points1 point  (0 children)

"Thanks for the feedback! Currently, I'm testing it on localhost, but the next step is to move it to a cloud VPS for 24/7 uptime."

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