🤖 Building Your Own AI Assistant - Part 3: RAG in n8n - Working with Documents & Vector Stores

In this comprehensive guide, we explore how to enhance your AI assistant by incorporating document processing and vector stores. Learn how to make your AI system smarter by providing it with context from various document sources like PDFs, wikis, and text files.

You can get the workflow here:

🚀I have also added a retrieval variant for an AI Agent on the workflow. Please make sure to give a good description for the Vector DB tool to the agent so it knows when and how to use it.

You can just copy the JSON code to the clipboard and paste it into n8n.

Please also check out @n8n-io for more videos.

📖 Chapters:
00:00 Introduction
00:40 Understanding Unstructured Data
03:30 Vector Stores Explained
06:10 Working with Vector Embeddings
08:30 Building the Document Processing Workflow
14:10 Understanding Embedding Models
16:30 Text Splitting Techniques
22:30 Creating a Chat Workflow
25:40 Practical Implementation
29:00 Conclusion & Next Steps

🔧 What You'll Learn in This Video:
• How to process and store unstructured data for AI consumption
• Understanding vector databases and similarity search
• Setting up document processing workflows in n8n
• Implementing efficient text splitting and embedding strategies
• Creating context-aware chat systems

🔗 Useful Links:

🛠️ Tools & Technologies Used:
• n8n
• Ollama
• Quadrant Vector Store
• Nomic Embed Text Model
• Docker

💡 Get More From This Tutorial:
• Follow our blog for more AI automation tutorials

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💭 Share Your Thoughts:
What kind of AI assistant would you like to build? Let us know in the comments below!

❓ Have questions? Drop them in the comments below!

#AIAutomation #VectorDatabase #MachineLearning #n8n #AITutorial

[mtamre]

Read this comment to get the full workflow🚀I have also added a retrieval variant for an AI Agent. Please make sure to give a good description for the Vector DB tool to the agent so it knows when and how to use it.

You can get the workflow here:

You can just copy the JSON code to the clipboard and paste it into n8n.

[craig.barker]

Just the information I needed - thanks!

[DreamsAPI]

Love you clear explanation and actions

[RabeeHanzla-vcdr]

This is just Brilliant!!
it would be amazing if you could also share the code snippets as well

[craig.barker]

Thanks again for the series - very helpful. Just a question regarding chat memory - is it possible to add postgres chat memory to a question and answer chain? Would we have to connect an AI Agent to the workflow to handle that?