Скачать или смотреть How to Build a Local AI Agent With n8n (NO CODE!)

Discover how to build a powerful AI agent that runs completely on your local machine in this step-by-step tutorial. Learn to combine N8N's workflow automation with Ollama's LLM capabilities and PostgreSQL's vector database features to create a responsive assistant that can access your documents, maintain conversation history, and retrieve real-time information from the web.

This video demonstrates a cost-effective solution requiring no paid API services or cloud subscriptions. You'll see how to properly configure Ollama with two essential models, set up Docker with PostgreSQL for vector search, and orchestrate everything through N8N's intuitive interface.

Perfect for developers, AI enthusiasts, and business users looking to implement private AI solutions, this tutorial covers common troubleshooting issues and provides simplified alternatives to more complex setups. Watch as your agent retrieves information from uploaded documents, maintains context across conversations, and delivers accurate responses using locally-run large language models.

If you're interested in self-hosted AI tools that respect your privacy while delivering powerful functionality, this comprehensive guide walks you through building an extensible foundation you can customize for your specific needs.

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POSTGRES DOCKER COMMAND:
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docker run --name pgvector-container -e POSTGRES_USER=myuser -e POSTGRES_PASSWORD=mypassword -e POSTGRES_DB=mydatabase -p 5432:5432 -d ankane/pgvector

🕒 TIMESTAMPS:
00:00 - Intro
00:33 - Demo
02:29 - Note on Starter Kit
02:55 - Ollama Setup
04:31 - Postgres Setup
06:20 - n8n Setup
07:01 - Create AI Agent
08:49 - Assign LLM (Ollama Node)
10:01 - Chat Memory (Postgres)
11:44 - Postgres Chat Memory
13:13 - Adding Tools
13:42 - Adding RAG (Postgres)
15:13 - Using OpenAI Node instead
16:24 - Housekeeping
17:02 - Add Web Search
17:59 - Add Docs to Vector DB

#n8n #aiagents #ollama