Thanks to Microsoft for sponsoring this video! Submit your #CodingWithCopilot stories so I can review them! I'm excited to check out more!

Today I'll be showing you how to build local AI agents using Python. We'll be using Ollama, LangChain, and something called ChromaDB; to act as our vector search database. All of this will be local and free to run.

🎞 Video Resources 🎞
Code in this Video: https://github.com/techwithtim/LocalAIAgentWithRAG
Ollama Library: https://ollama.com/library
Download Ollama: https://ollama.com/
Virtual Environments Video: https://www.youtube.com/watch?v=Y21OR1OPC9A
Ollama Video: https://www.youtube.com/watch?v=UtSSMs6ObqY&t=1s

⏳ Timestamps ⏳
00:00 | Video Overview
00:34 | Project Demo
02:02 | Python Setup/Installation
04:33 | Ollama Setup
07:14 | GitHub Copilot
08:22 | Local LLM Usage
14:52 | Vector Store Database Setup
23:24 | Connecting LLM & Vector Store

#sponsored

TechWithTim, founded by Tim Ruscica, is a popular YouTube channel and blog offering tutorials, guides, and projects on programming, game development, and machine learning. With a friendly and approachable teaching style, Tim covers a wide range of topics, including Python programming, game development with Pygame, and machine learning algorithms with TensorFlow and Keras. Developers of all skill levels can benefit from TechWithTim's engaging content and hands-on coding projects, making it an in resource for learning and honing technical skills.

Tech With Tim

Learn how to build a local AI agent using Python, LangChain, Ollama, and ChromaDB. The project demonstrates setting up an AI to query and interpret data from a CSV file, such as restaurant reviews, using retrieval augmented generation. All processes run locally without requiring external accounts or cloud services, making it a highly accessible project.

How to Build a Local AI Agent With Python (Ollama, LangChain & RAG)