If you're interested in building AI Applications then stick around, because I've got a great tutorial for you. In this video, I'm going to be showing you how to build a Multi-A.I. Agent Application, in just a few minutes using a fantastic tool called Langflow.

🎞 Video Resources 🎞
GitHub Link (Code, Flow & Sample Data): https://github.com/techwithtim/Langflow-Customer-Support-Agent
Get Started with DataStax Langflow: https://dtsx.io/agents
Checkout Langflow: https://dtsx.io/3VEPL6Z
OpenAI API Key: https://platform.openai.com/api-keys
Weighing RAG Results: https://medium.com/logspace/beyond-basic-rag-retrieval-weighting-86deb741f5cc

⏳ Timestamps ⏳
00:00 | AI Agent App
00:44 | Project Demo
03:57 | LangFlow Setup
08:35 | Building a RAG Agent
18:42 | Adding RAG Data
22:30 | Adding Multi-Agents & Tools
27:18 | Adding Sample Data
26:30 | Order & Product Lookup Agent
35:10 | Running the Agent via API
42:20 | Streamlit Frontend
46:51 | Weighing RAG Results

Hashtags
#pythontutorial #langflow #aiagents

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 multi-AI agent application using Langflow to handle complex tasks like customer support. This tutorial demonstrates step-by-step integration, including implementing retrieval augmented generation (RAG) for responsive data lookup from a database and combining multiple AI agents to solve real-world business cases effectively. The guide shows how to set up a front end with Streamlit and offers ways to extend and scale the system for practical use.

ADVANCED Python AI Agent Tutorial - Using RAG, Langflow & Multi-Agents