CrewAi04: Build AI StockPicker with CrewAI Custom Tools & Vector Memory Integration | Multiple LLMs

Video Description

CrewAi04 CustomToolDb: Build AI StockPicker with CrewAI Custom Tools & Vector Memory Integration | Multiple LLMs | CrewAI Custom Tools | Full Tutorial 🚀 Build a Production-Ready AI Stock Picker with CrewAI | Custom Tools & Vector Memory Tutorial Learn how to create an intelligent multi-agent AI system that analyzes financial news, researches companies, and picks the best investment opportunities—automatically! This comprehensive tutorial covers CrewAI custom tools, Pydantic validation, vector memory integration, and multi-LLM orchestration. 🎯 What You'll Build: ✅ Multi-agent AI system with 5 specialized agents ✅ Real-time financial news analysis and company research ✅ Custom push notification tool for investment alerts ✅ Vector memory integration for persistent learning ✅ Structured outputs with Pydantic validation ✅ Integration with GPT-4, Claude, and DeepSeek models 💡 Perfect for: - AI developers building production systems - Financial analysts exploring AI automation - CrewAI users wanting advanced implementations - Developers interested in multi-agent architectures 🔧 Technologies Covered: - CrewAI Framework - Pydantic for data validation - SQLite vector memory - SerperDev for web search - Multiple LLMs (OpenAI, Anthropic, DeepSeek) - Custom tool development - Pushover API integration 📂 Source Code: https://github.com/matinict/MyCrewAi/tree/main/stock_picker 📺 Watch Video: https://youtu.be/MOU9EwU6SXw 🔑 Get API Keys: - SerperDev: https://serper.dev - OpenAI: https://platform.openai.com - Anthropic: https://console.anthropic.com - Pushover: https://pushover.net ⏱️ CHAPTERS: 0:00 - Introduction & Project Overview 0:20 - Setting Up CrewAI Project 1:45 - Configuring Environment Variables & API Keys 3:10 - Agent Configuration: Trending Company Finder 5:00 - Agent Configuration: Financial Researcher 6:30 - Agent Configuration: Stock Picker Agent 8:00 - Agent Configuration: Manager Agent 9:15 - Task Configuration & Workflow Design 11:20 - Building Custom Push Notification Tool 13:00 - Crew.py Setup & Memory Integration 14:30 - Main.py Entry Point Configuration 15:45 - Running the System & Output Analysis 16:30 - Memory Storage & Output Files Explained 🎓 Key Learning Outcomes: - How to structure multi-agent AI systems - Creating custom tools for CrewAI agents - Implementing vector memory for AI learning - Using Pydantic for reliable AI outputs - Orchestrating multiple LLMs in one workflow - Building production-ready AI applications 📝 Prerequisites: - Basic Python knowledge - Understanding of APIs - CrewAI basics (helpful but not required) 🔥 Resources: - Full source code on GitHub (link above) - Complete documentation in README - Sample .env template included - Ready-to-run configurations 💬 Join Our Community: ⭐ Star the GitHub repo if you find it useful! 👍 Like this video if it helped you 💬 Comment with your questions or project ideas 🔔 Subscribe for more advanced AI tutorials! #CrewAI #AIAgents #MachineLearning #Python #AITutorial #StockAnalysis #MultiAgent #OpenAI #Claude #AIAutomation #FinTech #VectorDatabase #AITools #DeepSeek #ProductionAI #Pydantic #CustomTools 🔔 Don't forget to enable notifications for upcoming tutorials on: - Advanced CrewAI patterns - Building AI trading systems - Enterprise AI agent architectures - And much more! 📧 Questions? Drop them in the comments below!