Smart Investment Portfolio Advisor AI Agent with Java, Spring, Langchain4j, and OpenAI/Ollama

In this video, we'll walk you through creating a smart investment portfolio advisor AI agent using Java, Spring Boot, Langchain4j, and OpenAI/Ollama. This project integrates advanced features like function/tool calling in LLMs to access real-time financial information and assist in decision-making. We'll explore how to store stock orders, calculate positions, integrate with external APIs. Perfect for developers looking to blend AI and finance with modern tech stacks!

Topics Covered:
• Creating an API to store stock orders in PostgreSQL and calculate portfolio position
• Exploring different methods of calling LLM with Langchain4j
• Integrating Langchain4j with a Spring Boot stock advisor API using AIServices
• Sending various types of messages to LLM
• Implementing chat memory
• Overview of Retrieval-Augmented Generation (RAG)
• Overview of Tool/Function calling and its functionality
• Exposing company information services as tools to LLM
• Using chat to receive investment advice based on latest company data using tools
• Testing tool flows and tracing the application during testing
Exposing order creation and listing services as tools and using chat for order management

Tags: #SpringBoot #Langchain4j #OpenAI #Ollama #InvestmentAdvisor #FinanceApp #LLM #AI #RAG #NextJS #React

[skumar]

Thanks for this tutorial. I can now implement Lang chain in my production app.

[gauravsalunke]

which plugin ur using for auto code generation?

[skumar]

One more request bring tutorial on nextjs part as well. Currently I am using spring boot with thymeleaf for ui part. Maybe I learn nextjs as frontend. I am a spring boot backend guy.