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
• Fetching the latest company information from financialmodellingprep.com with RestClient
• 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
• Walkthrough of a UI created with Next.js and React for the portfolio advisor interface
Exposing order creation and listing services as tools and using chat for order management
Source - https://github.com/CodeWizzard01/stock-portfolio-advisor/tree/branch1
Blog - https://codewiz.info/blog/investment-advisor-langchain4j/
Medium Story - https://medium.com/@code.wizzard01/build-a-smart-investment-portfolio-advisor-with-java-spring-boot-and-langchain4j-and-ai-ce20591c962f
Tags: #SpringBoot #Langchain4j #OpenAI #Ollama #InvestmentAdvisor #FinanceApp #LLM #AI #RAG #NextJS #React
Видео Smart Investment Portfolio Advisor AI Agent with Java, Spring, Langchain4j, and OpenAI/Ollama канала Code Wiz
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
• Fetching the latest company information from financialmodellingprep.com with RestClient
• 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
• Walkthrough of a UI created with Next.js and React for the portfolio advisor interface
Exposing order creation and listing services as tools and using chat for order management
Source - https://github.com/CodeWizzard01/stock-portfolio-advisor/tree/branch1
Blog - https://codewiz.info/blog/investment-advisor-langchain4j/
Medium Story - https://medium.com/@code.wizzard01/build-a-smart-investment-portfolio-advisor-with-java-spring-boot-and-langchain4j-and-ai-ce20591c962f
Tags: #SpringBoot #Langchain4j #OpenAI #Ollama #InvestmentAdvisor #FinanceApp #LLM #AI #RAG #NextJS #React
Видео Smart Investment Portfolio Advisor AI Agent with Java, Spring, Langchain4j, and OpenAI/Ollama канала Code Wiz
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8 ноября 2024 г. 11:54:06
00:38:52
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