AI SummaryCopilot instructions for a full-stack wealth portfolio RAG agent that enables natural language querying across MongoDB and MySQL databases using LangChain and OpenAI. Developers building AI-assisted financial applications benefit from this structured guidance on integrating multi-database queries with modern AI frameworks.
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to add the "Wealth-Portfolio-RAG-Agent — Copilot Instructions" prompt rules to my project. Repository: https://github.com/AnujGupta1606/Wealth-Portfolio-RAG-Agent Please read the repo to find the rules/prompt file, then: 1. Download it to the correct location (.cursorrules, .windsurfrules, .github/prompts/, or project root — based on the file type) 2. If there's an existing rules file, merge the new rules in rather than overwriting 3. Confirm what was added
Description
Copilot Instructions for Wealth-Portfolio-RAG-Agent
Wealth Portfolio RAG Agent - Copilot Instructions
This project is a full-stack Natural Language Cross-Platform Data Query RAG Agent for wealth portfolio management.
Project Structure
• Backend: Python FastAPI with LangChain integration • Frontend: React TypeScript with Tailwind CSS • Databases: MongoDB (client data) + MySQL (transactions) • AI: LangChain RAG system with OpenAI
Key Technologies
• FastAPI, LangChain, ChromaDB, MongoDB, MySQL • React, TypeScript, Chart.js, Tailwind CSS • OpenAI GPT-4, Sentence Transformers
Business Domain
• Wealth management for film stars and sports personalities • Portfolio values 100+ crores • Multi-source data querying with natural language • Risk management and analytics
Discussion
Health Signals
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Works With
Any AI assistant that accepts custom rules or system prompts