This application allows users to query financial data efficiently using natural language. This project demonstrates how to integrate a ChromaDB vector store within a LangChain pipeline to build an AI-powered GPT Investment Advisor Q&A agent for querying and analyzing financial data.

2022 Full Year Annual Report – Macquarie Group 2022 Full Year Annual Report

Follow these steps to set up and run the project:

python -m venv env

• Windows:

  .\env\Scripts\activate

• Mac/Linux:

  source env/bin/activate

git clone https://github.com/dthatprince/finchain

cd finchain

pip install -r requirements.txt

Open app.py and update line 28 with your OpenAI API key (https://platform.openai.com/api-keys):

os.environ["OPENAI_API_KEY"] = "your-api-key-here"

streamlit run app.py

1. What was the net profit of the company?
2. What initiatives did the bank take towards sustainability?
3. Summarize the financial performance of the bank.

✅ AI-powered financial analysis
✅ Natural language queries
✅ ChromaDB vector storage integration
✅ LangChain-powered pipeline
✅ Easy deployment with Streamlit

• Python 3.8+
• OpenAI API Key
• Streamlit