Build Your Own AI-Powered Investment Banker in 5 Minutes

🧠Using your own documents allows for ultimate flexibility and customization in leveraging large language models.

🔍Chroma DB enables similarity search in your documents, making it easier to extract relevant information.

📄Loading and tokenizing PDF documents using Pi PDF and Chroma allows for more advanced querying with the GPT investment banker.

💼By combining the Open AI LLM service with your own documents, you can build a personalized investment banker for financial analysis tasks.

📈The AI-powered investment banker can generate responses and summaries based on specific prompts and queries, providing valuable insights.

Why should I use my own documents instead of pre-existing models?

—Using your own documents allows for customization and specificity, enabling the AI model to cater to your unique needs.

What types of tasks can the investment banker perform?

—The investment banker can analyze financial statements, summarize documents, provide responses to specific queries, and more.

What dependencies and tools are required for building the investment banker?

—You will need LangChain, Streamlit, Pi PDF Loader, and Chroma DB, among other dependencies.

Can I use a different document format instead of a PDF?

—Yes, you can use other document loaders provided by LangChain to work with different formats like Word documents.

How long does it take to build the investment banker?

—In just 5 minutes, you can set up and configure the AI-powered investment banker using the provided code and tools.

00:00Introduction to building an AI-powered investment banker using your own documents.

01:10Installing dependencies and setting up the application.

02:30Loading and tokenizing PDF documents using Pi PDF Loader and Chroma DB.

03:40Using the Vector Store Agent to query and search for relevant information.

04:45Running prompts and queries through the Open AI LLM service to generate responses and summaries.