LLMs-in-Finance
A collection of Jupyter notebooks demonstrating how to apply generative AI agent frameworks such as AutoGen, LlamaIndex and CrewAI to financial analysis, trading strategy and RAG on earnings reports.
LLMs-in-Finance is a set of hands-on Jupyter notebooks showing how to apply generative AI tools to financial workflows. It is organized into sections on AI agents in finance, using frameworks such as OpenAI's Agents SDK, AutoGen, LlamaIndex, CrewAI and LangGraph to build collaborative agents for market analysis and trading-strategy generation, retrieval-augmented generation for parsing and analyzing financial documents, and multimodal models tested on financial charts.
Individual notebook examples cover tasks such as an evaluator-optimizer multi-agent system for reviewing trading strategy code, a financial news bot, momentum trading strategy configuration, and stock-performance analysis with a code-interpreter agent. A separate section curates papers on generative AI in financial applications.