ai financial agent
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Basic Information
This repository is a proof-of-concept AI financial agent built to explore the use of large language models for investment research and financial analysis. It provides a ready-to-run chat assistant template that connects an LLM to a specialized financial data provider to surface stock prices, fundamentals, and other market data. The project is explicitly for educational and research purposes and is not intended for live trading or investment advice. The README documents local setup, required environment variables for OpenAI, Financial Datasets API, and LangSmith, and explains how to run the development server and deploy the application to Vercel. A live demo instance is available for evaluation.
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App Details
Features
The project includes a chat-based AI Financial Agent with a generative UI that displays stock prices and fundamental metrics. It integrates the Financial Datasets API to provide real-time and historical market data with over 30 years of coverage and 100% US market coverage. Data types mentioned include financial statements, stock prices, options data, insider trades, and institutional ownership. The template is implemented as a Node.js application using pnpm for dependency management and requires OpenAI and LangChain-related keys for LLM tracing and project tracking. The README also notes free sample data availability for a set of major tickers and shows how the data provider can be swapped if desired.
Use Cases
This repository is useful for developers, researchers, and learners who want a hands-on example of combining LLMs with financial market data to build chat assistants for research and prototyping. It provides an end-to-end template that includes environment configuration, local development instructions, and a path to deploy on Vercel, enabling rapid experimentation. The integration with a market-grade financial dataset and examples of data surfaces help demonstrate how an agent can query and summarize historical and real-time financial signals. The project also highlights responsible usage by disclaiming that it is not financial advice and by encouraging consultation with a financial advisor for real investment decisions.
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