In fintech or wealthtech products, people constantly need quick market context. They need to know why a particular stock moved, what changed recently, or what they should watch next. This usually beco

freeCodeCamp is a nonprofit organization offering free online coding courses and programming tutorials, covering topics such as web development, data science, and machine learning. Learners can gain practical coding skills, build real-world projects, and earn certifications to advance their careers in tech.

freeCodeCamp

A step-by-step guide to building a market copilot MVP that turns natural-language stock queries into structured market briefs. The architecture separates a LangChain/LangGraph ReAct agent backend (copilot.py) from a Streamlit UI shell (app.py). The agent calls EODHD API-backed tools for price returns, fundamentals, news headlines, and risk metrics, then composes a concise Markdown brief. Tool outputs are extracted from agent messages and passed directly to the UI as auditable artifacts, avoiding redundant API calls. Three demo workflows are shown: baseline brief, risk-first analysis, and news-only context. Practical notes cover ticker normalization, missing data handling, output drift prevention, and extension paths like multi-ticker comparison, scheduled briefs, caching, and FastAPI wrapping.

How to Build an LLM Market Copilot MVP with LangChain, APIs, and Streamlit