LangChain: Use the Power of GPT to Chat with Earnings Reports of Companies
Do you want to compare many quarterly reports of public companies? It’s tedious to look through all the quarterly reports by hand. An assistant would be very helpful, wouldn’t it? That’s our motivation to build an AI assistant for comparing different earnings reports. Be curious!
We implement the assistant with the frameworks LangChain and Plotly Dash in Python. If you want to learn more about Plotly Dash, we recommend our article “A Comprehensive Guide to Building Enterprise-Level Plotly Dash Apps (Si apre in una nuova finestra)”. This article shows you how to build a production-ready web app with Plotly Dash and Docker. If you are a LangChain beginner, we recommend our introduction article about LangChain.
https://hub.tinztwins.de/constructing-a-chatgpt-like-app-using-langchain-and-plotly-dash (Si apre in una nuova finestra)The article is a perfect starting point for understanding the basics of LangChain, and it’s essential for understanding the concepts in this article.
Now let’s start with what you can expect in this article.
What can you expect?
In this article, we’ll analyse the Q1–2023 earnings reports of Tesla, Mercedes Benz and BMW. First, we’ll give you a technical overview. The overview shows you the individual components which we need. Furthermore, we explain the loading of the PDF documents (earnings reports), the data preparation and how agents in LangChain work.
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