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This tutorial demonstrates how to use large language models (particularly the Gemini 2.0 Flash model) to build an advanced AI-powered stock dashboard that automatically interprets charts based on technical analysis. The workflow involves first creating a technical indicators chart and then sending an image of the chart to the Google AI Studio API to have the Gemini 2.0 Flash model interpret it. In a previous video, I showed how to do this process locally on your own computer using Meta's Llama 3.2 Vision model through Ollama ( • Build an AI-Powered Technical Analysis Sto... ) This is just a starter template that you can improve upon, including adding additional technical indicators, improving the prompt, integrating AI reasoning agents to better think through technical analysis interpretations, and backtesting to understand past performance. ***Important Note: This video is not financial or investing advice. It is an educational tutorial on how to use AI/LLM vision models in Python. Also, don't blindly trust the results of LLM model results without critical thinking or subject matter expertise 🧠. LLM's are still experimental technology that have high error rates.*** ****Beta Test Preview**** Want to run backtests directly in Google Sheets without any code? Check out the FREE Stock Backtester Google Sheets Add On: https://stockbacktester.com/ If you find this helpful : *Like (👍)* Comment *Subscribe* *Subscribe for FREE to the Deep Charts Newsletter* -- https://deepcharts.substack.com/ *Full Code (as seen in video)* https://deepcharts.substack.com/p/bui... *Premium Full Code* Includes additional technical indicators, ability to quickly customize parameters of technical indicators, and advanced charting Purchase one-time here: https://deep-charts-shop.fourthwall.c... *Resources* Google AI Studio (Get your API key): https://aistudio.google.com/welcome Gemini 2.0 Pricing: https://ai.google.dev/pricing Streamlit: https://docs.streamlit.io/ yfinance: https://ranaroussi.github.io/yfinance... *Chapters* 0:00 - Motivation and Intro 0:48 - How to extend this analysis even more 1:08 - Considerations of running this Technical Analysis 1:16 - Libraries and Models used to create dashboard 1:47 - Walkthrough of Workflow 2:44 - Where to find code for this tutorial as well as premium code 3:14 - Disclaimer -- this is not financial or investing advice 3:36 - How to create a Google AI Studio API Key for Gemini 2.0 Flash 4:26 - How to setup your Python Environment for this tutorial 4:50 - Streamlit Technical Analysis Dashboard Code Walkthrough 11:05 - Demo of Technical Analysis Dashboard