Build an AI-Powered Technical Analysis Stock Dashboard in Python with Streamlit and Ollama

This tutorial shows you how to build a large language model powered financial dashboard that interprets stock charts based on technical analysis. It leverages open source AI tools and models, such as Ollama and Meta's Llama 3.2-Vision, as well as Python libraries such as Streamlit, yfinance, Pandas, and Plotly.

This tutorial is just a skeletal workflow that could be expanded in multiple ways, including adding additional technical indicators for analysis, prompting the LLM to use specialized technical analysis theories, and using alternative open source models or API's such as Openai/ChatGPT, Anthropic, Google, or Mistral.

This tutorial is nowhere near rigorous, but is about the art of the possible -- it is up to you as the data scientist, machine learning engineer, or financial analyst to customize a workflow based on your own financial theories and perspectives.

*NOTE: Set yfinance to the following version to get chart working: "pip install yfinance==0.2.40"*

***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.***





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*NEW VIDEO using Gemini 2.0 Flash instead of Ollama:*
   • Build an Advanced AI-Powered Technical Ana...  

*Full Code*
deepcharts.substack.com/p/build-an-ai-powered-tech…

*Resources*
Ollama: ollama.com/
Llama 3.2-Vision Model: ai.meta.com/blog/llama-3-2-connect-2024-vision-edg…
Streamlit: docs.streamlit.io/
yfinance: ranaroussi.github.io/yfinance/index.html

*Chapters*
0:00 AI Technical Analysis Dashboard Demo
0:20 Ways to Further Customize this AI Analysis
0:38 Project Tech Stack
1:01 Reasons To Not Trust AI for Technical Analysis
1:31 Ollama and Llama 3.2-Vision Installation
1:55 Install Other Libraries
2:04 Streamlit Code for Building AI-Powered Technical Analysis Dashboard
3:39 Data Visualization, Chart Creation, and Technical Indicators Calculation
5:40 Initiating the AI Technical Analysis
6:44 Launching the Streamlit Dashboard
7:04 Additional Thoughts on How to Customize and Expand AI Analysis Workfl