Gemini API - YouTube Guru Prediction Analyzer

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AI Summary

Summary of YouTube Video Transcript

• The video discusses a project called “YouTube Guru Analyzer” which uses the Google Gemini API to analyze YouTube videos, extract financial predictions, and compare them with actual market outcomes.
• The project aims to provide a way to perform due diligence on financial influencers by analyzing their past predictions.
• The code for the project is shared on GitHub at github.com/slackingthemarkets under the repository “Gemini multimodal structured extraction.”
• The application is built using Python and requires several dependencies, including Streamlit for the UI, YT-DLP for YouTube metadata extraction, pandas and YFinance for financial data, and Altair for visualization.
• The Google Gemini API is used to analyze YouTube videos by passing in URLs and extracting predictions.
• The app’s UI allows users to input a YouTube URL, which is then processed to display predictions and their outcomes.
• The video demonstrates the app by analyzing predictions from financial influencers and comparing their accuracy with market performance.
• The app can identify successful predictions, such as Joseph Wang’s S&P 500 forecast, as well as poor recommendations, like those from the channel Financial Education.
• The creator suggests the tool could be extended to create a financial media search engine.

Detailed Instructions and URLs

• GitHub Repository: github.com/slackingthemarkets
  • Repository Name: “Gemini multimodal structured extraction”
• Dependencies Installation: pip install -r requirements.txt
• Running the App: streamlit run YouTubeGuru.py
• Google Gemini API: Used for video analysis (specific model and API key not provided)
• Financial Data Source: Yahoo Finance (via YFinance Python package)
• Visualization: Altair charts (via Streamlit Altair integration)

Tips and Additional Information

• The app uses structured extraction to parse predictions from videos.
• The Gemini API allows direct analysis of YouTube videos without downloading them.
• The app’s UI is simple, with an input field for YouTube URLs and dynamic text output.
• The video includes demonstrations of analyzing various financial influencers’ predictions.
• The creator emphasizes the cyclical nature of market sentiment and the potential for AI to analyze financial media content.