Description

The code demonstrates a practical implementation of using the Google Generative AI Python SDK to
interact with Gemini models for document analysis. By uploading documents from local files or URLs,
users can leverage Gemini's capabilities to answer questions, summarize content, analyze sentiment,
and translate documents. It installs necessary packages, sets up the API key and model, uploads
documents using local files or URLs, and then prompts the model to answer questions about the
document, including summarizing, sentiment analysis, and translation. This workflow showcases the
potential of Gemini for various document-based tasks and applications.

step-by-step explanation of the code:
1 Install and import: Install the google-generativeai package and import necessary libraries.
2 Setup API key: Configure your API key using genai.configure().
3 Setup model: Select a Gemini model using genai.GenerativeModel().
4 Upload document (local): Define a file path and upload using genai.upload_file().
5 Prompt with local document: Send prompts to the model using model.generate_content() with the
uploaded file.
6 Upload document (URL): Download a document from a URL and upload it using genai.upload_file().
Prompt with URL document: Send prompts to the model with the uploaded URL document.