This repository provides a concise, hands-on crash course for developers looking to integrate Google's Gemini AI models into their applications. It focuses on practical implementation and rapid learning for those new to the Gemini API.

How It Works

The course utilizes Python code examples to demonstrate key functionalities of the Gemini API, including text generation, multimodal input processing (text and images), and prompt engineering techniques. It emphasizes a direct, code-first approach to understanding model capabilities and API interactions.

Quick Start & Requirements

• Install: pip install google-generativeai
• Prerequisites: Python 3.7+, Google Cloud account with Gemini API enabled, API key.
• Setup: Requires obtaining and setting an environment variable for the Gemini API key.
• Docs: Google AI for Developers

Highlighted Details

• Covers text-only and multimodal (text + image) input.
• Demonstrates basic prompt engineering for controlled output.
• Includes examples for streaming responses.
• Provides a foundational understanding of Gemini's capabilities.

Maintenance & Community

This appears to be a personal project by krishnaik06, with no explicit mention of a dedicated community or ongoing maintenance beyond the initial content.

Licensing & Compatibility

The repository does not specify a license.

Limitations & Caveats

The course is a basic introduction and does not cover advanced topics such as fine-tuning, complex agentic workflows, or production-level deployment considerations. It is a learning resource rather than a production-ready library.