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Hello everyone! In this blog post, we'll explore how to get started with Google's Gemini API using Python. We'll guide you through setting up your development environment, generating text responses, handling multimodal inputs, and using Gemini for multi-turn conversations. By the end of this post, you'll have a solid understanding of how to interact with various Gemini models using the API keys you created earlier. Setting Up Your Environment To begin, ensure you have created your API key following the steps in the previous post. If you haven't done so, please refer to the previous guide to create your API key. We'll demonstrate this setup using Google Colab. Let's get started by setting up your development environment. Step 1: Install the Necessary Libraries First, we need to install the Google Generative AI package and other required libraries. !pip install -q -U google-generative-ai Step 2: Import Libraries and Configure API Key Next, we'll import the

Hello everyone! In this post, we'll guide you through the process of creating free API keys to access Google's Gemini models. These API keys are essential for leveraging the capabilities of Gemini models in your projects. Let's dive into the step-by-step process. Accessing Google AI Studio To begin, you need to visit the Google AI Studio. Here's the URL: AI Studio . Once you navigate to this URL, you'll land on the AI Studio page where you can get started with the Gemini API by signing in with your Google account. Understanding the Transition Initially, the Gemini models were available on a different website, MakerSuite. However, the URL has now changed to AI Studio. This new platform allows you to create API keys, design new prompts, and experiment with different models. Exploring Google Gemini Models Gemini 1.5 Pro Let's explore the Gemini 1.5 Pro model. Here’s a quick demo: Ask a Question : Type "Hi" and see the response. Request a Task : Ask "