Building an LLM Model using Google Gemini API

Since the release of ChatGPT and the GPT models from OpenAI and their partnership with Microsoft, everyone has given up on Google, which brought the Transformer Model to the AI space. More than a year after the GPT models were released, there were no big moves from Google, apart from the PaLM API, which failed to catch the attention of many. And then came all of a sudden the Gemini, a group of foundational models introduced by Google. Just a few days after the launch of Gemini, Google released the Gemini API, which we will be testing out in this guide and finally, we will be building a simple chatbot using it.Learn the fundamentals of Google’s Gemini series, including its different models (Ultra, Pro, Nano) and their focus on multimodality with text and image support.

Develop skills in creating chat-based applications using Gemini Pro’s chat model, understanding how to maintain chat history and generate responses based on user context.
Explore how Gemini ensures responsible AI usage by handling unsafe queries and providing safety ratings for various categories, enhancing user awareness.
Gain hands-on experience with Gemini Pro and Gemini Pro Vision models, exploring their text generation and vision-based capabilities, including image interpretation and description.
Learn how to integrate Langchain with the Gemini API, simplifying the interaction process, and discover how to batch inputs and responses for efficient handling of multiple queries.

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