Generative Ai
This repository, part of Google Cloud Platform, provides a comprehensive collection of sample code and Jupyter notebooks designed to showcase generative AI capabilities on Google Cloud. It focuses on the usage of Vertex AI and the Gemini family of models, including the Gemini Enterprise Agent Platform, for building a wide range of applications. The examples cover text generation, image and video understanding, audio processing, embeddings for semantic search, and the creation of conversational AI agents. The resource is continuously updated to reflect the latest model releases and API changes, ensuring developers have access to current best practices. The repository is structured into subdirectories like agents, audio, embeddings, and more, each containing self-contained notebooks and code snippets that can be executed in a Google Cloud environment or adapted locally. It serves as both an educational tool and a starting point for integrating generative AI into enterprise solutions, with clear instructions on prerequisites such as Google Cloud authentication and enabling necessary APIs. Additionally, it includes advanced topics like retrieval-augmented generation (RAG), function calling, and multi-modal interactions, making it suitable for both beginners and experienced practitioners.
- Category
- LLM
- Pricing
- Open Source
Problem solved
Developers and organizations often face a steep learning curve when adopting generative AI on cloud platforms, dealing with complex API integrations, model prompting, and ensuring production readiness. This repository solves that by providing ready-to-run, documented examples that demonstrate end-to-end workflows using Google Cloud's generative AI services, significantly reducing the time and effort required to prototype and deploy AI-powered features.
Use cases
- Building conversational AI agents using Gemini models
- Generating text, code, or creative content
- Analyzing and describing images and videos
- Implementing semantic search and recommendations with embeddings
- Processing and summarizing audio data
- Creating multimodal applications that combine text, images, and audio
Audience
- Developers
- ML Engineers
- Data Scientists
Pros
- Comprehensive coverage of generative AI use cases on Google Cloud
- Official Google resource with high-quality, maintained examples
- Easy-to-follow Jupyter notebooks for quick prototyping
- Up-to-date with the latest Gemini model versions and features
- Covers both basic and advanced topics like agents and RAG
Cons
- Requires a Google Cloud account and credits for execution
- Not a reusable library; code must be adapted for production use
- May be overwhelming for absolute beginners due to breadth
Official website: https://github.com/GoogleCloudPlatform/generative-ai
Canonical LambdaBase page: https://www.lambdabase.com/tools/generative-ai