The Sample Applications listed are provided as application templates that you can use. The key goal of these applications is to get you started quickly and help you understand how you can integrate the Gemini API in Vertex AI and the necessary commands to deploy these applications to Google Cloud.
Click on the application name to see detailed documentation, sample template and instructions to deploy on Google Cloud.
We provide instructions for setting up your environment in Cloud Shell. Before you run any of the sample applications, ensure that you have followed the instructions in SETUP.md.
| Description | Application Name | Technologies Used |
|---|---|---|
| Develop a Gemini application using Streamlit framework and Gemini API in Vertex AI model. | gemini-streamlit-cloudrun | Cloud Run, Streamlit, Python |
| Deploy a RAG + Gemini sample application to troubleshoot your car using the owner's manual. | fixmycar/ | Chat, Grounding, RAG, Java, Streamlit |
Try Gemini image recognition in bash and see Text-to-Speech read the description to you in ~any language. All from CLI! |
image-bash-jam/ | Text-to-Speech, Bash |
| This demo showcases how you can combine the data and documents you already have and the skills you already know with the power of AlloyDB AI, Vertex AI, Cloud Run, and Cloud Functions to build trustworthy Gen AI features into your existing applications. | GenWealth | Vertex AI, AlloyDB, Document AI, Cloud Run, Cloud Functions, Cloud Storage |
| End-to-end Gen AI App Starter pack: This folder provides a template starter pack for building a Generative AI application on Google Cloud. It provides a comprehensive set of resources to guide you through the entire development process, from prototype to production. | e2e-gen-ai-app-starter-pack | Vertex AI, FastAPI, LangChain, Cloud Run, Cloud Build, Terraform, Streamlit |