Documentation and resources for building and implementing generative AI applications with Google Cloud tools and products.
Start your proof of concept with $300 in free creditAccess 20+ free products for common use cases, including AI APIs, VMs, data warehouses, and more.
Learn about building generative AI applications Gen AI development flow Model exploration and hostingGoogle Cloud provides a set of state-of-the-art foundation models through Vertex AI, including Gemini. You can also deploy a third-party model to either Vertex AI Model Garden or self-host on GKE or Compute Engine.
Prompt design and engineeringPrompt design is the process of authoring prompt and response pairs to give language models additional context and instructions. After you author prompts, you feed them to the model as a prompt dataset for pretraining. When a model serves predictions, it responds with your instructions built in.
Grounding and RAGGrounding connects AI models to data sources to improve the accuracy of responses and reduce hallucinations. RAG, a common grounding technique, searches for relevant information and adds it to the model's prompt, ensuring output is based on facts and up-to-date information.
Agents and function callingAgents make it easy to design and integrate a conversational user interface into your mobile app, while function calling extends the capabilities of a model.
Model customization and trainingSpecialized tasks, such as training a language model on specific terminology, might require more training than you can do with prompt design or grounding alone. In that scenario, you can use model tuning to improve performance, or train your own model.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025-10-13 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-10-13 UTC."],[],[]]
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.5