googleapis/go-genai
Google Gen AI Go SDK provides an interface for developers to integrate Google's generative models into their Go applications.
What it solves
It provides a standardized interface for Go developers to integrate Google's generative AI models, such as Gemini, into their applications without having to write raw API calls.
How it works
The SDK acts as a client library that connects to either the Gemini Developer API or the Gemini Enterprise Agent Platform. Developers can configure a client using API keys or project-specific cloud settings and then call methods like GenerateContent to send multimodal inputs (text and images) to the models.
Who it’s for
Go developers who want to build AI-powered features using Google's generative models.
Highlights
- Supports both the Gemini Developer API and the Gemini Enterprise Agent Platform.
- Enables multimodal capabilities, allowing the generation of text from combined text and image inputs.
- Flexible client configuration via code or environment variables.
Related
- Project
googleapis/java-genaiA Java SDK for interacting with Gemini Developer and Gemini Enterprise Agent Platform APIs, enabling content generation, tool use, and multimodal inputs.
- Project
googleapis/python-aiplatformThe Python SDK for the Gemini Enterprise Agent Platform (formerly Vertex AI) allows developers to build, deploy, and optimize AI agents, manage prompts, and evaluate generative AI models.
- Project
GetStream/gemini-androidA demonstration project showing how to integrate Google's Gemini AI with the Stream Chat SDK to build an AI-powered chat application on Android.
- Project
googleapis/js-genaiOfficial JavaScript/TypeScript SDK (`@google/genai`) for calling Gemini LLMs via the Gemini Developer API or Gemini Enterprise Agent Platform. Provides model calls, streaming, chat state, caching, file upload, live sessions, function‑calling tools, and a high‑level Interactions API for complex, multimodal workflows.
- Project
googleapis/python-genaiOfficial Python SDK for Google’s Gemini generative‑AI models, supporting both public and enterprise APIs, typed request building, async/streaming calls, function calling, safety settings, and easy client management.