Genkit is an open-source framework for building full-stack AI-powered applications, built and used in production by Google's Firebase. It provides SDKs for multiple programming languages with varying levels of stability:
JavaScript/TypeScript: Production-ready with full feature support
Go: Production-ready with full feature support
Python (Beta): Wide feature support approaching production-readiness
Dart (Preview): Early development with core functionality
It offers a unified interface for integrating AI models from providers like Google, OpenAI, Anthropic, Ollama, and more. Rapidly build and deploy production-ready chatbots, automations, and recommendation systems using streamlined APIs for multimodal content, structured outputs, tool calling, and agentic workflows.
Building with a coding agent? Install the Genkit skill first.
It teaches your agent the current Genkit APIs and common gotchas.
Source and manual install: genkit-ai/skills.
Get started with just a few lines of code:
import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';
const ai = genkit({ plugins: [googleAI()] });
const { text } = await ai.generate({
model: googleAI.model('gemini-flash-latest'),
prompt: 'What is the meaning of life?'
});
Explore & build with Genkit
Play with AI sample apps, with visualizations of the Genkit code that powers
them, at no cost to you.
Use a unified interface to integrate with hundreds of models from providers like Google,
OpenAI,
Anthropic, Ollama, and more. Explore, compare, and use the best models for your needs.
Integrate seamlessly with frameworks and platforms including Next.js, React, Angular, iOS, Android, using purpose-built client SDKs and helpers.
Cross-language support
Build with the language that best fits your project. Genkit provides SDKs for JavaScript/TypeScript, Go, Python (Beta), and Dart (Preview) with consistent APIs and capabilities across all supported languages.
Accelerate AI development with a purpose-built, local CLI and Developer UI. Test prompts and
flows against individual inputs or datasets, compare outputs from different models, debug with detailed execution traces, and use immediate visual feedback to iterate rapidly on prompts.
Production monitoring
Ship AI features with confidence using comprehensive production monitoring. Track model performance, and request volumes, latency, and error rates in a purpose-built dashboard. Identify issues quickly with detailed observability metrics, and ensure your AI features meet quality and performance targets in real-world usage.
How does it work?
Genkit simplifies AI integration with an open-source SDK and unified APIs that
work across various model providers and programming languages. It abstracts away complexity so you can focus on delivering great user experiences.
Genkit is designed for server-side deployment in multiple language environments, and also provides seamless client-side integration through dedicated helpers and client SDKs.
Implementation path
1
Choose your language and model provider
Select the Genkit SDK for your preferred language (JavaScript/TypeScript, Go, Python (Beta), Dart (Preview)). Choose a model provider like Google Gemini or Anthropic, and get an API key. Some providers, like Vertex AI, may rely on a different means of authentication.
2
Install the SDK and initialize
Install the Genkit SDK, model-provider package of your choice, and the Genkit CLI. Import the Genkit and provider packages and initialize Genkit with the provider API key.
3
Write and test AI features
Use the Genkit SDK to build AI features for your use case, from basic text generation to complex multi-step workflows and agents. Use the CLI and Developer UI to help you rapidly test and iterate.
4
Deploy and monitor
Deploy your AI features to Firebase, Google Cloud Run, or any environment that supports your chosen programming language. Integrate them into your app, and monitor them in production in the Firebase console.
