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genkit

Build AI workflows with Firebase Genkit using TypeScript, Go, and Python.

Updated Aug 27, 2026
Search Tags:#typescript#ai#llm#rag#agents#workflows#genkit
One-click install
npx skills add https://github.com/supercent-io/skills-template --skill genkit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: genkit
Source: https://github.com/supercent-io/skills-template/tree/main/.agent-skills/genkit
Command: npx skills add https://github.com/supercent-io/skills-template --skill genkit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the creation and deployment of complex AI applications, from simple chatbots to sophisticated multi-agent systems, by providing a robust framework for building, testing, and deploying AI workflows.

Core Features & Use Cases

  • AI Workflow Orchestration: Build type-safe, observable, and deployable AI functions (flows).
  • Tool Calling & Agents: Equip LLMs with custom tools and implement agentic loops.
  • RAG Pipelines: Implement retrieval-augmented generation with various vector databases.
  • Streaming Responses: Support real-time token-by-token output for enhanced user experience.
  • Deployment: Easily deploy AI functions to Firebase Cloud Functions, Cloud Run, or Express.js servers.

Quick Start

Install the Genkit CLI and create a new TypeScript project to start building your AI workflows.

Frequently Asked Questions about genkit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build production-ready AI workflows with TypeScript?▼

You can build production-ready AI workflows with TypeScript using Firebase Genkit to orchestrate type-safe, observable flows for chatbots and complex multi-agent systems.

Can I use Genkit with OpenAI, Anthropic, and Gemini models?▼

Yes, Genkit integrates with Gemini, OpenAI, Anthropic, and Ollama plugins, providing model flexibility for developing and testing your AI workflows across different platforms.

How do I implement retrieval-augmented generation pipelines for LLMs?▼

You can implement retrieval-augmented generation pipelines by using Genkit's framework features designed to integrate various vector databases directly into your AI workflows.

What's the best way to deploy AI functions to Firebase and Cloud Run?▼

The best way to deploy AI functions to Firebase and Cloud Run is using Genkit, which facilitates seamless deployment of your orchestrated AI workflows to these server environments.

Does Genkit support tool-calling agents and real-time streaming responses?▼

Yes, Genkit supports equipping LLMs with custom tools to implement agentic loops and provides real-time token-by-token streaming responses for an enhanced user experience.

Can I build multi-agent systems using Python and Go?▼

Yes, Genkit supports building multi-agent systems and sophisticated AI workflows using TypeScript, Go, and Python, allowing you to leverage your preferred language.

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