Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to…
Type-safe AI workflows with flows, agents, RAG, and multi-model support across TypeScript, Go, and Python. Supports Gemini, OpenAI, Anthropic, Ollama, and Vertex AI with pluggable model providers; deploy to Firebase Cloud Functions or Cloud Run Define type-safe flows with Zod schemas for inputs/outputs; includes streaming, tool calling, and agentic loops with auto-execution Built-in RAG with vector database integrations (Pinecone, pgvector, Firestore, Chroma, LanceDB) and retrieval-augmented generation Developer UI at localhost:4000 provides flow runner, trace inspector, prompt playground, and model comparison tools Manage prompts as versioned .prompt files with Dotprompt; coordinate multi-agent systems by composing specialized flows Firebase Genkit When to use this skill AI workflow orchestration: Building multi-step AI pipelines with type-safe inputs/outputs Flow-based APIs: Wrapping LLM calls into deployable HTTP endpoints Tool calling / agents: Equipping models with custom tools and implementing agentic loops RAG pipelines: Retrieval-augmented generation with vector databases (Pinecone, pgvector, Firestore, Chroma, etc.) Multi-agent systems: Coordinating multiple specialized AI agents Streaming responses: Real-time token-by-token output for chat or long-form content Firebase/Cloud Run deployment: Deploying AI functions to Google Cloud Prompt management: Managing prompts as versioned .prompt files with Dotprompt Installation & Setup Step 1: Install the Genkit CLI
don't have the plugin yet? install it then click "run inline in claude" again.