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© 2026 YOLOX SYSTEM. ALL RIGHTS RESERVED.
© 2026 YOLOX SYSTEM. ALL RIGHTS RESERVED.
Gives your agent the ability to build, orchestrate, and deploy production-ready AI workflows and multi-agent systems using Firebase Genkit.
When building complex multi-step AI pipelines with type-safe inputs and outputs
When creating RAG pipelines with vector databases or multi-agent systems
When deploying AI functions to Firebase Cloud Functions or Google Cloud Run
Define your AI workflow requirements, including model selection and data sources
Specify the input and output schemas using Zod for type safety
Implement core AI logic such as prompt management, tool calling, or RAG
Use the Genkit CLI to test, trace, and evaluate your flows before deployment
You
I need to build a RAG pipeline for my documentation using Gemini and a local vector store.
Agent
I'll help you set up a Genkit project with the Google AI plugin. We'll define a flow that indexes your docs into a local vector store and another flow that retrieves relevant context to answer questions. I'll also include type-safe schemas and tracing so you can debug the retrieval process in the Genkit Developer UI.
Gives your agent the ability to quickly build and deploy modern AI chat interfaces with built-in tool streaming, approvals, and generative widgets.
Gives your agent the ability to run over 150 cloud-based AI applications for image generation, video creation, web search, and social media automation.
Gives your agent the ability to add a visual feedback and annotation toolbar to Next.js projects for real-time syncing between users and AI agents.
Gives your agent the ability to evaluate and improve its own output through iterative reflection, self-critique, and refinement loops.
Gives your agent the ability to automate browser tasks like navigating websites, filling forms, taking screenshots, and extracting data using a CLI.
© 2026 YOLOX SYSTEM. ALL RIGHTS RESERVED.
