◉GEMINI LABJP
●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20
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Gemini API2RAG1embeddings1Python1AI development1text-embedding-0041Structured Output1JSON Schema1Production1gemini1dspy1prompt-engineering1
◈ Gemini API/2026-05-05Intermediate

Choosing the Right Gemini RAG Pattern in 2026 — Simple vs Advanced vs Agentic, Compared with Real Code

Compare three RAG implementation patterns with the Gemini API — Simple, Advanced, and Agentic — using real code examples. Learn which pattern fits your use case and where to start.

◈ Gemini API/2026-04-30Advanced

A Blueprint for Production-Grade Structured Output with Gemini API

A practical blueprint for running Gemini API's Structured Output reliably in production. Covers schema design, error handling, and performance optimization end-to-end.

⬡ Gemini Advanced/2026-04-22Advanced

Gemini × DSPy: Retire from Prompt Craftsmanship — Automated Prompt Optimization

A hands-on implementation guide for combining Stanford's DSPy framework with Gemini to end the era of hand-written prompts. Covers Signatures, Modules, Optimizers, LLM-as-a-Judge metrics, and production pipelines — all with working code.