The Day You Switch Gemini Embedding Models: Designing a Zero-Downtime Reindex
Upgrade your embedding model and every vector you ever stored becomes incompatible. Here is a dual-index design for re-embedding hundreds of thousands of vectors without downtime, complete with a resumable reindex job and a query-side abstraction layer.
3 Gemini API Embedding Errors I Hit Building a Wallpaper App — and How I Fixed Them
Three real Gemini API Embedding errors encountered while building an auto-categorization feature for a wallpaper app with 50M+ downloads: INVALID_ARGUMENT, RESOURCE_EXHAUSTED 429, and poor RAG precision — with working code fixes.
Building a RAG Evaluation Framework with Gemini API: RAGAS, LLM-as-Judge, and Custom Metrics Production Masterclass
Complete guide to building a quantitative RAG evaluation framework using RAGAS, LLM-as-Judge with Gemini API, and custom domain metrics — including CI/CD integration and production monitoring.
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.
Building a Fully Edge RAG with Gemini API and Cloudflare Vectorize: A Production Guide for Low Latency, Low Cost, Global Delivery
Combine Gemini Embedding with Cloudflare Vectorize to ship a production RAG that runs entirely inside the Workers runtime — global latency, predictable cost, and a defensive layer covering subrequest limits, retries, and tenant isolation.
Building GraphRAG with the Gemini API — A Complete Production Guide to Hybrid Knowledge Graph + Vector Retrieval
When pure vector search hits a wall on multi-hop, relational, and aggregation queries, GraphRAG fills the gap. This guide walks through a production hybrid GraphRAG architecture powered by Gemini 2.5 Pro and Flash, with working code.
Citation-Grounded RAG with Gemini: Production Patterns for Source Attribution and Hallucination Detection
A practical guide to wiring trustworthy citations into a Gemini-powered RAG pipeline. Covers structured output, post-hoc validation, UI rendering, and a quantitative grounding score you can put on a dashboard.
Beyond Embeddings: Production Reranking with Vertex AI Ranking and Gemini-as-Judge
When pure embedding search nails the top-3 but buries the right answer at rank 4, you need a reranker. This guide walks through a production-grade two-stage architecture using Vertex AI Ranking API and Gemini-as-judge — with cost, latency, and evaluation patterns that hold up under load.
A Tiny RAG Stack With Gemini + sqlite-vec — Production Patterns for Solo Developers
If you have been holding off on adding RAG to your personal app because Pinecone's monthly fee or Qdrant's memory footprint felt like overkill, this guide is for you. We walk through a production-grade design that runs on a single server, pairing Gemini's embedding API with sqlite-vec, with working code you can lift straight into your project.
Building a Production RAG System with Gemma 4: Local LLM + Vector Search Architecture
A complete guide to building production RAG systems with Gemma 4, ChromaDB, and pgvector. Covers architecture design, chunking strategies, Long-Context RAG using the 256K window, hybrid search, and performance optimization.
Gemini API Embeddings vs Vector Databases: Pinecone, Qdrant, pgvector, and Cloud Spanner Compared for Production
Benchmark Pinecone, Qdrant, pgvector, and Cloud Spanner Vector using Gemini text-embedding-004 with real latency, cost, and code. The definitive production selection guide.
Gemma 4 API Advanced Integration Guide: Hybrid Development with Gemini API
Advanced patterns for using Gemma 4 API alongside Gemini API. Covers Vertex AI deployment, fine-tuning, RAG pipelines, and cost optimization strategies.