GEMINI LABJP
SUNSET — Three days until the image models shut down: Imagen 4 and the Gemini 3 Image family stop on August 17MIGRATE — gemini-3.1-flash-image is the recommended target; calls to generate_images() fail hard after the cutoff, so there is no grace periodFLASH — Gemini 3.6 Flash is generally available, with better token efficiency and stronger code and agentic planning at a lower price than 3.5 FlashLITE — Gemini 3.5 Flash-Lite also reached GA as a low-latency, cost-conscious subagent option aimed at high-volume automationPARAMS — The sampling parameters temperature, top_p, and top_k are now deprecated, so existing calls are worth revisitingROBOTICS — gemini-robotics-er-1.6-preview shuts down on August 31, so this is the window to plan the migrationSUNSET — Three days until the image models shut down: Imagen 4 and the Gemini 3 Image family stop on August 17MIGRATE — gemini-3.1-flash-image is the recommended target; calls to generate_images() fail hard after the cutoff, so there is no grace periodFLASH — Gemini 3.6 Flash is generally available, with better token efficiency and stronger code and agentic planning at a lower price than 3.5 FlashLITE — Gemini 3.5 Flash-Lite also reached GA as a low-latency, cost-conscious subagent option aimed at high-volume automationPARAMS — The sampling parameters temperature, top_p, and top_k are now deprecated, so existing calls are worth revisitingROBOTICS — gemini-robotics-er-1.6-preview shuts down on August 31, so this is the window to plan the migration
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Gemini API/2026-07-23Advanced

When to Hand Conversation State to the Server: previous_interaction_id vs. Pruning History Yourself

With the Interactions API, passing previous_interaction_id lets the server hold conversation state so you stop resending history. But a large tool output that lands mid-conversation can't be pruned afterward, and every later turn drags its weight. Here is a branching design that mixes server-side state with client-side pruning, plus a thin, working Python wrapper.

Gemini Dev/2026-07-11Advanced

Never Generate the Same Narration Twice: Cache-Key Design and Invalidation for Gemini TTS Output

For apps that replay the same audio over and over—meditation, language learning, storytelling—caching the Gemini TTS output itself drives the variable cost to near zero. This is a working design: how to build a cache key that text alone can't cover, a two-tier server-plus-device cache, and an invalidation policy that survives model shutdowns like the August 17 image-model deprecation.

Gemini API/2026-07-06Advanced

Ingested but Never Cited: Pruning a File Search Store with Citation Logs and a Quarantine Window

Most documents in a File Search store are never cited, quietly draining both cost and retrieval quality. Learn to log grounding metadata, surface never-cited documents from real usage data, and prune them safely with a quarantine window — with working code.

Gemini API/2026-07-02Advanced

Routing Between Local Gemma 4 and the Gemini API Cut My Bill from ¥32,000 to ¥9,000 — A Production Hybrid Router Design

How I cut a ¥32,000/month Gemini API bill to the ¥9,000 range with hybrid inference: routing design, a full Python router, production pitfalls, and how Gemma 4 arriving on the Gemini API in July 2026 changes the decision.

Gemini Advanced/2026-07-02Advanced

After You Improve the Prompt, How Far Back Do You Regenerate? — Designing a Budget-Bounded Backfill

A prompt improvement only helps future output — thousands of old artifacts stay on the previous generation. This piece covers a budget-bounded backfill: selection scoring, edit-detection hashes, a pre-replacement gate, and a resumable cursor, with working code.

Gemini API/2026-06-25Intermediate

Turning Articles into Audio with the Gemini 3.1 Flash TTS Preview: Splitting Long Text, Stitching It Back, and What It Actually Costs

The Gemini 3.1 Flash TTS preview launched today. Here is a single-narrator pipeline that converts a written article into clean audio, including how to split long text, stitch PCM without ugly seams, keep one voice steady, and estimate the real per-article cost.

Gemini API/2026-06-22Advanced

Before Free Users Quietly Eat Your Margin: Tier Design and Cost Ceilings for Gemini API Apps

Protecting the margin on a Gemini-powered app means designing around a per-user monthly cost ceiling, not request counts. Tier-aware model routing, real-cost metering in KV, and the token-bloat traps that drain profit, with working code.

Gemini API/2026-06-22Advanced

Structured Product Image Analysis with the Gemini API — A Production Pipeline Built on Thousands of Photos

Turn a one-off image analysis script into a production pipeline that auto-generates tags, descriptions, and categories at scale — covering structured output, resumable batches, measured cost, and model routing learned from real indie-developer operation.

Gemini API/2026-06-21Advanced

Gemini API Implicit Caching Not Working — Troubleshooting Guide by Root Cause

Troubleshoot Gemini API implicit caching issues: cache not hitting, unexpectedly high costs, or low cache hit rates. Covers token thresholds, prompt structure, model version consistency, TTL expiry, and multimodal caching with code examples.

Gemini API/2026-06-21Advanced

Classifying 8,000 App Reviews Overnight with Gemini Batch API — and Moving Polling to Webhooks

Implementation notes on clearing ~8,000 backlogged app reviews from six iOS/Android apps with the Gemini Batch API in a single night — now extended with the June 2026 event-driven Webhooks that replace the morning polling step. Real cost and runtime numbers, composite-key design, hung-job triage, and deprecation discipline, with working code.

Gemini API/2026-06-17Advanced

Keep Your Flash-to-Pro Routing Threshold Honest with Shadow Re-evaluation

A Flash-generates, Pro-on-low-confidence router starts drifting the moment you hand-pick its threshold. This is a working build of a loop that samples your kept-Flash outputs, scores them against Pro, and recalibrates the threshold from a quality budget.

Gemini API/2026-06-14Advanced

Controlling Image Tokens with the Gemini API media_resolution Setting — Tuning Batch Image Classification by Measurement

media_resolution, introduced in the Gemini 3 line, switches how many tokens an image input consumes across three levels. Through real batch-classification measurements, this guide shows how to balance cost and accuracy by assigning the right tier per task.