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●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 API/2026-07-12Advanced

When a Whole Chapter Vanished From My Long-PDF Summary — Field Notes on Auditing Coverage

Chapter-wise summarize-then-merge works well on long PDFs, but a lost extraction or a merge step can drop an entire chapter while the pipeline finishes without a single error. This walks through catching those silent drops with one number—coverage—and re-running only the chapters that fell out.

◈ Gemini API/2026-03-28Intermediate

Build an AI Document Summarizer with Gemini API and Python Flask — Hands-On Tutorial

Learn how to build a web app that automatically summarizes text and PDF documents using the Gemini API and Python Flask. From prompt design to deployment.

◈ Gemini API/2026-03-28Beginner

Automate Document Summarization and Meeting Notes with Gemini API

Learn how to build an automated document summarization and meeting notes system using the Gemini API and Python. Covers text, PDF, and audio file processing with practical code examples.

◈ Gemini API/2026-03-27Beginner

How to Analyze and Summarize PDFs with Gemini API — A Practical Python Guide

Learn how to extract text, summarize, and run Q&A on PDF files using the Gemini API in Python. A step-by-step guide covering File API uploads, multimodal processing, and structured data extraction.