●ARGON — gemini-4-argon is generally available as of 10/13, aimed at complex coding, agents, math and science●DEEP RES — The old Deep Research agent shut down on 10/23. If calls fail, move to deep-research-preview-04-2026●NANO — gemini-nano-banana-2.1 is GA (10/06). gemini-3.1-flash-image is deprecated with no shutdown date yet●MCP — One write-up cut an 85,000-token tool result to 310 tokens by wrapping it in an ADK FunctionTool●FLASH — gemini-3.7-flash and 3.5-flash now route automatically to newer Flash models (10/08)●NEW — Stop Re-Reading Every Crash Report: Gre…●ARGON — gemini-4-argon is generally available as of 10/13, aimed at complex coding, agents, math and science●DEEP RES — The old Deep Research agent shut down on 10/23. If calls fail, move to deep-research-preview-04-2026●NANO — gemini-nano-banana-2.1 is GA (10/06). gemini-3.1-flash-image is deprecated with no shutdown date yet●MCP — One write-up cut an 85,000-token tool result to 310 tokens by wrapping it in an ADK FunctionTool●FLASH — gemini-3.7-flash and 3.5-flash now route automatically to newer Flash models (10/08)●NEW — Stop Re-Reading Every Crash Report: Gre…

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gemini-api¹ pgvector¹ semantic-search¹ embeddings¹ production¹

◈ Gemini API/2026-06-19Advanced

When Your pgvector Search Quietly Gets Worse — Field Notes on Protecting Recall with Gemini Embeddings

A semantic search built on Gemini Embeddings and PostgreSQL pgvector tends to lose precision over months without throwing a single error. These are field notes on the real causes — model pinning, operator/index mismatch, HNSW reindexing, and recall collapse under filters — with working code.