Developer builds a fully offline Python RAG stack with Ollama and sqlite-vec
11/03/2026 — 11/03, 10:18·1 sources (all)·1 reports (all)
Key takeaways
- A developer published a full architecture breakdown on DEV Community for a fully private, offline RAG application built with Ollama, sqlite-…
Background & analysis
On November 3, 2026, a developer published a full architectural breakdown on DEV Community showing how to build a fully private, offline-capable RAG application using Ollama, sqlite-vec, and a function-calling Agent.
The article estimates a scenario of 10,000 queries per day with multi-turn context and reasoning models, and calculates that a token-metered cloud API would produce between $800 and $3,000 per month in variable costs. It adds that healthcare, legal, and enterprise customers flatly refuse to let sensitive internal documents cross public cloud network boundaries, which is why the author opts for a 100% private setup. The piece walks through the complete architecture, but both the summary and the excerpted text cut off before implementation-level details such as retrieval, chunking, or embedding choices can be verified.
AI-generated from 1 reports · updated 3 days ago
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A developer walks through building a fully private, offline RAG stack in pure Python with Ollama, sqlite-vec and function-calling agents. The post estimates metered API costs of $800 to $3,000 a month at 10,000 queries per day, and notes that healthcare, legal and enterprise clients refuse to let sensitive documents cross public cloud boundaries.
DEV Community · AIAI score 55
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