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CodeNodeX AI 社区管理员，关注 AI 编程、Next.js 和独立开发。
A vector database in a designated region does not mean RAG data never crosses borders. This article uses versioned residency policies, regional evidence, and egress gates to cover parsing, model calls, caches, logs, and recovery.
Insert or update? UPSERT handles it in one statement. This article covers PostgreSQL INSERT ON CONFLICT (specifying conflict columns, DO UPDATE, DO NOTHING), MySQL ON DUPLICATE KEY UPDATE, idempotent write scenarios (sync/retry without duplication), and the pitfalls of ON CONFLICT (partial indexes, multi-column conflicts).
A successful indexing job does not mean users receive the latest knowledge. This article covers freshness SLOs, source change detection, priority queues, stale-answer handling, and operational reporting to make RAG accountable for content currency.
A single Terraform file is enough for a demo, but production requires modules and remote state. This article covers module inputs, outputs, and versions; remote state backends using S3 with DynamoDB locking or Terraform Cloud; state drift and imports; and a production-grade project structure.
Switching embedding models is not as simple as rebuilding an index and routing traffic to it. This article covers versioned vectors, dual writes and reads, offline relevance evaluation, phased cutovers, and rollback criteria to reduce sudden retrieval-quality regressions.
A modal rendered deep in a component tree can be clipped by parent z-index, overflow, or transform rules. Portal renders it in document.body to escape those constraints. Learn Portal fundamentals, a complete modal implementation, accessibility, and why Radix Dialog handles the hard parts.
Stable offline RAG metrics do not guarantee a stable production experience. Learn how to maintain gold sets, detect query-distribution drift, connect production feedback, and tune retrieval and generation through controlled experiments.
There are three ways to improve a model in a domain: Prompting, RAG, and fine-tuning. Most teams choose incorrectly, fine-tuning problems suited to RAG or adding RAG where a prompt would suffice. This article offers a decision framework for knowledge, behavior, and style requirements, including when to combine approaches.
When a RAG system retrieves contradictory content from different versions, permission scopes, or sources, it cannot let the model choose the most convenient answer. This article covers source ranking, conflict detection, temporal semantics, and a safe clarification workflow.
Generics are among TypeScript's most powerful and most overused features. This guide explains constraints, defaults, inference, built-in Utility Types, when generics help, and when they do not, with one principle throughout: types should help you, not trap you.
A document entering a vector database does not mean the knowledge base is correct. Learn versioning, event deduplication, deletion tombstones, retries, and consistency checks for incremental indexing so RAG does not keep citing stale or deleted content.
Deployment isn’t just “pushing a new version”—how you push, cut over, and roll back when something breaks determines the risk. This article covers three strategies: blue-green (instant switch between two environments), canary (validate on small traffic before scaling), and rolling (gradual replacement), their fit and cost, and how to choose in production.