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refactor: flatten vectors references to root references directory
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -4,7 +4,7 @@
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## Overview
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## Overview
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Guides and best practices for working with Supabase. Covers getting started, Auth, Database, Storage, Edge Functions, Realtime, supabase-js SDK, CLI, and MCP integration. Use for any Supabase-related questions.
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Guides and best practices for working with Supabase. Covers getting started, Auth, Database, Vectors/AI, Storage, Edge Functions, Realtime, supabase-js SDK, CLI, and MCP integration. Use for any Supabase-related questions including vector search, embeddings, RAG, and semantic search.
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## Structure
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## Structure
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| Priority | Category | Impact | Prefix |
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| Priority | Category | Impact | Prefix |
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|----------|----------|--------|--------|
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|----------|----------|--------|--------|
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| 1 | Database | CRITICAL | `db-` |
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| 1 | Database | CRITICAL | `db-` |
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| 2 | Realtime | MEDIUM-HIGH | `realtime-` |
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| 2 | Vectors | MEDIUM | `vectors-` |
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| 3 | Realtime | MEDIUM-HIGH | `realtime-` |
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Reference files are named `{prefix}-{topic}.md` (e.g., `query-missing-indexes.md`).
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Reference files are named `{prefix}-{topic}.md` (e.g., `query-missing-indexes.md`).
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@@ -64,6 +65,16 @@ Reference files are named `{prefix}-{topic}.md` (e.g., `query-missing-indexes.md
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- `references/realtime-setup-auth.md`
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- `references/realtime-setup-auth.md`
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- `references/realtime-setup-channels.md`
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- `references/realtime-setup-channels.md`
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**Vectors** (`vectors-`):
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- `references/vectors-embed-generation.md`
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- `references/vectors-index-hnsw.md`
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- `references/vectors-index-ivfflat.md`
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- `references/vectors-perf-tuning.md`
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- `references/vectors-rag-patterns.md`
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- `references/vectors-search-hybrid.md`
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- `references/vectors-search-semantic.md`
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- `references/vectors-setup-pgvector.md`
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---
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---
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*27 reference files across 2 categories*
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*35 reference files across 3 categories*
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@@ -10,7 +10,12 @@ queries.
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**Impact:** CRITICAL
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**Impact:** CRITICAL
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**Description:** Row Level Security policies, connection pooling, schema design patterns, migrations, performance optimization, and security functions for Supabase Postgres.
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**Description:** Row Level Security policies, connection pooling, schema design patterns, migrations, performance optimization, and security functions for Supabase Postgres.
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## 2. Realtime (realtime)
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## 2. Vectors (vectors)
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**Impact:** MEDIUM
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**Description:** pgvector setup, HNSW/IVFFlat indexing, semantic and hybrid search, embedding generation, RAG patterns, and performance tuning.
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## 3. Realtime (realtime)
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**Impact:** MEDIUM-HIGH
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**Impact:** MEDIUM-HIGH
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**Description:** Channel setup, Broadcast messaging, Presence tracking, Postgres Changes listeners, cleanup patterns, error handling, and debugging.
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**Description:** Channel setup, Broadcast messaging, Presence tracking, Postgres Changes listeners, cleanup patterns, error handling, and debugging.
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# Section Definitions
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Reference files are grouped by prefix. Claude loads specific files based on user
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queries.
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---
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## 1. Setup (setup)
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**Impact:** HIGH
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**Description:** pgvector extension setup, vector column types (vector, halfvec, bit), dimension configuration, and Supabase-specific schema patterns.
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## 2. Indexing (index)
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**Impact:** CRITICAL
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**Description:** HNSW and IVFFlat index creation, parameter tuning (m, ef_construction, ef_search, lists, probes), operator classes, and concurrent index builds.
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## 3. Search (search)
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**Impact:** CRITICAL
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**Description:** Semantic search with match_documents functions, hybrid search combining vectors with full-text, RRF scoring, metadata filtering, and RLS integration.
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## 4. Embeddings (embed)
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**Impact:** HIGH
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**Description:** Embedding generation using gte-small built-in model, OpenAI integration, automatic embeddings with triggers, and Edge Function patterns.
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## 5. RAG (rag)
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**Impact:** HIGH
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**Description:** Retrieval-Augmented Generation patterns including document ingestion, chunking strategies, query pipelines, and Edge Function architectures.
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## 6. Performance (perf)
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**Impact:** CRITICAL
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**Description:** Vector search optimization, index pre-warming, compute sizing for vector workloads, batch operations, and query monitoring.
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