Changeset 0.14.0 (#67)

This commit is contained in:
2026-02-26 15:59:26 +00:00
parent 1a71658b24
commit e2149e249d
38 changed files with 5171 additions and 141 deletions

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@@ -0,0 +1,99 @@
-- 008_knowledge_bases.sql
-- Knowledge Bases: KB metadata, documents, chunks, channel links.
-- Requires: pgvector extension already installed (via db-bootstrap.sh).
-- ── Knowledge Bases ──────────────────────────
CREATE TABLE IF NOT EXISTS knowledge_bases (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
name TEXT NOT NULL,
description TEXT NOT NULL DEFAULT '',
scope TEXT NOT NULL DEFAULT 'global', -- global, team, personal
owner_id UUID REFERENCES users(id) ON DELETE CASCADE,
team_id UUID REFERENCES teams(id) ON DELETE CASCADE,
-- Snapshot of embedding config at creation time.
-- Changing the model requires a full re-embed (rebuild endpoint).
-- { "provider_config_id": "...", "model_id": "...", "dimensions": 1536 }
embedding_config JSONB NOT NULL DEFAULT '{}',
-- Denormalized stats, updated by ingest pipeline.
document_count INT NOT NULL DEFAULT 0,
chunk_count INT NOT NULL DEFAULT 0,
total_bytes BIGINT NOT NULL DEFAULT 0,
status TEXT NOT NULL DEFAULT 'active', -- active, processing, error
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT now(),
CONSTRAINT kb_scope_check CHECK (
(scope = 'global' AND owner_id IS NULL) OR
(scope = 'team' AND team_id IS NOT NULL) OR
(scope = 'personal' AND owner_id IS NOT NULL)
)
);
CREATE INDEX IF NOT EXISTS idx_kb_scope ON knowledge_bases(scope);
CREATE INDEX IF NOT EXISTS idx_kb_owner ON knowledge_bases(owner_id) WHERE owner_id IS NOT NULL;
CREATE INDEX IF NOT EXISTS idx_kb_team ON knowledge_bases(team_id) WHERE team_id IS NOT NULL;
-- ── KB Documents ─────────────────────────────
-- One row per uploaded file. Blobs live in ObjectStore under:
-- kb/{kb_id}/{doc_id}_{filename}
CREATE TABLE IF NOT EXISTS kb_documents (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
kb_id UUID NOT NULL REFERENCES knowledge_bases(id) ON DELETE CASCADE,
filename TEXT NOT NULL,
content_type TEXT NOT NULL,
size_bytes BIGINT NOT NULL,
storage_key TEXT NOT NULL,
extracted_text TEXT, -- full text for re-chunking
chunk_count INT NOT NULL DEFAULT 0,
status TEXT NOT NULL DEFAULT 'pending', -- pending, chunking, embedding, ready, error
error TEXT,
uploaded_by UUID NOT NULL REFERENCES users(id),
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE INDEX IF NOT EXISTS idx_kbdoc_kb ON kb_documents(kb_id);
-- ── KB Chunks ────────────────────────────────
-- Chunked text + embedding vector for similarity search.
-- vector(3072) accommodates all current embedding models:
-- OpenAI ada-002 / text-embedding-3-small = 1536
-- OpenAI text-embedding-3-large = 3072
-- Open-source models = typically 768-1024
-- Smaller vectors are zero-padded at insert time.
CREATE TABLE IF NOT EXISTS kb_chunks (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
kb_id UUID NOT NULL REFERENCES knowledge_bases(id) ON DELETE CASCADE,
document_id UUID NOT NULL REFERENCES kb_documents(id) ON DELETE CASCADE,
chunk_index INT NOT NULL,
content TEXT NOT NULL,
token_count INT NOT NULL DEFAULT 0,
embedding VECTOR(3072),
metadata JSONB NOT NULL DEFAULT '{}',
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE INDEX IF NOT EXISTS idx_kbchunk_kb ON kb_chunks(kb_id);
CREATE INDEX IF NOT EXISTS idx_kbchunk_doc ON kb_chunks(document_id);
-- NOTE: IVFFlat index for similarity search is created after first data
-- load (needs rows to train). The ingest handler creates it:
-- CREATE INDEX idx_kbchunk_embedding ON kb_chunks
-- USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
-- ── Channel-KB Links ─────────────────────────
-- Which KBs are active for a given channel.
CREATE TABLE IF NOT EXISTS channel_knowledge_bases (
channel_id UUID NOT NULL REFERENCES channels(id) ON DELETE CASCADE,
kb_id UUID NOT NULL REFERENCES knowledge_bases(id) ON DELETE CASCADE,
enabled BOOLEAN NOT NULL DEFAULT true,
added_at TIMESTAMPTZ NOT NULL DEFAULT now(),
PRIMARY KEY (channel_id, kb_id)
);

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@@ -0,0 +1,12 @@
-- 009_notes_embedding.sql
-- Adds vector embedding column to notes for semantic search.
-- Uses the same vector(3072) dimension as kb_chunks for uniformity.
ALTER TABLE notes ADD COLUMN IF NOT EXISTS embedding vector(3072);
-- NOTE: pgvector HNSW indexes are limited to 2000 dimensions.
-- For 3072-dim vectors, IVFFlat is the option but requires training
-- data (rows). The notes table is typically small enough that a
-- sequential scan is fast. If needed, create after data exists:
-- CREATE INDEX idx_notes_embedding ON notes
-- USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);

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@@ -62,16 +62,23 @@ func SetupTestDB() func() {
return func() {}
}
// Attempt to create the test DB. If the user lacks CREATE DATABASE
// permissions (e.g. CI already created it via admin bootstrap step),
// that's fine — we'll just connect to the existing one.
// Check if test DB already exists (e.g. created by CI bootstrap with
// admin privileges and extensions like pgvector already installed).
// Only create if it doesn't exist — never drop, because recreating
// as the app user would lose extensions that require superuser.
createdByUs := false
adminDB.Exec(fmt.Sprintf("DROP DATABASE IF EXISTS %s", testDBName))
if _, err := adminDB.Exec(fmt.Sprintf("CREATE DATABASE %s", testDBName)); err != nil {
log.Printf("⚠ Cannot CREATE DATABASE %s (will try to connect to existing): %v", testDBName, err)
var dbExists bool
err = adminDB.QueryRow("SELECT 1 FROM pg_database WHERE datname = $1", testDBName).Scan(&dbExists)
if err != nil {
// DB doesn't exist — create it
if _, err := adminDB.Exec(fmt.Sprintf("CREATE DATABASE %s", testDBName)); err != nil {
log.Printf("⚠ Cannot CREATE DATABASE %s (will try to connect to existing): %v", testDBName, err)
} else {
createdByUs = true
log.Printf("✓ Created test database: %s", testDBName)
}
} else {
createdByUs = true
log.Printf("✓ Created test database: %s", testDBName)
log.Printf("✓ Test database %s already exists (keeping extensions)", testDBName)
}
// Build DSN for the test DB
@@ -100,7 +107,7 @@ func SetupTestDB() func() {
TestDB = DB
// Ensure required extensions (may already exist from CI bootstrap)
for _, ext := range []string{"uuid-ossp", "pgcrypto"} {
for _, ext := range []string{"uuid-ossp", "pgcrypto", "vector"} {
DB.Exec(fmt.Sprintf(`CREATE EXTENSION IF NOT EXISTS "%s"`, ext))
}
@@ -166,6 +173,10 @@ func TruncateAll(t *testing.T) {
"messages",
"channel_models",
"channel_members",
"channel_knowledge_bases",
"kb_chunks",
"kb_documents",
"knowledge_bases",
"channels",
"user_model_settings",
"model_catalog",