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Disable pg_search migrations + override S3_ENDPOINT so LobeChat boots on pgvector pg16
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Browse Source 
- packages/database/migrations/{0090,0093}: comment out pg_search/bm25;
  pgvector/pgvector:pg16 image lacks pg_search.control. Vector RAG via
  pgvector still works; only BM25 full-text search is unavailable.
- docker-compose.yml: set S3_ENDPOINT to placeholder URL so the
  zod url() validator accepts it. Image bakes ENV S3_ENDPOINT='' which
  fails validation. This prototype does not use S3 file uploads.
This commit is contained in:
xiaohei
2026-04-21 13:35:39 +08:00
parent 20ef7c841a
commit 43b25769be
3 changed files with 10 additions and 216 deletions
Download Patch File Download Diff File Expand all files Collapse all files
packages/database/migrations/0090_enable_pg_search.sql
+4 -2
View File
@@ -1,2 +1,4 @@
-- Custom SQL migration file, put your code below! --
CREATE EXTENSION IF NOT EXISTS pg_search;
-- Disabled in local Docker prototype: pg_search extension not available in
-- pgvector/pgvector:pg16 image. BM25 full-text search will be unavailable.
-- Chat, RAG (via pgvector), tools, agents remain functional.
SELECT 1;
packages/database/migrations/0093_add_bm25_indexes_with_icu.sql
+2 -214
View File
@@ -1,214 +1,2 @@
-- Custom SQL migration file, put your code below! --
-- All tables include user_id (keyword tokenizer + fast) for filter pushdown into tantivy index scan.
-- Enum/filter fields (type, status, role, etc.) use keyword+fast for the same reason.
-- Large tables (documents, messages) are placed last to avoid blocking smaller index builds.
-- 1. agents: title, description, slug, tags(jsonb), system_role, user_id
DROP INDEX IF EXISTS agents_bm25_idx;--> statement-breakpoint
CREATE INDEX agents_bm25_idx ON agents
USING bm25 (id, title, description, slug, tags, system_role, user_id)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"slug": {"tokenizer": {"type": "icu"}},
"system_role": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}',
json_fields = '{
"tags": {"tokenizer": {"type": "icu"}}
}'
);--> statement-breakpoint
-- 2. topics: title, content, description, user_id
DROP INDEX IF EXISTS topics_bm25_idx;--> statement-breakpoint
CREATE INDEX topics_bm25_idx ON topics
USING bm25 (id, title, content, description, user_id)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"content": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 3. files: name, user_id, file_type
DROP INDEX IF EXISTS files_bm25_idx;--> statement-breakpoint
CREATE INDEX files_bm25_idx ON files
USING bm25 (id, name, user_id, file_type)
WITH (
key_field = 'id',
text_fields = '{
"name": {"tokenizer": {"type": "icu"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}},
"file_type": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 4. knowledge_bases: name, description, user_id
DROP INDEX IF EXISTS knowledge_bases_bm25_idx;--> statement-breakpoint
CREATE INDEX knowledge_bases_bm25_idx ON knowledge_bases
USING bm25 (id, name, description, user_id)
WITH (
key_field = 'id',
text_fields = '{
"name": {"tokenizer": {"type": "icu"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 5. user_memories: title, summary, details, memory_layer, memory_category, status, user_id
DROP INDEX IF EXISTS user_memories_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_bm25_idx ON user_memories
USING bm25 (id, title, summary, details, memory_layer, memory_category, status, user_id)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"summary": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"details": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"memory_layer": {"fast": true, "tokenizer": {"type": "keyword"}},
"memory_category": {"fast": true, "tokenizer": {"type": "keyword"}},
"status": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 6. chat_groups: title, description, content, user_id
DROP INDEX IF EXISTS chat_groups_bm25_idx;--> statement-breakpoint
CREATE INDEX chat_groups_bm25_idx ON chat_groups
USING bm25 (id, title, description, content, user_id)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"content": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 7. user_memories_contexts: title, description, current_status, type, user_id
DROP INDEX IF EXISTS user_memories_contexts_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_contexts_bm25_idx ON user_memories_contexts
USING bm25 (id, title, description, current_status, type, user_id)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"current_status": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"type": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 8. user_memories_preferences: conclusion_directives, suggestions, type, user_id
DROP INDEX IF EXISTS user_memories_preferences_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_preferences_bm25_idx ON user_memories_preferences
USING bm25 (id, conclusion_directives, suggestions, type, user_id)
WITH (
key_field = 'id',
text_fields = '{
"conclusion_directives": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"suggestions": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"type": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 9. user_memories_activities: notes, narrative, feedback, type, status, user_id
DROP INDEX IF EXISTS user_memories_activities_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_activities_bm25_idx ON user_memories_activities
USING bm25 (id, notes, narrative, feedback, type, status, user_id)
WITH (
key_field = 'id',
text_fields = '{
"notes": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"narrative": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"feedback": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"type": {"fast": true, "tokenizer": {"type": "keyword"}},
"status": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 10. user_memories_identities: description, role, type, relationship, user_id
DROP INDEX IF EXISTS user_memories_identities_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_identities_bm25_idx ON user_memories_identities
USING bm25 (id, description, role, type, relationship, user_id)
WITH (
key_field = 'id',
text_fields = '{
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"role": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"type": {"fast": true, "tokenizer": {"type": "keyword"}},
"relationship": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 11. user_memories_experiences: situation, reasoning, possible_outcome, action, key_learning, type, user_id
DROP INDEX IF EXISTS user_memories_experiences_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memories_experiences_bm25_idx ON user_memories_experiences
USING bm25 (id, situation, reasoning, possible_outcome, action, key_learning, type, user_id)
WITH (
key_field = 'id',
text_fields = '{
"situation": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"reasoning": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"possible_outcome": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"action": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"key_learning": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"type": {"fast": true, "tokenizer": {"type": "keyword"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 12. user_memory_persona_documents: tagline, persona, user_id
DROP INDEX IF EXISTS user_memory_persona_documents_bm25_idx;--> statement-breakpoint
CREATE INDEX user_memory_persona_documents_bm25_idx ON user_memory_persona_documents
USING bm25 (id, tagline, persona, user_id)
WITH (
key_field = 'id',
text_fields = '{
"tagline": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"persona": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 13. documents (large table): title, description, content, slug, user_id, file_type, source_type
DROP INDEX IF EXISTS documents_bm25_idx;--> statement-breakpoint
CREATE INDEX documents_bm25_idx ON documents
USING bm25 (id, title, description, content, slug, user_id, file_type, source_type)
WITH (
key_field = 'id',
text_fields = '{
"title": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"description": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"content": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"slug": {"tokenizer": {"type": "icu"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}},
"file_type": {"fast": true, "tokenizer": {"type": "keyword"}},
"source_type": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);--> statement-breakpoint
-- 14. messages (largest table): content, summary, user_id, role
DROP INDEX IF EXISTS messages_bm25_idx;--> statement-breakpoint
CREATE INDEX messages_bm25_idx ON messages
USING bm25 (id, content, summary, user_id, role)
WITH (
key_field = 'id',
text_fields = '{
"content": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"summary": {"tokenizer": {"type": "icu", "stemmer": "English", "stopwords_language": "English"}},
"user_id": {"fast": true, "tokenizer": {"type": "keyword"}},
"role": {"fast": true, "tokenizer": {"type": "keyword"}}
}'
);
-- Disabled: depends on pg_search (see 0090).
SELECT 1;