rogee
c72e359e48
- ArticleEmbeddingRepo (new): Upsert, GetByArticleID, DeleteByArticleID, SearchByEmbedding using pgvector cosine distance (vector_embedding column) - ArticleEmbedding model: add VectorEmbedding pgvector.Vector field alongside existing JSONB Embedding (backward compatible) - ArticleService: add SemanticSearch() — generates query embedding via LLM, searches articles by cosine similarity; add GenerateEmbedding() — creates and stores article embedding from title+description+content - ArticleHandler: add SemanticSearch endpoint GET /portals/:portal_id/articles/semantic_search?query=... - bootstrap.go: inject articleEmbeddingRepo + llmProvider into ArticleService - router.go: register /articles/semantic_search route - migration 000049: add vector(1536) column to article_embeddings table, create ivfflat index, migrate existing JSONB data to vector format Verified: go build + go vet + go test all pass
6 lines
226 B
SQL
6 lines
226 B
SQL
-- 000049_add_article_embedding_vector.down.sql
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-- Remove the pgvector column from article_embeddings
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DROP INDEX IF EXISTS idx_article_embeddings_vector;
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ALTER TABLE article_embeddings DROP COLUMN IF EXISTS vector_embedding;
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