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james.maesandClaude Opus 5.5 c487c87051 feat: RAG over instance content, permission-filtered through the UI API (P-f)
- Embeddings: EmbeddingProvider SPI, OpenAI-compatible /embeddings
  (batching, Azure path), assistant_model.model_kind CHAT/EMBEDDING and
  embedding_dimensions; chat selection ignores embedding models.
- VectorStore SPI: in-memory store, and the new qbit-assistant-rag-pgvector
  module (one schema per instance, HNSW cosine index, parameterized SQL).
  The index holds NO record content: table, key, field, chunk, hash and
  vector only.
- assistant_rag_source (Knowledge sources) with Index now / Clear index
  record actions that read through the UI API as the clicking admin,
  skip unchanged chunks and drop removed records.
- search_knowledge tool: vector search, then every hit re-read through the
  UI API with the asking user's session (403/404 hits dropped), AI field
  exposure and masking applied, /app citations; PHI rule for embeddings;
  classification raised by results.
- pgvector container test (pgvector/pgvector:pg16) passes with Docker.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-13 19:51:40 -05:00

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