The provider-agnostic vector store stack (VectorStore::Pgvector + the
Embeddable concern) already shipped to main. This PR closes the
Anthropic loop:
- VectorStore::Registry.adapter_name now returns :pgvector when
Setting.llm_provider == "anthropic" and no explicit
VECTOR_STORE_PROVIDER override is set. Anthropic has no hosted vector
store, so falling back to the local pgvector adapter is the only
correct default. Explicit VECTOR_STORE_PROVIDER still wins.
- SearchFamilyFiles surfaces a longer message when no adapter is wired
up — calling out pgvector + EMBEDDING_URI_BASE as the supported
Anthropic-only path so the user is not stuck with an "OpenAI required"
hint that is no longer accurate.
The Embeddable concern already pulls embeddings from
EMBEDDING_URI_BASE / EMBEDDING_ACCESS_TOKEN (with OpenAI as fallback),
so Anthropic installs point this at Voyage AI, a local Ollama instance,
or OpenAI embeddings — independent of the chat provider.
Tests cover the new default routing, the existing OpenAI default
staying intact, and explicit VECTOR_STORE_PROVIDER overriding the
Anthropic default.
Stacked on #1985 (PR 3/5). 5/5 settings UI + retention disclosure next.
* Add SearchFamilyImportedFiles assistant function with vector store support
Implement per-Family document search using OpenAI vector stores, allowing
the AI assistant to search through uploaded financial documents (tax returns,
statements, contracts, etc.). The architecture is modular with a provider-
agnostic VectorStoreConcept interface so other RAG backends can be added.
Key components:
- Assistant::Function::SearchFamilyImportedFiles - tool callable from any LLM
- Provider::VectorStoreConcept - abstract vector store interface
- Provider::Openai vector store methods (create, upload, search, delete)
- Family::VectorSearchable concern with document management
- FamilyDocument model for tracking uploaded files
- Migration adding vector_store_id to families and family_documents table
https://claude.ai/code/session_01TSkKc7a9Yu2ugm1RvSf4dh
* Extract VectorStore adapter layer for swappable backends
Replace the Provider::VectorStoreConcept mixin with a standalone adapter
architecture under VectorStore::. This cleanly separates vector store
concerns from the LLM provider and makes it trivial to swap backends.
Components:
- VectorStore::Base — abstract interface (create/delete/upload/remove/search)
- VectorStore::Openai — uses ruby-openai gem's native vector_stores.search
- VectorStore::Pgvector — skeleton for local pgvector + embedding model
- VectorStore::Qdrant — skeleton for Qdrant vector DB
- VectorStore::Registry — resolves adapter from VECTOR_STORE_PROVIDER env
- VectorStore::Response — success/failure wrapper (like Provider::Response)
Consumers updated to go through VectorStore.adapter:
- Family::VectorSearchable
- Assistant::Function::SearchFamilyImportedFiles
- FamilyDocument
Removed: Provider::VectorStoreConcept, vector store methods from Provider::Openai
https://claude.ai/code/session_01TSkKc7a9Yu2ugm1RvSf4dh
* Add Vector Store configuration docs to ai.md
Documents how to configure the document search feature, covering all
three supported backends (OpenAI, pgvector, Qdrant), environment
variables, Docker Compose examples, supported file types, and privacy
considerations.
https://claude.ai/code/session_01TSkKc7a9Yu2ugm1RvSf4dh
* No need to specify `imported` in code
* Missed a couple more places
* Tiny reordering for the human OCD
* Update app/models/assistant/function/search_family_files.rb
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Signed-off-by: Juan José Mata <jjmata@jjmata.com>
* PR comments
* More PR comments
---------
Signed-off-by: Juan José Mata <jjmata@jjmata.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
