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566dd75c27
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.
78 lines
2.3 KiB
Ruby
78 lines
2.3 KiB
Ruby
class VectorStore::Registry
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ADAPTERS = {
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openai: "VectorStore::Openai",
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pgvector: "VectorStore::Pgvector",
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qdrant: "VectorStore::Qdrant"
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}.freeze
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class << self
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# Returns the configured adapter instance.
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# Reads from VECTOR_STORE_PROVIDER env var, falling back to :openai
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# when OpenAI credentials are present.
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def adapter
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name = adapter_name
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return nil unless name
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build_adapter(name)
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end
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def configured?
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adapter.present?
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end
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def adapter_name
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explicit = ENV["VECTOR_STORE_PROVIDER"].presence
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return explicit.to_sym if explicit && ADAPTERS.key?(explicit.to_sym)
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# Default routing:
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# - When the configured LLM provider is Anthropic (which has no hosted
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# vector store), fall back to the local pgvector adapter. The
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# Embeddable concern still pulls embeddings from EMBEDDING_URI_BASE /
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# OPENAI_ACCESS_TOKEN — Anthropic users typically point this at
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# Voyage AI, a local Ollama instance, or OpenAI embeddings.
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# - Otherwise, use OpenAI when credentials are available.
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return :pgvector if Setting.llm_provider == "anthropic"
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:openai if openai_access_token.present?
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end
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private
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def build_adapter(name)
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klass = ADAPTERS[name]&.safe_constantize
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raise VectorStore::ConfigurationError, "Unknown vector store adapter: #{name}" unless klass
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case name
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when :openai then build_openai
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when :pgvector then build_pgvector
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when :qdrant then build_qdrant
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else raise VectorStore::ConfigurationError, "No builder defined for adapter: #{name}"
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end
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end
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def build_openai
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token = openai_access_token
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return nil unless token.present?
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VectorStore::Openai.new(
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access_token: token,
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uri_base: ENV["OPENAI_URI_BASE"].presence || Setting.openai_uri_base
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)
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end
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def build_pgvector
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VectorStore::Pgvector.new
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end
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def build_qdrant
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url = ENV.fetch("QDRANT_URL", "http://localhost:6333")
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api_key = ENV["QDRANT_API_KEY"].presence
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VectorStore::Qdrant.new(url: url, api_key: api_key)
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end
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def openai_access_token
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ENV["OPENAI_ACCESS_TOKEN"].presence || Setting.openai_access_token
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end
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end
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end
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