7439540f8f
Captures the design language (CONTEXT.md) and the framing decisions from the requirements interview: pursue hybrid embeddings+concept-graph retrieval gated on a benchmark (0001), target the API/Postgres deployment while SQLite stays lexical (0002), and permit hosted embedding APIs for non-sensitive memories only (0003). Groundwork for the research/prototype/benchmark effort. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
19 lines
1 KiB
Markdown
19 lines
1 KiB
Markdown
# External embedding/extraction APIs allowed for non-sensitive memories
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Embedding and concept extraction may use **hosted APIs** (e.g. OpenAI `text-embedding-3`,
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Voyage, Cohere) for **non-sensitive** memories, to access a higher quality ceiling than
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self-hosted models alone. **Sensitive / Vault-encrypted (secret) memories are never sent
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externally** and are excluded from the corpus that gets embedded or extracted.
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This is a deliberate relaxation of the homelab's usual local-only posture, made because the
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quality gain is worth it for non-secret personal memory content. The research/benchmark may
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still compare hosted vs self-hostable models (nomic-embed, bge-m3, gte-Qwen2, e5) so the
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production choice is data-driven; this ADR only records that egress is *permitted* within the
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sensitive-data boundary.
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## Consequences
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- The corpus-export step MUST filter out `is_sensitive` / secret memories before any external
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call.
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- Production deployment needs an embedding API key (or falls back to the in-cluster
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llama-cpp model when absent).
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