Amr Gharbeia
11254b56ec
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1. Wire :foveal-vector into context-awareness-assemble: pass the foveal node's embedding vector to context-object-render. Previously always nil → similarity always 0.0 → no semantic boosting. 2. Replace default :hashing (SHA-256) with :trigram (character-trigram Jaccard). SHA-256 is a cryptographic hash with the avalanche property — one-bit input differences produce entirely different outputs. Useless for similarity. Trigram bloom filter (128-dim) captures lexical overlap in pure Lisp with zero external dependencies: - 'authentication' vs 'authenticate' → 0.80 similarity - 'authentication' vs 'banana' → 0.00 similarity 3. Rename old embedding-backend-hashing → embedding-backend-sha256 (integrity-only, explicit opt-in). Add embedding-backend-trigram. 4. Add test-semantic-retrieval-trigram: related texts > 0.75, unrelated < 0.3. Test: 97/0 across 13 suites (context 12/0, embedding 12/0)