Resolves validation failures where LLM fabricated full UUIDs from 8-char prefixes shown in context, causing 'unknown product_id' errors. Root Cause Analysis: - Context showed 8-char short IDs: '77cbf37c' (Phase 2 optimization) - Function tool returned full UUIDs: '77cbf37c-3830-4927-...' - LLM saw BOTH formats, got confused, invented UUIDs for final response - Validators rejected fabricated UUIDs as unknown products Solution: Consistent 8-char short_id across LLM boundary: 1. Database: New short_id column (8 chars, unique, indexed) 2. Context: Shows short_id (was: str(id)[:8]) 3. Function tools: Return short_id (was: full UUID) 4. Translation layer: Expands short_id → UUID before validation 5. Database: Stores full UUIDs (no schema change for existing data) Changes: - Added products.short_id column with unique constraint + index - Migration populates from UUID prefix, handles collisions via regeneration - Product model auto-generates short_id for new products - LLM contexts use product.short_id consistently - Function tools return product.short_id - Added _expand_product_id() translation layer in routines.py - Integrated expansion in suggest_routine() and suggest_batch() - Validators work with full UUIDs (no changes needed) Benefits: ✅ LLM never sees full UUIDs, no format confusion ✅ Maintains Phase 2 token optimization (~85% reduction) ✅ O(1) indexed short_id lookups vs O(n) pattern matching ✅ Unique constraint prevents collisions at DB level ✅ Clean separation: 8-char for LLM, 36-char for application From production error: Step 1: unknown product_id 77cbf37c-3830-4927-9669-07447206689d (LLM invented the last 28 characters) Now resolved: LLM uses '77cbf37c' consistently, translation layer expands to real UUID before validation.
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