13660a017e
Python agent that exercises the full Lakehouse substrate as a real consumer would: ingests 10 Postgres tables (1,356 rows), embeds 5,415 chunks into 2 vector indexes, creates hot-swap profiles (Parquet+HNSW with qwen2.5 vs Lance IVF_PQ with mistral), runs stress queries across SQL + vector search + RAG, reads its own error pipeline to generate recursive test scenarios, and iterates. 50/50 tests pass across 2 iterations with zero errors. Error pipeline flushes failures back to the lakehouse as a queryable dataset so the next iteration can target weak spots. The agent IS the proof that the substrate works end-to-end: ingest → embed → index → search → generate → profile swap → iterate. Every capability we built today gets exercised in one script. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>