2cfcfdd1af
Phase 2.6.1: co_occurrence_edges migration - build_co_occurrence_edges_from_qdrant() - Qdrant embeddings → frame grouping → YOLO objects - Result: 6679 edges (vs 6701 PostgreSQL) Phase 2.6.2: face_face_edges migration - build_face_face_edges_from_qdrant() - Qdrant embeddings → frame grouping → face pairs - mutual_gaze detection preserved - Result: 6 edges (exact match) Phase 2.6.3: speaker_face_edges migration - build_speaker_face_edges_from_qdrant() - Qdrant embeddings → trace_id frame ranges - SPEAKS_AS edge creation Architecture: - All edges use Qdrant payload (no face_detections queries) - PostgreSQL fallback for empty Qdrant - Estimated 3.6x performance improvement Testing: - Playground (3003): ✓ All Phase 2.6 logs verified - Edge counts: ✓ Close match with PostgreSQL - Fallback: ✓ Working Docs: - docs_v1.0/DESIGN/TKG_PHASE2_6_EDGES_MIGRATION.md - docs_v1.0/M4_workspace/2026-06-21_phase2_6_test.md
25 lines
584 B
Bash
Executable File
25 lines
584 B
Bash
Executable File
#!/bin/bash
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# Start Gemma 2 9B with MLX
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PORT=8083
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MODEL="mlx-community/gemma-2-9b-it-4bit"
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LOG_FILE="/Users/accusys/momentry_core/logs/gemma2_9b_mlx_8083.log"
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# Kill existing process if running
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if lsof -i :$PORT > /dev/null 2>&1; then
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OLD_PID=$(lsof -i :$PORT | awk 'NR>1 {print $2}')
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kill $OLD_PID
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sleep 2
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fi
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# Start MLX server
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nohup python3 -m mlx_lm.server \
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--model $MODEL \
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--host 0.0.0.0 \
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--port $PORT \
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> $LOG_FILE 2>&1 &
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echo "Gemma 2 9B MLX started on port $PORT"
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echo "Log file: $LOG_FILE"
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echo "Health check: http://localhost:$PORT/health"
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