Dom e8a0fb0e42 feat(competences): extract batch candidates

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..

_bench_t2a_out

backup: snapshot post-démo GHT 2026-05-19

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analyze_bench_results.py

backup: snapshot post-démo GHT 2026-05-19

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append_excel_steps_interop.py

backup: snapshot post-démo GHT 2026-05-19

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bench_safety_checks_models.py

feat(qw4): bench rigoureux LLM safety_checks → gemma4:latest par défaut

2026-05-06 09:23:09 +02:00

bench_t2a_post_fix.py

backup: snapshot post-démo GHT 2026-05-19

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benchmark_grounding.py

feat(grounding): pipeline centralisé + serveur UI-TARS transformers + nettoyage code mort

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benchmark_medgemma_demo.py

backup: snapshot post-démo GHT 2026-05-19

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competence_validator.py

feat(competences): extract batch candidates

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duplicate_demo_urgence_2_interop.py

backup: snapshot post-démo GHT 2026-05-19

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duplicate_demo_urgence_3_db.py

backup: snapshot post-démo GHT 2026-05-19

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extract_competences_from_session.py

feat(competences): extract batch candidates

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lea_bench_ollama.py

feat(evaluation): add local Ollama LeaBench adapter

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lea_bench.py

feat(evaluation): add LeaBench computer-use scorer

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probe_qwen3vl_processor.py

backup: snapshot post-démo GHT 2026-05-19

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run_session_cleaner.sh

feat: session_cleaner — outil leger de nettoyage de sessions avant replay

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session_cleaner.py

feat: journée 17 avril — tests E2E validés, dashboard fleet+audit, VWB bridge, cleaner C2

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start_grounding_server.sh

feat(grounding): pipeline centralisé + serveur UI-TARS transformers + nettoyage code mort

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test_instruction.sh

chore: sauvegarde pré-stabilisation — audit 66/66 tests OK

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test_replay_e2e.py

test(e2e): harness replay reproductible — mock client Léa V1 contre serveur réel

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