# workflows

id: wf_806a420bac54
name: Démo : Traitement batch factures
created_at: 2026-04-18T08:57:02.688695
updated_at: 2026-04-18T08:57:02.688695
source: manual
review_status: approved
description:
  Pipeline complet : import Excel → boucle sur chaque facture → saisie dans le logiciel de facturation → validation.

  Cas d'usage : traiter 8 factures en attente depuis un fichier Excel.


id: wf_603a9fa759ca
name: Démo : Extraction IA depuis écran
created_at: 2026-04-18T08:57:02.688695
updated_at: 2026-04-18T08:57:02.688695
source: manual
review_status: approved
description:
  Léa capture l'écran du logiciel métier, analyse avec l'IA locale (Ollama), extrait les informations clés et les stocke en base de données.

  Cas d'usage : extraire automatiquement les données patient visibles à l'écran.


id: wf_a38aeebea5e6_1778162737
name: Urgence_aiva_demo
tags_json: ["demo","ght","aiva-vision"]
trigger_examples_json: []
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-07 16:05:37.751722
source: manual
description:
  Démo GHT Sud 95 — workflow simplifié aligné sur maquette aiva-vision (1 DPI textarea + Justification + Analyser). Construit le 7 mai 2026.


id: wf_test_etscroll_2026_05_10
name: Test_extract_text_scroll_2026-05-10
tags_json: ["test", "extract_text_scroll", "demo_interne"]
trigger_examples_json: []
created_at: 2026-05-10T16:21:53.020153
updated_at: 2026-05-10T16:21:53.020153
source: manual
description:
  Workflow JOUET pour démontrer le nouveau type extract_text_scroll. Ne pas exécuter en démo client : sert juste à vérifier que le type est accepté en BDD et que le VWB l'affiche.


# visual_anchors

id: anchor_b4f4ea58dec2_1769196042
created_at: 2026-01-23 19:20:42.904579
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b4f4ea58dec2_1769196042_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b4f4ea58dec2_1769196042_thumb.png


id: anchor_956ea7b56ff8_1769196809
created_at: 2026-01-23 19:33:29.248069
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_956ea7b56ff8_1769196809_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_956ea7b56ff8_1769196809_thumb.png


id: anchor_8a3cbb3ee5bb_1769197487
created_at: 2026-01-23 19:44:47.327205
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_8a3cbb3ee5bb_1769197487_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_8a3cbb3ee5bb_1769197487_thumb.png


id: anchor_0c2836b2e973_1769197682
created_at: 2026-01-23 19:48:02.771167
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0c2836b2e973_1769197682_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0c2836b2e973_1769197682_thumb.png


id: anchor_faaab112603a_1769200099
created_at: 2026-01-23 20:28:19.504457
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_faaab112603a_1769200099_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_faaab112603a_1769200099_thumb.png


id: anchor_64ba9e3f9c7c_1769200373
created_at: 2026-01-23 20:32:53.285581
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_64ba9e3f9c7c_1769200373_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_64ba9e3f9c7c_1769200373_thumb.png


id: anchor_319dfe912d42_1769202022
created_at: 2026-01-23 21:00:22.073207
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_319dfe912d42_1769202022_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_319dfe912d42_1769202022_thumb.png


id: anchor_81dff98904fa_1769203030
created_at: 2026-01-23 21:17:10.939458
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_81dff98904fa_1769203030_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_81dff98904fa_1769203030_thumb.png


id: anchor_6aee482db978_1769203064
created_at: 2026-01-23 21:17:44.302848
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6aee482db978_1769203064_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6aee482db978_1769203064_thumb.png


id: anchor_03c42f2ed139_1769203089
created_at: 2026-01-23 21:18:09.440999
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_03c42f2ed139_1769203089_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_03c42f2ed139_1769203089_thumb.png


id: anchor_b0688d5625ce_1769203327
created_at: 2026-01-23 21:22:07.792435
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b0688d5625ce_1769203327_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b0688d5625ce_1769203327_thumb.png


id: anchor_51c04e0e1db5_1769203445
created_at: 2026-01-23 21:24:05.149159
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_51c04e0e1db5_1769203445_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_51c04e0e1db5_1769203445_thumb.png


id: anchor_5e14740aea06_1769213675
created_at: 2026-01-24 00:14:35.678073
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_5e14740aea06_1769213675_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_5e14740aea06_1769213675_thumb.png


id: anchor_b73d32ff6a3a_1770801636
created_at: 2026-02-11 09:20:36.443540
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b73d32ff6a3a_1770801636_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_b73d32ff6a3a_1770801636_thumb.png


id: anchor_c7c0b9088949_1773728901
created_at: 2026-03-17 06:28:21.774264
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c7c0b9088949_1773728901_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c7c0b9088949_1773728901_thumb.png


id: anchor_4439b64e3caa_1773736394
created_at: 2026-03-17 08:33:15.037649
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4439b64e3caa_1773736394_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4439b64e3caa_1773736394_thumb.png


id: anchor_d1225c82da1b_1773737966
created_at: 2026-03-17 08:59:26.902310
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d1225c82da1b_1773737966_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d1225c82da1b_1773737966_thumb.png


id: anchor_471082f0e00d_1773738121
created_at: 2026-03-17 09:02:01.582689
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_471082f0e00d_1773738121_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_471082f0e00d_1773738121_thumb.png


id: anchor_6922a0f202af_1773752674
created_at: 2026-03-17 13:04:34.821242
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6922a0f202af_1773752674_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6922a0f202af_1773752674_thumb.png


id: anchor_e1aac27739bc_1773753053
created_at: 2026-03-17 13:10:53.816117
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e1aac27739bc_1773753053_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e1aac27739bc_1773753053_thumb.png


id: anchor_c9cc912d3fa3_1773753143
created_at: 2026-03-17 13:12:23.320795
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c9cc912d3fa3_1773753143_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c9cc912d3fa3_1773753143_thumb.png


id: anchor_ce7793f20dc4_1773786531
created_at: 2026-03-17 22:28:51.665317
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_ce7793f20dc4_1773786531_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_ce7793f20dc4_1773786531_thumb.png


id: anchor_0c0a348a78a0_1773826365
created_at: 2026-03-18 09:32:46.450888
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0c0a348a78a0_1773826365_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0c0a348a78a0_1773826365_thumb.png


id: anchor_4b54f1114b51_1773828865
created_at: 2026-03-18 10:14:25.145783
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4b54f1114b51_1773828865_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4b54f1114b51_1773828865_thumb.png


id: anchor_e54628b75227_1773829452
created_at: 2026-03-18 10:24:12.285852
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e54628b75227_1773829452_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e54628b75227_1773829452_thumb.png


id: anchor_dd32b09238ca_1773833606
created_at: 2026-03-18 11:33:26.599135
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_dd32b09238ca_1773833606_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_dd32b09238ca_1773833606_thumb.png


id: anchor_2d51b88900d7_1773833805
created_at: 2026-03-18 11:36:45.853678
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_2d51b88900d7_1773833805_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_2d51b88900d7_1773833805_thumb.png


id: anchor_e699f12dea5d_1776523946
created_at: 2026-04-18 14:52:27.112921
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e699f12dea5d_1776523946_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_e699f12dea5d_1776523946_thumb.png


id: anchor_04532e157999_1776524087
created_at: 2026-04-18 14:54:47.349203
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_04532e157999_1776524087_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_04532e157999_1776524087_thumb.png


id: anchor_c4784649c3f7_1776524106
created_at: 2026-04-18 14:55:06.444842
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c4784649c3f7_1776524106_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c4784649c3f7_1776524106_thumb.png


id: anchor_5a56db01200d_1776534190
created_at: 2026-04-18 17:43:10.244097
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_5a56db01200d_1776534190_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_5a56db01200d_1776534190_thumb.png


id: anchor_1874fab6cb2d_1776586868
created_at: 2026-04-19 08:21:08.417045
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1874fab6cb2d_1776586868_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1874fab6cb2d_1776586868_thumb.png


id: anchor_4483b2b8c0b8_1776591775
created_at: 2026-04-19 09:42:55.454058
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4483b2b8c0b8_1776591775_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4483b2b8c0b8_1776591775_thumb.png


id: anchor_6a2d95e5e8ca_1776591968
created_at: 2026-04-19 09:46:08.418251
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6a2d95e5e8ca_1776591968_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6a2d95e5e8ca_1776591968_thumb.png


id: anchor_d438bb353be7_1776591997
created_at: 2026-04-19 09:46:38.018255
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d438bb353be7_1776591997_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d438bb353be7_1776591997_thumb.png


id: anchor_61cc3fb364e0_1776592347
created_at: 2026-04-19 09:52:28.070119
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_61cc3fb364e0_1776592347_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_61cc3fb364e0_1776592347_thumb.png


id: anchor_21bba6b6c341_1776611920
created_at: 2026-04-19 15:18:40.975232
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_21bba6b6c341_1776611920_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_21bba6b6c341_1776611920_thumb.png


id: anchor_057327ea792b_1776752947
created_at: 2026-04-21 06:29:08.045552
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_057327ea792b_1776752947_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_057327ea792b_1776752947_thumb.png


id: anchor_54bc07f31fa2_1776753841
created_at: 2026-04-21 06:44:01.369695
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_54bc07f31fa2_1776753841_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_54bc07f31fa2_1776753841_thumb.png


id: anchor_917976585f0d_1776753856
created_at: 2026-04-21 06:44:16.696167
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_917976585f0d_1776753856_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_917976585f0d_1776753856_thumb.png


id: anchor_1aab89528bbb_1776754033
created_at: 2026-04-21 06:47:13.149652
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1aab89528bbb_1776754033_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1aab89528bbb_1776754033_thumb.png


id: anchor_f1d6079bcbd4_1776755196
created_at: 2026-04-21 07:06:36.634225
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_f1d6079bcbd4_1776755196_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_f1d6079bcbd4_1776755196_thumb.png


id: anchor_feced7833ae6_1776755329
created_at: 2026-04-21 07:08:49.194685
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_feced7833ae6_1776755329_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_feced7833ae6_1776755329_thumb.png


id: anchor_1a7fe1d6ebc1_1776772886
description: - -
created_at: 2026-04-21 12:01:26.653876
capture_method: screen_capture
target_text: - -
ocr_description: - -
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1a7fe1d6ebc1_1776772886_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1a7fe1d6ebc1_1776772886_thumb.png


id: anchor_410afea7073e_1776772869
created_at: 2026-04-21 12:01:26.802250
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_410afea7073e_1776772869_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_410afea7073e_1776772869_thumb.png


id: anchor_c47602cedc05_1776773318
description: emo
created_at: 2026-04-21 12:08:39.380768
capture_method: screen_capture
target_text: emo
ocr_description: Folder icon named Demo
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c47602cedc05_1776773318_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c47602cedc05_1776773318_thumb.png


id: anchor_be5bf2b0088b_1776773876
description: CR_patient demo
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target_text: CR_patient demo
ocr_description: File icon named CR_patient_demo
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id: anchor_fdfc0baf59e6_1776774010
description: - -
created_at: 2026-04-21 12:20:10.400137
capture_method: screen_capture
target_text: File icon named Fichier
ocr_description: File icon named Fichier
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id: anchor_b8ae007cfb07_1776784723
description: - C
created_at: 2026-04-21 15:18:44.266323
capture_method: screen_capture
target_text: Search bar with magnifier icon.
ocr_description: Search bar with magnifier icon.
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id: anchor_f4ee64c796b1_1776784765
description: - C
created_at: 2026-04-21 15:19:25.546836
capture_method: screen_capture
target_text: Search bar with magnifier icon.
ocr_description: Search bar with magnifier icon.
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id: anchor_9ae247db4408_1776784857
description: Ouvrir Nouveau document Nouvelle feuille de calcul
created_at: 2026-04-21 15:20:58.165262
capture_method: screen_capture
target_text: Ouvrir Nouveau document Nouvelle feuille de calcul
ocr_description: Ouvrir Nouveau document Nouvelle feuille de calcul
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id: anchor_42f88df6fbff_1776784879
description: Nouveau - doc # Nouvelle feu Nouvelle pre
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target_text: Nouveau - doc # Nouvelle feu Nouvelle pre
ocr_description: Nouveau - doc # Nouvelle feu Nouvelle pre
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id: anchor_ab3b0bdcbfbf_1776784888
description: Nouveau document Nouvelle feuille de calcul Nouvelle présentation
created_at: 2026-04-21 15:21:28.637341
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target_text: Nouvelle feuille de calcul
ocr_description: New spreadsheet icon
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id: anchor_f7f42b73e699_1776950513
description: Home button with 'Accueil - Henne' text.
created_at: 2026-04-23 13:21:56.973393
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target_text: Accueil - Henner Dépôt de pièc...
ocr_description: Home button with 'Accueil - Henne' text.
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id: anchor_4a36bac6c830_1776950738
description: Previsua aliser/Appliquer sur un échantillon: N OGC:21 FICHE VIEDICALE DE RI Seul le reco
created_at: 2026-04-23 13:25:38.690602
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target_text: Previsua aliser/Appliquer sur un échantillon: N OGC:21 FICHE VIEDICALE DE RI Seul le reco
ocr_description: Previsua aliser/Appliquer sur un échantillon: N OGC:21 FICHE VIEDICALE DE RI Seul le reco
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id: anchor_c286742d2b27_1777188109
description: 4 - - -
created_at: 2026-04-26 07:21:53.428603
capture_method: screen_capture
target_text: 4 - - -
ocr_description: 4 - - -
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id: anchor_9770845a0054_1777188094
created_at: 2026-04-26 07:21:53.429067
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id: anchor_67fa8e31b79d_1777188080
description: - - 1 -
created_at: 2026-04-26 07:21:53.429448
capture_method: screen_capture
target_text: - - 1 -
ocr_description: - - 1 -
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id: anchor_a13037fc2012_1777480229
description: Blue bar with text
created_at: 2026-04-29 16:30:33.370123
capture_method: screen_capture
ocr_description: Blue bar with text
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target_text:
  Claude - I Claude DD D Al Voice Generator... Easily Assure Urgences - Maquette POC Patients Planning Dossier en cours Codage T2A Sta


id: anchor_d1be6121b2af_1777489580
description: Input field with placeholder text.
created_at: 2026-04-29 19:06:51.839903
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target_text: Papsayes - AuYenLes m - Saisir un IPP ou un nom...
ocr_description: Input field with placeholder text.
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id: anchor_0b47fabbea12_1777489591
description: Input field with placeholder text.
created_at: 2026-04-29 19:06:52.222227
capture_method: screen_capture
target_text: Papsayes - AuYenLes m - Saisir un IPP ou un nom...
ocr_description: Input field with placeholder text.
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id: anchor_06cc0919f7e5_1777489599
description: Input field for IP or name.
created_at: 2026-04-29 19:06:52.651198
capture_method: screen_capture
target_text: Papsayes - AuYenLes m - Saisir un IPP ou un nom...
ocr_description: Input field for IP or name.
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id: anchor_8e345f114ca4_1777489609
description: Input field for IP or name.
created_at: 2026-04-29 19:06:53.429926
capture_method: screen_capture
target_text: Papsayes - AuYenLes m - Saisir un IPP ou un nom...
ocr_description: Input field for IP or name.
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id: anchor_14d665a55f1d_1777490197
description: Search button with magnifier icon.
created_at: 2026-04-29 19:16:40.733421
capture_method: screen_capture
target_text: ces Rechercher Prénom
ocr_description: Search button with magnifier icon.
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id: anchor_69b2c91fb615_1777490306
description: IP address displayed.
created_at: 2026-04-29 19:18:26.833756
capture_method: screen_capture
target_text: Patients Planning Dossier IPP: 25003284 MOREL . Ca : - - - 3 cio
ocr_description: IP address displayed.
image_path:
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id: anchor_7a8fdcd69290_1777561991
description: Liste des passages aux urgences
created_at: 2026-04-30 15:13:14.377144
capture_method: screen_capture
ocr_description: Liste des passages aux urgences
image_path:
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target_text:
  raucCIILS nammy couaye 5 LGLISLIyues riue Liste des passages aux urgences TPP / Nom - Saisir un IPP ou un. nom Rechercher


id: anchor_e8f1ed9cc27d_1777563217
description: 25003284
created_at: 2026-04-30 15:33:40.737852
capture_method: screen_capture
target_text: IPP No 25003284 MC 25003362 LA
ocr_description: 25003284
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id: anchor_d1a0f310ccff_1777563577
description: Table with patient data.
created_at: 2026-04-30 15:39:43.735615
capture_method: screen_capture
ocr_description: Table with patient data.
image_path:
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target_text:
  IPP /Nom : Saisir un IPP out un nom... Rechercher Date 01/01/2025 IPP Nom Prénom Né(e) le Arrivée Motif Médecin Statut 25003284 MOREL Catherine 14/03/1947 01/01/2025 03:12 Asthme BONNET Antoine Sortie 25003362 LAFFONT Alice 08/05/2021 01/01/2025 13:49 Intoxication médicamenteuse THOMAS Sandrine Sortie 25003364 LEROY Bernard 07/03/1953 01/01/2025 13:55 Dyspnée SIMON Hélène Hospitalisé 25003451 ROUX Lou 12/06/2021 01/01/2025 20:19 Dermabrasion / plaie ROBERT Julien Sortie 25003475 PERRIN Marion 18/06/1990 01/01/2025 23:27 Céphalée + paresthésie MEUNIERI David Sortie 25005866 MARTINS Diego 11/02/2007 03/01/2025 22:59 Trauma crânien hockey ROBERT Julien Sortie 25010621 FAURE Tom 03/11/2019 09/01/2025 12:50 Dyspnée / laryngite MARCHAND Sophie Sortie 25012257 BRUNEL Henri 23/05/1948 11/01/2025 06:40 Douleur abdominale DUMONT Sarah Sortie 25048485 NGUYEN Léo 15/09/2011 28/02/2025 10:40 Crise convulsive MARCHAND Sophie Sortie 25056615 PIRES Camille 22/04/1985 12/03/2025 16:30 Douleur fosse iliaque G MORIN Lucas Transfert 25151530 DA: SILVA Manuel 12/11/1966 25/07/2025 03:25 Colique néphrétique ROUSSEAU Camille Sortie Cliquer sur un IPP pour ouvrir le dossier patient correspondant. 11 dossiers cliniques (4 UHCD, 3 Forfaits PE2 pédia, 1 Forfait SU2 acte CCAM, 2 Forfaits Standard, icas pilote asthme/VRS) tous identifiants anonymisés.


id: anchor_f9bbb873c964_1777565422
description: Menu icon with 'File' option.
created_at: 2026-04-30 16:10:25.871574
capture_method: screen_capture
target_text: IPP: 25003284 MORELC Motif & IDE Examens clini Motif de la venue
ocr_description: Menu icon with 'File' option.
image_path:
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id: anchor_e584dad8e54e_1777565484
description: Table with columns and rows.
created_at: 2026-04-30 16:11:25.307647
capture_method: screen_capture
ocr_description: Table with columns and rows.
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target_text:
  w B - a - E Easily Assure urgences Maquette POC Patients Planning Dossier en cours Codage T2A Statistique IPP : 25003284 MOREL Catherine Né(e) le 14/03/1947 I 77 a


id: anchor_2ce7fb5e527b_1777565794
description: Motif & IDE
created_at: 2026-04-30 16:16:37.046985
capture_method: screen_capture
target_text: IPP: 25003284 MOREL C Motit & IDE Examens clini I V . IT d L venue
ocr_description: Motif & IDE
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id: anchor_fb9cf5270f95_1777565819
description: Medical record screenshot.
created_at: 2026-04-30 16:17:07.145046
capture_method: screen_capture
ocr_description: Medical record screenshot.
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target_text:
  Patients Planning Dossier en cours Codage T2A Statistiques IPP : 25003284 MOREL Catherine Né(e) lei 14/03/1947 77ans I Sexe :F Arrivée 01/01/2025 03:12 I IAO CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif F&IDE Examens cliniques Notes médicales Synthèse Urgences Codage T2A > Motif del la venue Symptômes à l'orientation: 01/01/2025 03:31 CARON Sandrine Asthme Observations IDE Description Date Dernière modif par depuis 23h, quintes det toux sèche 01/01/2025 03:31 CARON Sandrine apris 2+2Bde VENTO = inefficace 01/01/2025 03:31 contage familial, vacciné grippe etc COVIDilya3sem ATCD =a asthme, insuf coronarienne TTT = RESITUNE, INNOVAIR, SINGULAIR, ALLERGIE =0 enl IOA = HYPERTHERME, masque mis, toux sèche, bon débit de parole, PEAKFLOW 260 TEST Ag COVID fait etl NEGATIF V Diagnostics 112.1_Pneumopathie-dueauvirusrrespiratoiresyyncytial(VRSLICMA2) Principal 01/01/2025 06:45 DR. Antoine BONNET Signes vitaux résumé Item de surveillance 01/01/2025 05:13 01/01/2025 03:25 Température oC 39,4 39,3 Pouls bt/min 117 91 PAS Systolique mmHg 136 PAI Diastolique mmHg 61 PAN Moyenne 86 Saturation 02 % 96 95 Fréq. respiratoire br/min 20 Ventilation Ventilation spontanée Air ambiant


id: anchor_3ecfe3f695ac_1777565884
description: Examens cliniques
created_at: 2026-04-30 16:18:05.097155
capture_method: screen_capture
target_text: 284 MOREL Catherine Né(e) le a 14 - Examens cliniques Notes médical a venue
ocr_description: Examens cliniques
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id: anchor_2cc4d2b1b2d4_1777565934
description: Exams cliniques' tab
created_at: 2026-04-30 16:19:01.662842
capture_method: screen_capture
ocr_description: Exams cliniques' tab
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target_text:
  IPP : 25003284 MOREL Catherine Né(e) le 14/03/1947 1 77 ans I Sexe: F Arrivée 01/01/2025 03:12 I IAO: CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif&IDE Examens dliniques Notes médicales Synthèsel Urgences Codage T2A: > Examens Cliniques Questionnaire Score Réponse significative 1 Etat Dernière modification le Motif de suppression Examen clinique(Général) Synthèse Examen Clinique: : Note del l'examen clinique: : Verrouillé 01/01/2025 04:06 ABONNET fébrileà 39 Conscience OK bien orienté RAS Ventilation: léger frein expi, finit ses phrases. Sibilants bilat pas def foyer CV:fc 90 pas de choc pas d'ic Abdomen RAS Avis Spécialisés Recherche Aucun avis spécialisé enregistré Notes paramédicales Recherche 01/01/2025 04:01 NoteIDE noté par Marie LEGRAND (Infirmier en puériculture), 01/01/2025 06:59 Enregistré Aeu BS+P pose KT. Aérosols X3 selon PM. Devenir: Retour au domicile après ablation KT.


id: anchor_3e47e9de0562_1777565966
description: Notes médicales
created_at: 2026-04-30 16:19:27.466802
capture_method: screen_capture
target_text: erine Né(e) le 14/03/1947 I // ans es Notes médicales Synthèse Urg
ocr_description: Notes médicales
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id: anchor_94792774d3e9_1777566772
description: Notes médicales tab
created_at: 2026-04-30 16:33:00.831285
capture_method: screen_capture
ocr_description: Notes médicales tab
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target_text:
  IPP : 25003284 MOREL Catherine Né(e) le 14/03/1947 I 77 ans I Sexe F Arrivée 01/01/2025 03:12 I IAO: CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif&IDE Examens cliniques Notes médicales Synthèsel Urgences Codage T2A> Notes médicales Recherche 01/01/2025 06:44 Conclusion Obs. médicales noté par DR. Antoinel BONNET (Médecin), 01/01/2025 06:44 Verrouillé Infection à VRS sans signe de gravité respiratoire mais probable début de surinfection base gauche. Mis sous augmentin comptet tenu dut terrain cardiovasculaire Ventoline 1bouffée: x3/j Refaire lep point à 48h 01/01/2025 06:43 Noted'évolution noté par DR. Antoine BONNET (Médecin), 01/01/2025 06:43 Verrouillé Nettement amélioré par les aérosols 01/01/2025 06:37 Noted'évolution noté par DR. Antoine BONNET (Médecin), 01/01/2025 06:43 Corrigé Bio 11000GB CRP 25 PCR VRS + 01/01/2025 06:31 Notedévolution noté par DR. Marc GIRARD (Médecin), 01/01/2025 06:31 Verrouillé RESULTATS: Petite plage de condensation parenchymateusel basithoracique gauche avec émoussement du cul-de-sacp pleural minime foyer infectieux dans le contexte ?Pas d'anomalie pleuroparenchymateuse visible àdroite. Intégrité delas silhouette cardiomédiastinale. Dr Sébastien PETIT 01/01/2025 04:05 Histoire dela maladie noté par DR. Antoine BONNET (Médecin), 01/01/2025 04:05 Verrouillé


id: anchor_f303a3f88342_1777566871
description: Maquette pédagogique données fictives usage interne POC GHT Sud 95 W
created_at: 2026-04-30 16:34:31.611692
capture_method: screen_capture
target_text: Maquette pédagogique données fictives usage interne POC GHT Sud 95 W
ocr_description: Maquette pédagogique données fictives usage interne POC GHT Sud 95 W
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target_text:
  DrSébastien PETIT 01/01/2025 04:05 Histoire delamaladie noté par DR. Antoine BONNET (Médecin), 01/01/2025 04:05 Verrouillé MH :toux etc dyspnéef fébrile ATCD: insuffisance coronarienne (Dr Cohen) Asthme TIT: amlodipine 5 resitune 5 innovair 2/0/2 singulair 10 pulmicort 10 Allergies:0 HDM: depuis 23h, quintes det toux sèche insomniantes et dyspnéisantes malgrél la prise de2bouffées de ventoline Notion de contage familial Vacciné grippe et COVID ilya3sem


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description: Synthèse d'urgence
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target_text: 1/03/1947 I 11 ans I Sexe : h Arrivée : 01/0 les Synthese Urgences Codage T2A: >
ocr_description: Synthèse d'urgence
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id: anchor_1e7a355e4a6a_1777567028
description: Synthèse d'urgence
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target_text: 1/03/1947 I 11 ans I Sexe : h Arrivée : 01/0 les Synthese Urgences Codage T2A: >
ocr_description: Synthèse d'urgence
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id: anchor_35d887e713bc_1777567602
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target_text:
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id: anchor_83df5e3bccf7_1777567683
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ocr_description: 8:+3$)-"9&+72'#)6C#F
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target_text: Coder T2A >
ocr_description: *D/(7.C127/32>E7:936
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ocr_description: <)37%%7"*E##--,/98.
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target_text: exe:F Arrivée : - 01/01/2025 03:12 I AO es Codage T2A: >
ocr_description: 52@,10F%E0:D+?+1=03
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id: anchor_f1c1e4e77d9b_1777568077
description: A("?E1BCB/"7&#2?+2":
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target_text: exe:F Arrivée - - 01/01/2025 03:12 I I IAO es Codage T2A: >
ocr_description: A("?E1BCB/"7&#2?+2":
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id: anchor_bdaf0a5b85f5_1777577252
description: Codage text in blue color
created_at: 2026-04-30 19:27:35.986182
capture_method: screen_capture
target_text: urs Codage Statistiques rine Né(e) le 14/03/1947 I - 77
ocr_description: Codage text in blue color
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id: anchor_7b72f0e5aabb_1777577266
description: Codage text in blue color
created_at: 2026-04-30 19:27:47.349380
capture_method: screen_capture
target_text: urs Codage Statistiques rine Né(e) le 14/03/1947 I - 77
ocr_description: Codage text in blue color
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id: anchor_01b083af68a4_1777577411
description: Checkbox with text 'Critère validé
created_at: 2026-04-30 19:30:14.249287
capture_method: screen_capture
ocr_description: Checkbox with text 'Critère validé
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target_text:
  Cocher chaque critère validé pour ce passage. Les preuves sont à rechercher dans lec dossier (Notes IDE, Notes médicales, Examens, Synthèse Urgences). L'algorithme suit lal logique UHCD vsl Forfaits Urgences validée par l'équipe DIM. 1. Pathologie potentiellement évolutive ? Critère validé Rédiger ici la justification du critère 1à partir des éléments du dossier (motif d'admission, signes vitaux, terrain à risque, traitement initial...). 2. Nécessité de surveillance médicale et naramédicale?


id: anchor_ff3bfdf7f6d4_1777577699
description: Validation checkbox and text field
created_at: 2026-04-30 19:35:02.491337
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ocr_description: Validation checkbox and text field
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target_text:
  2. Nécessité de surveillance médicale et paramédicale ? Critère validé Rédiger ici ila justification du critère 2( (constantes IDE, observations médicales, surveillance en box, durée de PEC..).


id: anchor_d6c574420481_1777578052
description: Path icon with text.
created_at: 2026-04-30 19:40:55.405275
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ocr_description: Path icon with text.
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target_text:
  Cocher chaque critère validé pour C6 L Pathologie potentiel Critére validé Rédigerici la justification du


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description: Checkbox with label 'Nécessaire
created_at: 2026-04-30 19:41:15.257432
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target_text: 2. Nécessité de surve Critère validé Rédiger - ICI I la justification
ocr_description: Checkbox with label 'Nécessaire
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id: anchor_6a4db9f10eb0_1777578174
description: Checkbox with label "Critères
created_at: 2026-04-30 19:42:55.764810
capture_method: screen_capture
target_text: 5. Réalisation d'examen Critère validé
ocr_description: Checkbox with label "Critères
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target_text: 3. Réalisation d'examens ou d'actes ? Critère validé
ocr_description: Checkbox with 'Critères' label.
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target_text: Coder >
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target_text: Coder >
ocr_description: Blue button with text 'Coder'.
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id: anchor_af71906a6de5_1777589140
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created_at: 2026-04-30 22:46:07.734129
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target_text: arrivée: - 01/01/2025 20:19 IAO: CARO ces Codage >
ocr_description: Codage button with arrow
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description: Codage button with arrow
created_at: 2026-04-30 22:46:22.457560
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target_text: arrivée: - 01/01/2025 20:19 IAO: CARO ces Codage >
ocr_description: Codage button with arrow
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id: anchor_930fa9de55fb_1778147052
description: Liste des passages aux urgences
created_at: 2026-05-07 09:44:15.078239
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ocr_description: Liste des passages aux urgences
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target_text:
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created_at: 2026-05-07 09:59:37.272591
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ocr_description: Table with patient data.
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target_text:
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id: anchor_4852d99cae10_1778156445
description: 250003284
created_at: 2026-05-07 12:20:47.719187
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target_text: IPP No - 25003284 MC 25003362 LA
ocr_description: 250003284
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id: anchor_a8918d5802a7_1778156542
description: Motif de la venue
created_at: 2026-05-07 12:22:29.821251
capture_method: screen_capture
ocr_description: Motif de la venue
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target_text:
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id: anchor_cdfe229d3976_1778156566
description: Patient details section
created_at: 2026-05-07 12:22:52.794449
capture_method: screen_capture
ocr_description: Patient details section
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target_text:
  Easily Assure Urgences Maquette POC DR. Antoine BONNET Liste patients Reset Déconnexion Patients Planning Dossier en cours Codage Statistiques IPP: 25003284 MOREL Catherine Né(e) le 14/03/1947 I 77 ans I Sexe: F Arrivée 01/01/2025 03:12 I IAO : CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif d'admission Examens cliniques Imagerie Notes médicales Synthèse Urgences Codage > Motif de la venue Symptômes àl l'orientation: : 01/01/2025 03:31 CARON Sandrine Asthme V Observations IDE Description Date Dernière modif par depuis 23h, quintes de toux sèche 01/01/2025 03:31 CARON: Sandrine a pris 2+21 B de VENTO = inefficace 01/01/2025 03:31 contage familial, vacciné grippe et COVIDilya3sem ATCD = asthme, insuf coronarienne TIT = RESITUNE, INNOVAIR,SINGULAIR, ALLERGIE =0 en IOA = HYPERTHERME, masque mis, toux sèche, bon débit de parole, PEAKFLOW 260 TEST Ag COVID fait et NEGATIF V Diagnostics J12.1Pneumopathies due au virus respiratoiresynoydial(VRSIICM2] - Principal 01/01/2025 06:45 DR. Antoine BONNET V Signes vitaux résumé


id: anchor_14ae7e4587c0_1778156651
description: Pedagogical model - fictional data - internal use POC GHT Sud 9
created_at: 2026-05-07 12:24:12.595669
capture_method: screen_capture
target_text: Maquette pedagogique données fictives usage interne POC GHT Sud 95 Ln .
ocr_description: Pedagogical model - fictional data - internal use POC GHT Sud 9
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_14ae7e4587c0_1778156651_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_14ae7e4587c0_1778156651_thumb.png


id: anchor_9ae251da05f0_1778156720
description: Signs vitals summary table.
created_at: 2026-05-07 12:25:23.583499
capture_method: screen_capture
ocr_description: Signs vitals summary table.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_9ae251da05f0_1778156720_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_9ae251da05f0_1778156720_thumb.png

target_text:
  Signes vitaux résumé Item de surveillance 01/01/2025 05:13 01/01/2025 03:25 Température °C 39,4 39,3 Pouls bt/min 117 91 PA Systolique mmHg 136 PA Diastolique mmHg 61 PA Moyenne 86 Saturation 02 % 96 95 Fréq. respiratoire br/min 20 Ventilation Ventilation_spontanée Air ambiant Maquette pédagogique données fictives usage interne POC GHI Sud 95 19°C - Amm A - a a C ou 14:23 ez


id: anchor_a1924e28fa6c_1778156767
description: Examens cliniques icon
created_at: 2026-05-07 12:26:08.058309
capture_method: screen_capture
target_text: MOREL Catherine Ne(e) le 14/03/1 Examens cliniques Imagerie Je
ocr_description: Examens cliniques icon
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_a1924e28fa6c_1778156767_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_a1924e28fa6c_1778156767_thumb.png


id: anchor_4ee508d0af1c_1778156793
description: Examens cliniques
created_at: 2026-05-07 12:26:34.091941
capture_method: screen_capture
target_text: MOREL Catherine Ne(e) le 14/03/1 Examens cliniques Imagerie Je
ocr_description: Examens cliniques
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4ee508d0af1c_1778156793_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4ee508d0af1c_1778156793_thumb.png


id: anchor_4b7a49bddfbc_1778161000
description: Examens cliniques
created_at: 2026-05-07 13:36:42.635515
capture_method: screen_capture
target_text: MOREL Catherine Né(e) le 14/03/: Examens cliniques Imagerie niques
ocr_description: Examens cliniques
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4b7a49bddfbc_1778161000_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_4b7a49bddfbc_1778161000_thumb.png


id: anchor_c3929b00816a_1778161050
description: Exams Cliniques' section
created_at: 2026-05-07 13:37:34.873395
capture_method: screen_capture
ocr_description: Exams Cliniques' section
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c3929b00816a_1778161050_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_c3929b00816a_1778161050_thumb.png

target_text:
  Motif d'admission Examens cliniques Imagerie Notes médicales Synthèse Urgences Codage > Examens Cliniques Questionnaire Score Réponse significative 1 Etat Dernière modification le Motif de suppression Examen clinique (Général) U Synthèse Examen Clinique Note del l'examen clinique : Verrouillé 01/01/2025 04:06 ABONNET fébrile à39 Conscience OKI bien orienté RAS Ventilation : léger frein expi, finit ses phrases. Sibilants bilat pas de foyer CV: fc 90 pas de choc pas d'ic Abdomen RAS V Avis Spécialisés Recherche Aucun avis spécialisé enregistré.


id: anchor_97c78934c22a_1778161108
description: Text element named "Imagerie
created_at: 2026-05-07 13:38:28.839202
capture_method: screen_capture
target_text: NCC 3 - ) I 0211941 - a Imagerie Notes médi
ocr_description: Text element named "Imagerie
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_97c78934c22a_1778161108_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_97c78934c22a_1778161108_thumb.png


id: anchor_29c0ef6eddb2_1778161153
description: Search bar with magnifier icon.
created_at: 2026-05-07 13:39:20.181310
capture_method: screen_capture
ocr_description: Search bar with magnifier icon.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_29c0ef6eddb2_1778161153_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_29c0ef6eddb2_1778161153_thumb.png

target_text:
  IPP: : 25003284 MOREL Catherine Né(e) le 14/03/1947 77 ans Sexe: F Arrivée 01/01/2025 03:12 IAO CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif d'admission Examens cliniques Imagerie Notes médicales Synthèse Urgences Codage > Comptes-rendus d'imagerie (radio, scan, échographie) Recherche Aucun examen d'imagerie enregistré pour ce passage. Maquette pédagogique données fictives usage interne POCGHT Sud 95 19°C 15:38 Ensoleillé C Rechercher II U A (x € 07/05/2026 B


id: anchor_0438bd2d9bdd_1778161174
description: Image gallery icon.
created_at: 2026-05-07 13:39:34.757001
capture_method: screen_capture
target_text: ine Né(e) le 14/03/1947 I 77 ans es Imagerie Notes médical J scan, echograj phie
ocr_description: Image gallery icon.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0438bd2d9bdd_1778161174_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0438bd2d9bdd_1778161174_thumb.png


id: anchor_588c9c1c673c_1778161204
description: Imagerie tab
created_at: 2026-05-07 13:40:10.484150
capture_method: screen_capture
ocr_description: Imagerie tab
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_588c9c1c673c_1778161204_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_588c9c1c673c_1778161204_thumb.png

target_text:
  IPP: 25003284 MOREL Catherine Né(e) le 14/03/1947 77 ans Sexe: :F Arrivée 01/01/2025 03:12 I IAO CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif d'admission Examens cliniques Imagerie Notes médicales Synthèse Urgences Codage > V Comptes-rendus d'imagerie (radio, scan, échographie) Recherche Aucun examen d'imagerie enregistré pour ce passage. Maquette pédagogique données fictives usage interne POCGHT Sud 95 19°C H C Rechercher a 5S E 0' A 0 a Ax € 15:38 E7


id: anchor_eed66b340a98_1778161242
description: Notes médicale
created_at: 2026-05-07 13:40:43.031750
capture_method: screen_capture
target_text: 4/03/1947 I 77 ans I Sexe: F Arrivée e Notes médicales Synthese Urg ohie)
ocr_description: Notes médicale
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_eed66b340a98_1778161242_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_eed66b340a98_1778161242_thumb.png


id: anchor_d2edf48ceeb2_1778161762
description: Patient information card
created_at: 2026-05-07 13:49:31.316546
capture_method: screen_capture
ocr_description: Patient information card
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d2edf48ceeb2_1778161762_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_d2edf48ceeb2_1778161762_thumb.png

target_text:
  Patients Planning Dossier en cours Codage Statistiques IPP: 25003284 MOREL Catherine Né(e) le 14/03/1947 I 77 ans Sexe: F Arrivée: 01/01/2025 03:12 I IAO CARON Sandrine (03:25) Médecin BONNET Antoine I Sortie 01/01/2025 06:49 Motif d'admission Examens cliniques Imagerie Notes médicales Synthèse Urgences Codage > Synthèse Urgences Détails del l'épisode Episode Date 01/01/2025 à 03:12 Mode de transport à l'arrivée Véhicule personnel Médicalisation du transport Aucune médicalisation Mode d'entrée Autres admissions urgentes Origine du transfert Détails del l'orientation aux Urgences Date d'orientation 01/01/2025 à 03:25 IAO CARON Sandrine Priorité Priorité 3 Episode Sous-type Médecine Circonstances Asthme Motif de prise en charge depuis 23h, quintes de toux sèche Observ. IDE Urg a pris 2+2 Bd de VENTO =i inefficace contage familial, vacciné grippe et COVID ilya3sem ATCD = asthme, insuf coronarienne Détails del la prise en charge Médecin del lay prise en charge BONNET Antoine médicale Date del lap prise en charge médicale 01/01/2025 à 03:12 CCMU 3. Etat lésionnel et/ou pronostic fonctionnel jugés susceptibles de s'aggraver aux urgences ou durant l'intervention du SMUR, sans mettre en jeu lei pronostic vital GEMSA 2. Patient non convoqué sortant après consultation ou soins. 19°C - m A i 0 I C C w i oll - 15:48 EZ


id: anchor_8d1822fbaad3_1778164480
description: Coller dossier patient
created_at: 2026-05-07 14:34:43.281059
capture_method: screen_capture
target_text: Coller ou saisir le dossier patient Coller ou saisir le dossier patient
ocr_description: Coller dossier patient
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_8d1822fbaad3_1778164480_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_8d1822fbaad3_1778164480_thumb.png


id: anchor_03089ab44df5_1778164541
description: Justification button with text.
created_at: 2026-05-07 14:35:42.189185
capture_method: screen_capture
target_text: JUSTIFICATION Justification de la décision modifiable Léa peut écrire avant l'analyse)
ocr_description: Justification button with text.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_03089ab44df5_1778164541_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_03089ab44df5_1778164541_thumb.png


id: anchor_1958d72f71c4_1778164548
description: Justification button with text.
created_at: 2026-05-07 14:35:49.051122
capture_method: screen_capture
target_text: JUSTIFICATION Justification de la décision modifiable Léa peut écrire avant l'analyse)
ocr_description: Justification button with text.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1958d72f71c4_1778164548_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1958d72f71c4_1778164548_thumb.png


id: anchor_fef87bd7524e_1778229061
description: Image gallery icon.
created_at: 2026-05-08 08:31:07.462710
capture_method: screen_capture
target_text: ine Né(e) - le 14/03/1947 I I 77 al es Imagerie Notes médica
ocr_description: Image gallery icon.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_fef87bd7524e_1778229061_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_fef87bd7524e_1778229061_thumb.png


id: anchor_6a2591e7c51c_1778229076
description: Notes médiatiques
created_at: 2026-05-08 08:31:17.617420
capture_method: screen_capture
target_text: à 14/03/1947 I 77 ans I I Sexe F Arrivé ie Notes médicales Synthèse Ur
ocr_description: Notes médiatiques
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6a2591e7c51c_1778229076_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_6a2591e7c51c_1778229076_thumb.png


id: anchor_ab29f9be8673_1778420995
description: Coller ou saisir dossier patient
created_at: 2026-05-10 13:50:21.201540
capture_method: screen_capture
target_text: Coller ou saisir le dossier patient Coller ou saisir le dossier patient
ocr_description: Coller ou saisir dossier patient
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_ab29f9be8673_1778420995_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_ab29f9be8673_1778420995_thumb.png


id: anchor_3c8a9303a3a2_1778422742
description: Notes médicales
created_at: 2026-05-10 14:19:27.705758
capture_method: screen_capture
target_text: à 14/03/1947 I 77 ans I I Sexe F Arrivé ie Notes médicales Synthèse Ur
ocr_description: Notes médicales
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_3c8a9303a3a2_1778422742_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_3c8a9303a3a2_1778422742_thumb.png


id: anchor_807d29c6ab5b_1778422860
description: Urgencies summary button
created_at: 2026-05-10 14:21:02.094669
capture_method: screen_capture
target_text: à I Sexe : F Arrivée : 01/01/2025 03:12 I IAC S Synthèse Urgences Codage >
ocr_description: Urgencies summary button
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_807d29c6ab5b_1778422860_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_807d29c6ab5b_1778422860_thumb.png


id: anchor_efe9d72f07e3_1778425168
created_at: 2026-05-10 15:00:29.360775
capture_method: screen_capture
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_efe9d72f07e3_1778425168_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_efe9d72f07e3_1778425168_thumb.png

description:
  re Urgences = Maquette POC DR.. Antoine BONNET Liste patients ning Dossier en cours Codage Statistiques MOREL Catherine Né(e) le 14/03/1947 I 77 ans Sexe : F Arrivée : 01/01/2025 03:12 I IAO : CARON Sandrine (03:25) Médecin : BONNET Antoine I Sortie : 01/01/2025 06:49 Arbre décisionnel UHCD / Forfait Urgences Aide à la décision de facturation urgences ualification en hospitalisation MCO décision T2A/PMSI assistée par LLM local atient (DPI urgences) Décision facturation ossier patient En attente d'analyse e dossier patient Vérité-terrain : CONFIANCE DURÉE PASSAGE LATENCE JUSTIFICATION Justification de la décision (modifiable - Léa peut écrire avant l'analyse)

target_text:
  re Urgences = Maquette POC DR.. Antoine BONNET Liste patients ning Dossier en cours Codage Statistiques MOREL Catherine Né(e) le 14/03/1947 I 77 ans Sexe : F Arrivée : 01/01/2025 03:12 I IAO : CARON Sandrine (03:25) Médecin : BONNET Antoine I Sortie : 01/01/2025 06:49 Arbre décisionnel UHCD / Forfait Urgences Aide à la décision de facturation urgences ualification en hospitalisation MCO décision T2A/PMSI assistée par LLM local atient (DPI urgences) Décision facturation ossier patient En attente d'analyse e dossier patient Vérité-terrain : CONFIANCE DURÉE PASSAGE LATENCE JUSTIFICATION Justification de la décision (modifiable - Léa peut écrire avant l'analyse)

ocr_description:
  re Urgences = Maquette POC DR.. Antoine BONNET Liste patients ning Dossier en cours Codage Statistiques MOREL Catherine Né(e) le 14/03/1947 I 77 ans Sexe : F Arrivée : 01/01/2025 03:12 I IAO : CARON Sandrine (03:25) Médecin : BONNET Antoine I Sortie : 01/01/2025 06:49 Arbre décisionnel UHCD / Forfait Urgences Aide à la décision de facturation urgences ualification en hospitalisation MCO décision T2A/PMSI assistée par LLM local atient (DPI urgences) Décision facturation ossier patient En attente d'analyse e dossier patient Vérité-terrain : CONFIANCE DURÉE PASSAGE LATENCE JUSTIFICATION Justification de la décision (modifiable - Léa peut écrire avant l'analyse)


id: anchor_0efb3b8f61bb_1778434669
description: Number: 250003284
created_at: 2026-05-10 17:38:14.350989
capture_method: screen_capture
target_text: IPP No - 25003284 MC 25003362 LA
ocr_description: Number: 250003284
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0efb3b8f61bb_1778434669_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_0efb3b8f61bb_1778434669_thumb.png


id: anchor_7ed58bbe1194_1778434871
description: Button labeled "Examens cliniques"
created_at: 2026-05-10 17:41:12.643186
capture_method: screen_capture
target_text: MOREL Catherine Ne(e) le 14/03/1 Examens cliniques Imagerie Je
ocr_description: Button labeled "Examens cliniques"
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_7ed58bbe1194_1778434871_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_7ed58bbe1194_1778434871_thumb.png


id: anchor_30ef2bca7362_1778434976
description: Text element named Imagerie
created_at: 2026-05-10 17:42:57.836635
capture_method: screen_capture
target_text: NCC 3 - ) I 0211941 - a Imagerie Notes médi
ocr_description: Text element named Imagerie
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_30ef2bca7362_1778434976_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_30ef2bca7362_1778434976_thumb.png


id: anchor_507abcd28b06_1778435668
description: Blank white screen.
created_at: 2026-05-10 17:54:58.022735
capture_method: screen_capture
target_text: Blank white screen.
ocr_description: Blank white screen.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_507abcd28b06_1778435668_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_507abcd28b06_1778435668_thumb.png


id: anchor_1a8811a99aa8_1778435686
description: Blank white screen.
created_at: 2026-05-10 17:55:02.990187
capture_method: screen_capture
target_text: Blank white screen.
ocr_description: Blank white screen.
image_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1a8811a99aa8_1778435686_full.png

thumbnail_path:
  /home/dom/ai/rpa_vision_v3/visual_workflow_builder/backend/data/anchors/anchor_1a8811a99aa8_1778435686_thumb.png


# steps

id: step_6184d7fd0f5b_1769196774
workflow_id: wf_d55b71373f0a_1769184759
action_type: click_anchor
anchor_id: anchor_b73d32ff6a3a_1770801636
label: click_anchor
created_at: 2026-01-23 19:32:54.829648
updated_at: 2026-04-14 12:31:34.286872
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_b73d32ff6a3a_1770801636", "bounding_box": {"x": 7, "y": 1020, "width": 54, "height": 51}}}


id: step_274b22100233_1769197670
workflow_id: wf_d55b71373f0a_1769184759
action_type: click_anchor
anchor_id: anchor_0c2836b2e973_1769197682
label: click_anchor
created_at: 2026-01-23 19:47:50.020525
updated_at: 2026-04-14 12:31:37.437791
parameters_json:
  {"delay_before": 100, "visual_anchor": {"anchor_id": "anchor_0c2836b2e973_1769197682", "bounding_box": {"height": 179, "width": 190, "x": 899, "y": 110}}}


id: step_957fe56946d0_1769200014
workflow_id: wf_d55b71373f0a_1769184759
action_type: click_anchor
anchor_id: anchor_faaab112603a_1769200099
label: click_anchor
created_at: 2026-01-23 20:26:54.532315
updated_at: 2026-01-29 21:29:01.952231
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_faaab112603a_1769200099", "bounding_box": {"x": 740, "y": 105, "width": 181, "height": 177}}}


id: step_4fcf94236ff1_1769200173
workflow_id: wf_d55b71373f0a_1769184759
action_type: wait_for_anchor
anchor_id: anchor_64ba9e3f9c7c_1769200373
label: wait_for_anchor
created_at: 2026-01-23 20:29:33.672977
updated_at: 2026-01-29 21:29:05.696224
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_64ba9e3f9c7c_1769200373", "bounding_box": {"x": 765, "y": 213, "width": 571, "height": 17}}}


id: step_f6cdd716f062_1769200383
workflow_id: wf_d55b71373f0a_1769184759
action_type: type_text
label: Saisir texte Kimi K2.5
created_at: 2026-01-23 20:33:03.224838
updated_at: 2026-04-14 12:31:44.685861
parameters_json:
  {"clear_before": true, "text": "Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.\n\nKey Features\nNative Multimodality: Pre-trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross-modal reasoning, and agentic tool use grounded in visual inputs.\nCoding with Vision: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.\nAgent Swarm: K2.5 transitions from single-agent scaling to a self-directed, coordinated swarm-like execution scheme. It decomposes complex tasks into parallel sub-tasks executed by dynamically instantiated, domain-specific agents.", "output_variable": "texte_kimi"}


id: step_117f3ccc46d1_1769202475
workflow_id: wf_d55b71373f0a_1769184759
action_type: click_anchor
anchor_id: anchor_51c04e0e1db5_1769203445
label: Ouvrir lanceur Ubuntu
created_at: 2026-01-23 21:07:55.403915
updated_at: 2026-03-11 14:57:13.870348
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_51c04e0e1db5_1769203445", "bounding_box": {"height": 54, "width": 60, "x": 4, "y": 1018}}}


id: step_56bb4454972a_1769202487
workflow_id: wf_d55b71373f0a_1769184759
action_type: click_anchor
anchor_id: anchor_03c42f2ed139_1769203089
label: Cliquer icône gedit
created_at: 2026-01-23 21:08:07.145479
updated_at: 2026-01-23 21:18:12.181182
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_03c42f2ed139_1769203089", "bounding_box": {"height": 164, "width": 158, "x": 913, "y": 109}}}


id: step_2e998e88fb89_1769202492
workflow_id: wf_d55b71373f0a_1769184759
action_type: wait_for_anchor
anchor_id: anchor_b0688d5625ce_1769203327
label: Attendre gedit
created_at: 2026-01-23 21:08:12.676819
updated_at: 2026-01-23 21:23:11.518208
parameters_json:
  {"timeout_ms": 10000, "visual_anchor": {"anchor_id": "anchor_b0688d5625ce_1769203327", "bounding_box": {"height": 42, "width": 77, "x": 72, "y": 76}}}


id: step_a393cbf114cb_1769720990
workflow_id: wf_d55b71373f0a_1769184759
action_type: ai_analyze_text
label: ai_analyze_text
created_at: 2026-01-29 21:09:50.975856
updated_at: 2026-04-14 12:31:47.470294
parameters_json:
  {"input_text": "{{texte_kimi}}", "model": "gpt-oss:latest", "output_variable": "resultat_analyse", "prompt": "Analyse le texte. Rends le parfaitement compr\u00e9hensif dans la langue que tu d\u00e9tectes, corrige les fautes de syntaxe, d'orthographe etc... Traduis le texte en fran\u00e7ais. Ensuite dans un nouveau paragraphe traduis le texte en chinois."}


id: step_c995dee8b9be_1773753106
workflow_id: wf_372eabf626f8_1773752892
action_type: click_anchor
anchor_id: anchor_e54628b75227_1773829452
label: click_anchor
created_at: 2026-03-17 13:11:46.953317
updated_at: 2026-03-18 21:47:42.577243
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_e54628b75227_1773829452", "bounding_box": {"x": 560, "y": 1536, "width": 230, "height": 59}}}


id: step_ea85af7945d8_1773832513
workflow_id: wf_372eabf626f8_1773752892
action_type: click_anchor
anchor_id: anchor_dd32b09238ca_1773833606
label: click_anchor
created_at: 2026-03-18 11:15:13.399805
updated_at: 2026-03-18 11:37:20.723627
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_dd32b09238ca_1773833606", "bounding_box": {"x": 670, "y": 310, "width": 51, "height": 51}}}


id: step_597f49e6ade0_1773833663
workflow_id: wf_372eabf626f8_1773752892
action_type: wait_for_anchor
anchor_id: anchor_2d51b88900d7_1773833805
label: wait_for_anchor
created_at: 2026-03-18 11:34:23.818256
updated_at: 2026-03-25 15:59:57.198954
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_2d51b88900d7_1773833805", "bounding_box": {"x": 287, "y": 290, "width": 70, "height": 92}}}


id: step_6ed5e49c626f_1776436788
workflow_id: wf_bb6df0b368e7_1776436788
action_type: click_anchor
label: Clic : text_field
created_at: 2026-04-17 14:39:48.866312
updated_at: 2026-04-17 14:39:48.866314
parameters_json:
  {"compound_steps": [{"type": "mouse_click", "position": [273, 1456], "x_pct": 0.142187, "y_pct": 1.348148, "button": "left", "ref_width": 1920, "ref_height": 1080}, {"type": "wait", "duration_ms": 3483}, {"type": "text_input", "text": "n"}, {"type": "wait", "duration_ms": 841}, {"type": "text_input", "text": "om"}, {"type": "wait", "duration_ms": 957}, {"type": "text_input", "text": ":"}, {"type": "wait", "duration_ms": 1090}, {"type": "text_input", "text": " "}, {"type": "wait", "duration_ms": 2292}, {"type": "text_input", "text": "bazin"}, {"type": "wait", "duration_ms": 2251}, {"type": "text_input", "text": "p"}, {"type": "wait", "duration_ms": 2357}, {"type": "text_input", "text": "renom"}, {"type": "wait", "duration_ms": 797}, {"type": "text_input", "text": " "}, {"type": "wait", "duration_ms": 988}, {"type": "text_input", "text": ": "}, {"type": "wait", "duration_ms": 2781}, {"type": "text_input", "text": "dominique"}, {"type": "wait", "duration_ms": 2729}, {"type": "text_input", "text": "date"}, {"type": "wait", "duration_ms": 1174}, {"type": "text_input", "text": " :"}, {"type": "wait", "duration_ms": 1065}, {"type": "text_input", "text": " "}, {"type": "wait", "duration_ms": 2097}, {"type": "text_input", "text": "!"}, {"type": "wait", "duration_ms": 1598}, {"type": "text_input", "text": "!"}], "target_role": "text_field"}


id: step_14ac44d2d665_1776438896
workflow_id: wf_28e4e246bf22_1776438896
action_type: click_anchor
label: Clic : text_field
created_at: 2026-04-17 15:14:56.026375
updated_at: 2026-04-17 15:14:56.026377
parameters_json:
  {"compound_steps": [{"type": "mouse_click", "position": [1468, 258], "x_pct": 0.764583, "y_pct": 0.238889, "button": "left", "ref_width": 1920, "ref_height": 1080}, {"type": "wait", "duration_ms": 3969}, {"type": "text_input", "text": "hello"}, {"type": "wait", "duration_ms": 571}, {"type": "text_input", "text": " "}, {"type": "wait", "duration_ms": 2941}, {"type": "text_input", "text": "bonjour "}, {"type": "wait", "duration_ms": 2067}, {"type": "text_input", "text": ":-)"}], "target_role": "text_field"}


id: step_c916e56fdce1
workflow_id: wf_806a420bac54
action_type: import_excel
label: Importer factures.xlsx
parameters_json:
  {"file_path": "data/demo/factures_demo.xlsx", "table_name": "factures_demo", "sheet_name": "Factures", "detect_types": true}


id: step_75d1d8b801e6
workflow_id: wf_806a420bac54
action_type: click_anchor
label: Clic : champ N° Facture
parameters_json:
  {"target_text": "N° Facture", "target_role": "text_field", "description": "Cliquer sur le champ de saisie du numéro de facture"}


id: step_2e99b5fce910
workflow_id: wf_806a420bac54
action_type: click_anchor
label: Clic : bouton Valider
parameters_json:
  {"target_text": "Valider", "target_role": "button", "description": "Valider la saisie de la facture"}


id: step_ed84912082ee
workflow_id: wf_603a9fa759ca
action_type: click_anchor
label: Clic : ouvrir dossier patient
parameters_json:
  {"target_text": "Dossier patient", "target_role": "menu_item", "description": "Ouvrir le dossier patient dans le DPI"}


id: step_a8476b449a61
workflow_id: wf_603a9fa759ca
action_type: extract_text
label: Extraire texte de l'écran
parameters_json:
  {"extraction_mode": "full", "output_variable": "texte_ecran", "description": "Capture et extraction OCR du contenu visible"}


id: step_350a617f0e5d
workflow_id: wf_603a9fa759ca
action_type: ai_analyze_text
label: IA : extraire données structurées
parameters_json:
  {"input_text": "{{texte_ecran}}", "analysis_prompt": "Extrais les informations suivantes du texte :\n- Nom du patient\n- Date de naissance\n- Numéro de séjour\n- Service\n- Diagnostic principal\n\nRetourne un JSON structuré.", "output_variable": "donnees_patient", "temperature": 0.1}


id: step_c8d56661d696
workflow_id: wf_603a9fa759ca
action_type: db_save_data
label: Sauvegarder en base
parameters_json:
  {"table_name": "patients_extraits", "data_variable": "donnees_patient", "key_column": "numero_sejour"}


id: step_43385710215a_1776523435
workflow_id: wf_f87a537d53fc_1776523414
action_type: click_anchor
anchor_id: anchor_e699f12dea5d_1776523946
label: click_anchor
created_at: 2026-04-18 14:43:55.614208
updated_at: 2026-04-19 08:18:11.311086
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_e699f12dea5d_1776523946", "bounding_box": {"x": 1207, "y": 1025, "width": 52, "height": 50}}}


id: step_b35f862735ca_1776523964
workflow_id: wf_f87a537d53fc_1776523414
action_type: wait_for_anchor
anchor_id: anchor_c4784649c3f7_1776524106
label: wait_for_anchor
created_at: 2026-04-18 14:52:44.672190
updated_at: 2026-04-19 08:18:13.408218
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_c4784649c3f7_1776524106", "bounding_box": {"height": 93, "width": 140, "x": 190, "y": 35}}, "timeout_ms": 1000}


id: step_31adff7bf08d_1776586703
workflow_id: wf_f87a537d53fc_1776523414
action_type: keyboard_shortcut
anchor_id: anchor_1874fab6cb2d_1776586868
label: keyboard_shortcut
created_at: 2026-04-19 08:18:23.604514
updated_at: 2026-04-19 08:21:20.909553
parameters_json:
  {"keys": ["enter"], "visual_anchor": {"anchor_id": "anchor_1874fab6cb2d_1776586868", "bounding_box": {"height": 27, "width": 116, "x": 494, "y": 154}}}


id: step_d1031d09c146_1776591746
workflow_id: wf_46cb704f1971_1776591579
action_type: click_anchor
anchor_id: anchor_4483b2b8c0b8_1776591775
label: click_anchor
created_at: 2026-04-19 09:42:26.216476
updated_at: 2026-04-26 13:55:42.783938
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_4483b2b8c0b8_1776591775", "bounding_box": {"x": 666, "y": 1024, "width": 100, "height": 43}}}


id: step_c3dd154cd6a7_1776591947
workflow_id: wf_46cb704f1971_1776591579
action_type: wait_for_anchor
anchor_id: anchor_6a2d95e5e8ca_1776591968
label: wait_for_anchor
created_at: 2026-04-19 09:45:47.470123
updated_at: 2026-04-26 13:55:47.567912
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_6a2d95e5e8ca_1776591968", "bounding_box": {"x": 1353, "y": 144, "width": 113, "height": 124}}}


id: step_3284c3c5563f_1776591977
workflow_id: wf_46cb704f1971_1776591579
action_type: click_anchor
anchor_id: anchor_d438bb353be7_1776591997
label: click_anchor
created_at: 2026-04-19 09:46:17.165930
updated_at: 2026-04-26 13:55:49.872478
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_d438bb353be7_1776591997", "bounding_box": {"x": 1171, "y": 378, "width": 129, "height": 47}}}


id: step_12b0f637266c_1776592327
workflow_id: wf_46cb704f1971_1776591579
action_type: wait_for_anchor
anchor_id: anchor_61cc3fb364e0_1776592347
label: wait_for_anchor
created_at: 2026-04-19 09:52:07.747578
updated_at: 2026-04-26 13:55:52.519601
parameters_json:
  {"timeout_ms": 2000, "visual_anchor": {"anchor_id": "anchor_61cc3fb364e0_1776592347", "bounding_box": {"height": 104, "width": 66, "x": 468, "y": 5}}}


id: step_1f657c041ad7_1776765219
workflow_id: wf_1cc92ee05159_1776752816
action_type: double_click_anchor
anchor_id: anchor_c47602cedc05_1776773318
label: double_click_anchor
created_at: 2026-04-21 09:53:39.122730
updated_at: 2026-04-21 17:01:51.833340
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_c47602cedc05_1776773318", "bounding_box": {"x": 92, "y": 689, "width": 154, "height": 121}}}


id: step_c8c9d97853e0_1776773741
workflow_id: wf_1cc92ee05159_1776752816
action_type: double_click_anchor
anchor_id: anchor_be5bf2b0088b_1776773876
label: double_click_anchor
created_at: 2026-04-21 12:15:41.761215
updated_at: 2026-04-23 06:58:42.630242
parameters_json:
  {"delay_before": 200, "visual_anchor": {"anchor_id": "anchor_be5bf2b0088b_1776773876", "bounding_box": {"height": 55, "width": 220, "x": 312, "y": 243}}}


id: step_b08e9c1f2d86_1776773949
workflow_id: wf_1cc92ee05159_1776752816
action_type: wait_for_anchor
anchor_id: anchor_fdfc0baf59e6_1776774010
label: wait_for_anchor
created_at: 2026-04-21 12:19:09.162865
updated_at: 2026-04-21 18:10:58.570953
parameters_json:
  {"timeout_ms": 1000, "visual_anchor": {"anchor_id": "anchor_fdfc0baf59e6_1776774010", "bounding_box": {"height": 91, "width": 80, "x": 427, "y": 157}}, "check_interval": 5}


id: step_4c1ba6711cb4_1776784685
workflow_id: wf_1cc92ee05159_1776752816
action_type: click_anchor
anchor_id: anchor_b8ae007cfb07_1776784723
label: click_anchor
created_at: 2026-04-21 15:18:05.603215
updated_at: 2026-04-21 15:22:05.610211
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_b8ae007cfb07_1776784723", "bounding_box": {"height": 52, "width": 294, "x": 642, "y": 1024}}}


id: step_a5ecf10c3eda_1776784733
workflow_id: wf_1cc92ee05159_1776752816
action_type: type_text
anchor_id: anchor_f4ee64c796b1_1776784765
label: type_text
created_at: 2026-04-21 15:18:53.352020
updated_at: 2026-04-21 18:09:12.743211
parameters_json:
  {"text": "only", "visual_anchor": {"anchor_id": "anchor_f4ee64c796b1_1776784765", "bounding_box": {"height": 52, "width": 294, "x": 642, "y": 1024}}}


id: step_472e4a131027_1776784823
workflow_id: wf_1cc92ee05159_1776752816
action_type: click_anchor
anchor_id: anchor_ab3b0bdcbfbf_1776784888
label: click_anchor
created_at: 2026-04-21 15:20:23.186590
updated_at: 2026-04-23 15:10:49.133967
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_ab3b0bdcbfbf_1776784888", "bounding_box": {"height": 29, "width": 184, "x": 1201, "y": 476}}}


id: step_2430fe8f9336_1777478974
workflow_id: wf_b964befbfa97_1777473952
action_type: wait_for_anchor
anchor_id: anchor_930fa9de55fb_1778147052
label: wait_for_anchor
created_at: 2026-04-29 16:09:34.792615
updated_at: 2026-05-07 11:44:36.701707
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_930fa9de55fb_1778147052", "bounding_box": {"x": 22, "y": 379, "width": 479, "height": 36}}}


id: step_7a8dd625c78d_1777565394
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_f9bbb873c964_1777565422
label: click_anchor
created_at: 2026-04-30 16:09:54.186624
updated_at: 2026-05-07 11:49:30.077116
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_f9bbb873c964_1777565422", "bounding_box": {"x": 14, "y": 361, "width": 170, "height": 48}}}


id: step_e56202c2197a_1777565444
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_cdfe229d3976_1778156566
label: extract_text
created_at: 2026-04-30 16:10:44.332166
updated_at: 2026-05-07 13:35:48.961077
parameters_json:
  {"variable_name": "motif_admin_1", "visual_anchor": {"anchor_id": "anchor_cdfe229d3976_1778156566", "bounding_box": {"height": 883, "width": 2518, "x": 2, "y": 303}}}


id: step_cece85b96895_1777565869
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_4b7a49bddfbc_1778161000
label: click_anchor
created_at: 2026-04-30 16:17:49.080978
updated_at: 2026-05-07 13:36:42.636314
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_4b7a49bddfbc_1778161000", "bounding_box": {"x": 232, "y": 424, "width": 230, "height": 45}}}


id: step_c66873eca316_1777565901
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_c3929b00816a_1778161050
label: extract_text
created_at: 2026-04-30 16:18:21.116015
updated_at: 2026-05-07 13:38:11.836517
parameters_json:
  {"variable_name": "t2", "visual_anchor": {"anchor_id": "anchor_c3929b00816a_1778161050", "bounding_box": {"height": 643, "width": 2538, "x": 6, "y": 467}}}


id: step_92069034135f_1777565955
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_eed66b340a98_1778161242
label: click_anchor
created_at: 2026-04-30 16:19:15.274428
updated_at: 2026-05-07 14:05:11.006401
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_eed66b340a98_1778161242", "bounding_box": {"x": 602, "y": 424, "width": 181, "height": 46}}}


id: step_69e2cc4fcd9f_1777566722
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_94792774d3e9_1777566772
label: extract_text
created_at: 2026-04-30 16:32:02.897858
updated_at: 2026-05-07 13:41:30.194551
parameters_json:
  {"variable_name": "note_medicales_1", "visual_anchor": {"anchor_id": "anchor_94792774d3e9_1777566772", "bounding_box": {"height": 774, "width": 2513, "x": 5, "y": 335}}}


id: step_d0c4acb40f86_1777567003
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_1e7a355e4a6a_1777567028
label: click_anchor
created_at: 2026-04-30 16:36:43.426264
updated_at: 2026-05-07 13:50:46.411419
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_1e7a355e4a6a_1777567028", "bounding_box": {"x": 548, "y": 343, "width": 189, "height": 45}}}


id: step_f60cdf66665e_1777567557
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_d2edf48ceeb2_1778161762
label: extract_text
created_at: 2026-04-30 16:45:57.516259
updated_at: 2026-05-07 13:49:52.858002
parameters_json:
  {"variable_name": "tsynthese_urgence_1", "visual_anchor": {"anchor_id": "anchor_d2edf48ceeb2_1778161762", "bounding_box": {"height": 1166, "width": 2538, "x": 2, "y": 349}}}


id: step_e8bfa1f369b2_1777567700
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_90a77dd7e94d_1777567721
label: extract_text
created_at: 2026-04-30 16:48:20.790913
updated_at: 2026-05-07 13:51:08.427961
parameters_json:
  {"variable_name": "synthes_uregence_2", "visual_anchor": {"anchor_id": "anchor_90a77dd7e94d_1777567721", "bounding_box": {"height": 566, "width": 2510, "x": 14, "y": 815}}}


id: step_c6f83ad615bf_1777568045
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_76a0ff320080_1777589181
label: click_anchor
created_at: 2026-04-30 16:54:05.689375
updated_at: 2026-04-30 22:46:29.568854
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_76a0ff320080_1777589181", "bounding_box": {"height": 46, "width": 131, "x": 751, "y": 342}}}


id: step_17e09cacb7c1_1777571560
workflow_id: wf_b964befbfa97_1777473952
action_type: t2a_decision
label: t2a_decision
created_at: 2026-04-30 17:52:40.765615
updated_at: 2026-05-05 12:32:50.721022
parameters_json:
  {"input_template": "{{t0}}                                                                                                                                                                                \n  ---   \n  {{t1}}                                                                                                                                                                                \n  {{t2}}                                                             \n  {{t3}}\n  {{t5}}\n  {{t6}}\n", "output_var": "dec"}


id: step_dd8aa7209ca1_1777572831
workflow_id: wf_b964befbfa97_1777473952
action_type: pause_for_human
label: pause_for_human
created_at: 2026-04-30 18:13:51.651532
updated_at: 2026-04-30 19:49:45.638872
parameters_json:
  {"message": "D\u00e9cision : {{dec.decision_court}}                                                                                                                                                          \n                                                                                                                                                                                        \n  {{dec.justification}}   "}


id: step_85efc3f62530_1777577382
workflow_id: wf_b964befbfa97_1777473952
action_type: type_text
anchor_id: anchor_01b083af68a4_1777577411
label: type_text
created_at: 2026-04-30 19:29:42.558302
updated_at: 2026-04-30 22:40:58.983474
parameters_json:
  {"text": "{{dec.preuve_critere1}}", "visual_anchor": {"anchor_id": "anchor_01b083af68a4_1777577411", "bounding_box": {"height": 395, "width": 2486, "x": 31, "y": 420}}}


id: step_e5011cfc08f8_1777577640
workflow_id: wf_b964befbfa97_1777473952
action_type: type_text
anchor_id: anchor_ff3bfdf7f6d4_1777577699
label: type_text
created_at: 2026-04-30 19:34:00.869916
updated_at: 2026-04-30 19:51:15.058296
parameters_json:
  {"text": "{{dec.preuve_critere2}}", "visual_anchor": {"anchor_id": "anchor_ff3bfdf7f6d4_1777577699", "bounding_box": {"height": 400, "width": 2514, "x": 13, "y": 815}}}


id: step_a397eea07768_1777577713
workflow_id: wf_b964befbfa97_1777473952
action_type: type_text
anchor_id: anchor_29b89a0891b5_1777578702
label: type_text
created_at: 2026-04-30 19:35:13.431669
updated_at: 2026-04-30 22:40:54.871292
parameters_json:
  {"text": "{{dec.preuve_critere3}}", "visual_anchor": {"anchor_id": "anchor_29b89a0891b5_1777578702", "bounding_box": {"height": 88, "width": 450, "x": 30, "y": 824}}}


id: step_d16fdd40127f_1777578041
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_d6c574420481_1777578052
label: click_anchor
created_at: 2026-04-30 19:40:41.038966
updated_at: 2026-04-30 22:41:06.315096
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_d6c574420481_1777578052", "bounding_box": {"x": 20, "y": 429, "width": 129, "height": 131}}, "condition": "dec.critere1_valide"}


id: step_a019f6a5668f_1777578064
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_a2d52564f86a_1777578074
label: click_anchor
created_at: 2026-04-30 19:41:04.098750
updated_at: 2026-04-30 22:41:08.111985
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_a2d52564f86a_1777578074", "bounding_box": {"x": 31, "y": 838, "width": 101, "height": 120}}, "condition": "dec.critere2_valide"}


id: step_e9839a813d7d_1777578082
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_6a4db9f10eb0_1777578174
label: click_anchor
created_at: 2026-04-30 19:41:22.450836
updated_at: 2026-04-30 22:41:10.050237
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_6a4db9f10eb0_1777578174", "bounding_box": {"x": 33, "y": 832, "width": 123, "height": 71}}, "condition": "dec.critere3_valide"}


id: step_f4c3588f8d65_1778147951
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_table
anchor_id: anchor_d7b26c54198f_1778147971
label: extract_table
created_at: 2026-05-07 09:59:11.128454
updated_at: 2026-05-07 11:44:42.484914
parameters_json:
  {"variable_name": "patients_ipp", "visual_anchor": {"anchor_id": "anchor_d7b26c54198f_1778147971", "bounding_box": {"height": 543, "width": 2522, "x": 20, "y": 499}}}


id: step_30fe20a049a9_1778149168
workflow_id: wf_b964befbfa97_1777473952
action_type: pause_for_human
label: pause_for_human
created_at: 2026-05-07 10:19:28.254209
updated_at: 2026-05-07 12:15:58.291644
parameters_json:
  {"message": "j'ai trouv\u00e9 des dossiers dans la liste : {{patients_ipp}}. Je vais traiter MOREL Catherine pour la d\u00e9mo. On y va ?"}


id: step_d2d7b0c20ecb_1778155930
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_4852d99cae10_1778156445
label: click_anchor
created_at: 2026-05-07 12:12:10.191568
updated_at: 2026-05-07 12:20:47.719596
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_4852d99cae10_1778156445", "bounding_box": {"x": 30, "y": 548, "width": 101, "height": 30}}}


id: step_9d2eddf2c731_1778156696
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_9ae251da05f0_1778156720
label: extract_text
created_at: 2026-05-07 12:24:56.358709
updated_at: 2026-05-07 13:35:57.111983
parameters_json:
  {"variable_name": "motif_admin_2", "visual_anchor": {"anchor_id": "anchor_9ae251da05f0_1778156720", "bounding_box": {"height": 544, "width": 2507, "x": 17, "y": 969}}}


id: step_4f7b9761be73_1778161097
workflow_id: wf_b964befbfa97_1777473952
action_type: click_anchor
anchor_id: anchor_0438bd2d9bdd_1778161174
label: click_anchor
created_at: 2026-05-07 13:38:17.246714
updated_at: 2026-05-07 13:39:34.757296
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_0438bd2d9bdd_1778161174", "bounding_box": {"x": 444, "y": 424, "width": 146, "height": 48}}}


id: step_c15df8188851_1778161180
workflow_id: wf_b964befbfa97_1777473952
action_type: extract_text
anchor_id: anchor_588c9c1c673c_1778161204
label: extract_text
created_at: 2026-05-07 13:39:40.025394
updated_at: 2026-05-07 14:05:09.062216
parameters_json:
  {"variable_name": "imagerie", "visual_anchor": {"anchor_id": "anchor_588c9c1c673c_1778161204", "bounding_box": {"height": 1112, "width": 2558, "x": 2, "y": 410}}}


id: step_1dada40f6a44_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: pause_for_human
label: Confirmer démarrage
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 18:22:04.616842
parameters_json:
  {"message": "Léa : j'ai trouvé ces dossiers : {{patients_ipp}}. Pour la démo je vais traiter MOREL Catherine (25003284). On y va ?", "safety_level": "standard"}


id: step_288d0bceea90_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_0efb3b8f61bb_1778434669
label: Ouvrir dossier MOREL (25003284)
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 18:22:06.145101
parameters_json:
  {"by_text": "25003284", "visual_anchor": {"anchor_id": "anchor_0efb3b8f61bb_1778434669", "bounding_box": {"x": 30, "y": 548, "width": 101, "height": 30}}}


id: step_3b13c973d737_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_30ef2bca7362_1778434976
label: Onglet Notes médicales
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 18:47:10.592395
parameters_json:
  {"by_text": "Notes m\u00e9dicales", "visual_anchor": {"anchor_id": "anchor_30ef2bca7362_1778434976", "bounding_box": {"x": 483, "y": 432, "width": 96, "height": 31}}}


id: step_8767d8e2e221_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_3c8a9303a3a2_1778422742
label: Onglet Synthèse Urgences
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 17:41:58.983816
parameters_json:
  {"by_text": "Synth\u00e8se Urgences", "visual_anchor": {"anchor_id": "anchor_3c8a9303a3a2_1778422742", "bounding_box": {"x": 580, "y": 423, "width": 192, "height": 47}}}


id: step_835e5dd54bb7_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: extract_text
anchor_id: anchor_efe9d72f07e3_1778425168
label: Lire Synthèse Urgences
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 17:51:40.704697
parameters_json:
  {"paragraph": true, "variable_name": "t_notes_medicales", "visual_anchor": {"anchor_id": "anchor_efe9d72f07e3_1778425168", "bounding_box": {"height": 754, "width": 1964, "x": 236, "y": 272}}}


id: step_fc5a9676af55_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: t2a_decision
label: Décision T2A (LLM)
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 18:09:26.330097
parameters_json:
  {"input_template": "{{t_motif_admission}}\n{{t_examen_clinique}}\n{{t_imagerie}}\n{{t_notes_medicales}}\n{{t_synthese_urgences}}", "output_var": "dec.justification"}


id: step_36346c1c40b9_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_1a8811a99aa8_1778435686
label: Cliquer textarea DPI
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 17:55:02.991022
parameters_json:
  {"by_text": "Coller ou saisir le dossier patient", "visual_anchor": {"anchor_id": "anchor_1a8811a99aa8_1778435686", "bounding_box": {"x": 277, "y": 782, "width": 859, "height": 310}}}


id: step_44edb8dcb683_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: type_text
label: Saisir DPI dans aiva-vision
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 17:55:38.960407
parameters_json:
  {"text": "{{t_motif_admission}}\n{{t_examen_clinique}}\n{{t_imagerie}}\n{{t_notes_medicales}}\n{{t_synthese_urgences}}\n"}


id: step_294095ba7571_1778162737752
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_1958d72f71c4_1778164548
label: Cliquer textarea Justification
created_at: 2026-05-07 16:05:37.751722
updated_at: 2026-05-10 17:56:58.370889
parameters_json:
  {"by_text": "Justification de la d\u00e9cision", "visual_anchor": {"anchor_id": "anchor_1958d72f71c4_1778164548", "bounding_box": {"height": 31, "width": 619, "x": 1350, "y": 981}}}


id: step_073e3ef34b62_1778422832
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_807d29c6ab5b_1778422860
label: click_anchor
created_at: 2026-05-10 14:20:32.395545
updated_at: 2026-05-10 17:45:25.710331
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_807d29c6ab5b_1778422860", "bounding_box": {"x": 784, "y": 424, "width": 234, "height": 45}}}


id: st_0a2a80ee8fc1
workflow_id: wf_test_etscroll_2026_05_10
action_type: pause_for_human
label: Préparer page longue
created_at: 2026-05-10T16:21:53.020153
updated_at: 2026-05-10T16:21:53.020153
parameters_json:
  {"message": "Ouvre une page web longue (Wikipedia FR par ex), positionne-la au premier plan puis valide pour lancer l'extraction scroll."}


id: step_175980693283_1778434840
workflow_id: wf_a38aeebea5e6_1778162737
action_type: click_anchor
anchor_id: anchor_7ed58bbe1194_1778434871
label: click_anchor
created_at: 2026-05-10 17:40:40.399660
updated_at: 2026-05-10 18:25:33.615644
parameters_json:
  {"visual_anchor": {"anchor_id": "anchor_7ed58bbe1194_1778434871", "bounding_box": {"x": 264, "y": 421, "width": 199, "height": 51}}}


# executions

id: exec_2e307672cb0d_1769201817
workflow_id: wf_d55b71373f0a_1769184759
status: error
started_at: 2026-01-23 20:56:57.753172
ended_at: 2026-01-23 20:57:10.891965
error_message:
  Contrat violé à l'étape 7: Contrat violé pour 'ai_analyze_text': Paramètre obligatoire 'visual_anchor' manquant pour l'action 'ai_analyze_text'; Paramètre obligatoire 'analysis_prompt' manquant pour l'action 'ai_analyze_text'


id: exec_db0a034da25f_1769207607
workflow_id: wf_d55b71373f0a_1769184759
status: error
started_at: 2026-01-23 22:33:27.424794
ended_at: 2026-01-23 22:33:32.526149
error_message:
  Erreur à l'étape 4: Ancre non trouvée à l'écran (confiance: 0.28). Confiance trop faible pour utiliser les coordonnées statiques


id: exec_1497ee6673fa_1769448615
workflow_id: wf_d55b71373f0a_1769184759
status: error
started_at: 2026-01-26 17:30:15.636372
ended_at: 2026-01-26 17:31:13.747520
error_message:
  Contrat violé à l'étape 13: Contrat violé pour 'click_anchor': Paramètre obligatoire 'visual_anchor' manquant pour l'action 'click_anchor'


id: exec_08c080cec58d_1773753520
workflow_id: wf_372eabf626f8_1773752892
status: error
started_at: 2026-03-17 13:18:40.623541
ended_at: 2026-03-17 13:18:45.913630
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.27). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_81ad0ae724a9_1773753981
workflow_id: wf_372eabf626f8_1773752892
status: error
started_at: 2026-03-17 13:26:21.624533
ended_at: 2026-03-17 13:26:26.143491
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.24). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_db486fa017cb_1773753996
workflow_id: wf_372eabf626f8_1773752892
status: error
started_at: 2026-03-17 13:26:36.746405
ended_at: 2026-03-17 13:26:44.977672
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.65). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_956e34b2fb65_1773754031
workflow_id: wf_372eabf626f8_1773752892
status: error
started_at: 2026-03-17 13:27:11.877786
ended_at: 2026-03-17 13:27:17.209654
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.39). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_cbd3a2bb5677_1773754429
workflow_id: wf_372eabf626f8_1773752892
status: error
started_at: 2026-03-17 13:33:50.056814
ended_at: 2026-03-17 13:33:56.822810
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.23). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_4366d7fb85a4_1776524248
workflow_id: wf_f87a537d53fc_1776523414
status: error
started_at: 2026-04-18 14:57:28.924454
ended_at: 2026-04-18 14:57:37.908658
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.81). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_82d946f97831_1776534241
workflow_id: wf_f87a537d53fc_1776523414
status: error
started_at: 2026-04-18 17:44:01.671802
ended_at: 2026-04-18 17:44:10.020941
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.99). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_f1f8b5f420c2_1776534866
workflow_id: wf_f87a537d53fc_1776523414
status: error
started_at: 2026-04-18 17:54:26.973816
ended_at: 2026-04-18 17:54:35.497632
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.96). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_a298e9ac51c2_1776544788
workflow_id: wf_650cdfe60f4d_1776439665
status: error
started_at: 2026-04-18 20:39:49.095523
ended_at: 2026-04-18 20:39:49.105034
error_message:
  Contrat violé à l'étape 1: Contrat violé pour 'click_anchor': Paramètre obligatoire 'visual_anchor' manquant pour l'action 'click_anchor'


id: exec_ff8529f2f1e5_1776550630
workflow_id: wf_f87a537d53fc_1776523414
status: error
started_at: 2026-04-18 22:17:12.564484
ended_at: 2026-04-18 22:17:14.780227
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.00). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_1bf09844aa12_1776677485
workflow_id: wf_46cb704f1971_1776591579
status: error
started_at: 2026-04-20 09:31:27.727842
ended_at: 2026-04-20 09:31:32.852567
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.52). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_0dd42f3596f8_1776755358
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 07:09:20.013505
ended_at: 2026-04-21 07:09:26.499774
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.53). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_593c08796cc5_1776755407
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 07:10:09.783395
ended_at: 2026-04-21 07:10:14.147955
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.47). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_1e498fa5dfe0_1776758014
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 07:53:35.835634
ended_at: 2026-04-21 07:55:46.173212
error_message:
  Erreur à l'étape 1: Ancre non trouvée à l'écran (confiance: 0.50). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_b01080fe5a4c_1776781208
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 14:20:10.766305
ended_at: 2026-04-21 14:21:58.659375
error_message:
  Erreur à l'étape 1: Erreur vision: cannot access local variable 'result' where it is not associated with a value. Ancre introuvable à l'écran.


id: exec_0bd34d90a270_1776785295
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 15:28:17.159982
ended_at: 2026-04-21 15:31:48.489553
error_message:
  Erreur à l'étape 5: Ancre non trouvée à l'écran (confiance: 0.49). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_7d03492a1e6d_1776789662
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-21 16:41:04.129607
ended_at: 2026-04-21 16:41:09.530777
error_message:
  Erreur à l'étape 1: Erreur vision: PyAutoGUI fail-safe triggered from mouse moving to a corner of the screen. To disable this fail-safe, set pyautogui.FAILSAFE to False. DISABLING FAIL-SAFE IS NOT RECOMMENDED.. Ancre introuvable à l'écran.


id: exec_e08183381171_1776860440
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 12:20:42.467437
ended_at: 2026-04-22 12:21:34.021152
error_message:
  Erreur à l'étape 2: Ancre non trouvée à l'écran (confiance: 0.44). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_503c45a08b69_1776860891
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 12:28:12.904849
ended_at: 2026-04-22 12:29:20.037992
error_message:
  Erreur à l'étape 2: Ancre non trouvée à l'écran (confiance: 0.43). Aucune méthode visuelle n'a trouvé l'ancre à l'écran


id: exec_4f9e547c16d4_1776862161
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 12:49:23.385546
ended_at: 2026-04-22 12:50:33.018013
error_message:
  Étape 4: vérification échouée — Aucun changement détecté (distance=0) | VLM: matches=False, état='Le texte sélectionné n'a pas été copié.'


id: exec_081c2988d7c8_1776862471
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 12:54:33.585687
ended_at: 2026-04-22 12:55:34.305956
error_message:
  Étape 5: vérification échouée — Aucun changement détecté (distance=0) | VLM: matches=False, état='...'


id: exec_1ba088bc46d1_1776869452
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 14:50:54.303901
ended_at: 2026-04-22 14:51:32.770776
error_message:
  Étape 1: element_not_found — recovery 'exhausted' échoué. Élément 'emo' introuvable après attente + scroll + UI-TARS élargi


id: exec_c64d69ac0b0c_1776870341
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 15:05:43.300462
ended_at: 2026-04-22 15:06:13.319901
error_message:
  Étape 1: overlay_blocking — recovery 'close_dialog_retry_failed' échoué. Dialogue fermé mais l'action originale a encore échoué


id: exec_18ce6dc1d741_1776870389
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 15:06:31.300443
ended_at: 2026-04-22 15:07:21.512637
error_message:
  Étape 2: overlay_blocking — recovery 'close_dialog_retry_failed' échoué. Dialogue fermé mais l'action originale a encore échoué


id: exec_dae56d34d605_1776880796
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-22 17:59:58.080830
ended_at: 2026-04-22 18:00:31.114005
error_message:
  Étape 7: overlay_blocking — recovery 'close_dialog_retry_failed' échoué. Dialogue fermé mais l'action originale a encore échoué


id: exec_3b6af3505934_1776925078
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 06:17:59.986541
ended_at: 2026-04-23 06:18:13.153452
error_message:
  Étape 1: overlay_blocking — recovery 'error' échoué. Erreur recovery overlay: 'NoneType' object has no attribute 'get'


id: exec_c340bf5c71ae_1776936792
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 09:33:14.466097
ended_at: 2026-04-23 09:33:44.318088
error_message:
  Étape 1: overlay_blocking — recovery 'close_overlay_retry_failed' échoué. Overlay 'dialog_ok' résolu mais l'action originale a encore échoué


id: exec_835405031300_1776946066
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 12:07:48.213273
ended_at: 2026-04-23 12:08:02.773475
error_message:
  Étape 1: overlay_blocking — recovery 'close_overlay_retry_failed' échoué. Overlay 'fenêtre' résolu mais l'action originale a encore échoué


id: exec_90162f5fcc6e_1776946527
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 12:15:29.681385
ended_at: 2026-04-23 12:16:05.565339
error_message:
  Étape 7: overlay_blocking — recovery 'close_overlay_retry_failed' échoué. Overlay 'fenêtre' résolu mais l'action originale a encore échoué


id: exec_4cc78ad098b1_1776955289
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 14:41:31.071886
ended_at: 2026-04-23 14:42:14.608715
error_message:
  Étape 5: element_not_found — recovery 'exhausted' échoué. Élément 'Search bar with magnifier icon.' introuvable après attente + scroll + UI-TARS élargi


id: exec_2d303d25a354_1776958911
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 15:41:54.081672
ended_at: 2026-04-23 15:43:26.109025
error_message:
  Étape 2: element_not_found — recovery 'exhausted' échoué. Élément 'CR_patient demo' introuvable après attente + scroll + UI-TARS élargi


id: exec_cdb6a96597d6_1776960202
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-23 16:03:25.699731
ended_at: 2026-04-23 16:04:23.654753
error_message:
  Étape 2: wrong_screen — recovery 'alt_tab' partiel. Double-clic : changement mineur insuffisant (distance=6), attendu majeur | VLM: matches=False, état='L'écran n'a pas changé après le clic sur 'CR_patient demo'.'


id: exec_d6c5c44c986b_1777224112
workflow_id: wf_46cb704f1971_1776591579
status: error
started_at: 2026-04-26 17:21:54.748577
ended_at: 2026-04-26 17:22:36.762835
error_message:
  Étape 6: raccourci 'ctrl+shift+s' — cascade post-raccourci non résolue (dialogue absent ou bloqué). Workflow stoppé pour éviter un clic dans un contexte incohérent.


id: exec_8257fd9acd9b_1777242361
workflow_id: wf_1cc92ee05159_1776752816
status: error
started_at: 2026-04-26 22:26:03.233922
ended_at: 2026-04-26 22:26:22.625453
error_message:
  Étape 4: raccourci 'ctrl+A,ctrl+c' — cascade post-raccourci non résolue (dialogue absent ou bloqué). Workflow stoppé pour éviter un clic dans un contexte incohérent.


id: exec_a03ab66cee24_1777578929
workflow_id: wf_b964befbfa97_1777473952
status: error
started_at: 2026-04-30 19:55:31.143205
ended_at: 2026-04-30 19:56:49.736337
error_message:
  Étape 14: overlay_blocking — recovery 'error' échoué. Erreur recovery overlay: PyAutoGUI fail-safe triggered from mouse moving to a corner of the screen. To disable this fail-safe, set pyautogui.FAILSAFE to False. DISABLING FAIL-SAFE IS NOT RECOMMENDED.


id: exec_d64030d091af_1777579750
workflow_id: wf_b964befbfa97_1777473952
status: error
started_at: 2026-04-30 20:09:11.876228
ended_at: 2026-04-30 20:11:07.387074
error_message:
  Étape 14: overlay_blocking — recovery 'close_overlay_retry_failed' échoué. Overlay 'fenêtre' résolu mais l'action originale a encore échoué


id: exec_054eca9e6a2f_1777643162
workflow_id: wf_b964befbfa97_1777473952
status: error
started_at: 2026-05-01 13:46:03.826149
ended_at: 2026-05-01 13:46:15.253450
error_message:
  Erreur à l'étape 14: PyAutoGUI fail-safe triggered from mouse moving to a corner of the screen. To disable this fail-safe, set pyautogui.FAILSAFE to False. DISABLING FAIL-SAFE IS NOT RECOMMENDED.


# execution_steps

execution_id: exec_391b8ae73e40_1769198657
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 20:04:17.346553
ended_at: 2026-01-23 20:04:19.635017
output_json:
  {"clicked_at": {"x": 181, "y": 551}, "mode": "debug", "confidence": 0.5167397856712341, "method": "template_matching"}


execution_id: exec_79512b0976f1_1769200540
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 20:35:40.987096
ended_at: 2026-01-23 20:35:43.247686
output_json:
  {"clicked_at": {"x": 1674, "y": 180}, "mode": "debug", "confidence": 0.5838662385940552, "method": "template_matching"}


execution_id: exec_79512b0976f1_1769200540
step_id: step_f6cdd716f062_1769200383
status: success
started_at: 2026-01-23 20:35:53.510981
ended_at: 2026-01-23 20:35:54.170947
output_json:
  {"typed": "Overview\nWe\u2019re releasing LightOnOCR-2-1B, our second-generation 1B-parameter, end-to-end vision-language OCR model optimized for state-of-the-art conversion of document pages (PDF renders) into clean, naturally ordered text without relying on multi-stage pipelines. Alongside transcription, it can also output bounding boxes for embedded figures/images for workflows that need lightweight layout cues. LightOnOCR-2 is released under the Apache 2.0 license, together with a small family of open-weight checkpoints (OCR-focused and bbox-capable variants, plus base checkpoints) that can be used by the community for fine-tuning, domain adaptation, and layout-oriented applications.\n\n01/26 UPDATE: The paper is now out! It includes the full training recipe including data/normalization pipeline, RLVR, and merging details. Read it here"}


execution_id: exec_77146d84f620_1769200560
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 20:36:00.130456
ended_at: 2026-01-23 20:36:02.449729
output_json:
  {"clicked_at": {"x": 1790, "y": 691}, "mode": "debug", "confidence": 0.5061049461364746, "method": "template_matching"}


execution_id: exec_2e307672cb0d_1769201817
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 20:56:57.755935
ended_at: 2026-01-23 20:57:00.017413
output_json:
  {"clicked_at": {"x": 1789, "y": 879}, "mode": "debug", "confidence": 0.5394411683082581, "method": "template_matching"}


execution_id: exec_2e307672cb0d_1769201817
step_id: step_0c7fba2458fe_1769201174
status: error
started_at: 2026-01-23 20:57:10.884586
ended_at: 2026-01-23 20:57:10.887359
output_json: {}
error_message:
  Contrat violé: Contrat violé pour 'ai_analyze_text': Paramètre obligatoire 'visual_anchor' manquant pour l'action 'ai_analyze_text'; Paramètre obligatoire 'analysis_prompt' manquant pour l'action 'ai_analyze_text'


execution_id: exec_36dff01ef107_1769201877
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 20:57:57.310530
ended_at: 2026-01-23 20:57:59.440199
output_json:
  {"clicked_at": {"x": 1784, "y": 497}, "mode": "debug", "confidence": 0.6574908494949341, "method": "template_matching"}


execution_id: exec_68f3ca92cda2_1769203345
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:22:25.482165
ended_at: 2026-01-23 21:22:27.695310
output_json:
  {"clicked_at": {"x": 1786, "y": 768}, "mode": "debug", "confidence": 0.7270947098731995, "method": "template_matching"}


execution_id: exec_d450fb7afe4f_1769203399
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:23:19.947896
ended_at: 2026-01-23 21:23:22.153377
output_json:
  {"clicked_at": {"x": 1786, "y": 768}, "mode": "debug", "confidence": 0.7001616358757019, "method": "template_matching"}


execution_id: exec_f8b20943ab6c_1769203458
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:24:19.276392
ended_at: 2026-01-23 21:24:21.440020
output_json:
  {"clicked_at": {"x": 1781, "y": 580}, "mode": "debug", "confidence": 0.7132450342178345, "method": "template_matching"}


execution_id: exec_6bff96218179_1769203898
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:31:38.678772
ended_at: 2026-01-23 21:31:41.791774
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_6bff96218179_1769203898
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 21:31:42.130623
ended_at: 2026-01-23 21:31:44.355439
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_6bff96218179_1769203898
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:31:44.362390
ended_at: 2026-01-23 21:31:46.602583
output_json:
  {"clicked_at": {"x": 1443, "y": 856}, "mode": "debug", "confidence": 0.5064713954925537, "method": "template_matching"}


execution_id: exec_6bff96218179_1769203898
step_id: step_f6cdd716f062_1769200383
status: success
started_at: 2026-01-23 21:31:51.617951
ended_at: 2026-01-23 21:31:52.498248
output_json:
  {"typed": "Overview\nWe\u2019re releasing LightOnOCR-2-1B, our second-generation 1B-parameter, end-to-end vision-lang..."}


execution_id: exec_d9b15b607d59_1769204043
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:34:03.935934
ended_at: 2026-01-23 21:34:04.155585
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8522899150848389, "method": "direct_template"}


execution_id: exec_d9b15b607d59_1769204043
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:34:06.757157
ended_at: 2026-01-23 21:34:06.987002
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8585057258605957, "method": "direct_template"}


execution_id: exec_6f93bce97171_1769204067
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:34:27.608702
ended_at: 2026-01-23 21:34:27.833468
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8560399413108826, "method": "direct_template"}


execution_id: exec_6f93bce97171_1769204067
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:34:30.497078
ended_at: 2026-01-23 21:34:30.746459
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8704209327697754, "method": "direct_template"}


execution_id: exec_7a9e4715b5fc_1769204198
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:36:38.595446
ended_at: 2026-01-23 21:36:38.814453
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8541945219039917, "method": "direct_template"}


execution_id: exec_7a9e4715b5fc_1769204198
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:36:41.502877
ended_at: 2026-01-23 21:36:41.735232
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8704099059104919, "method": "direct_template"}


execution_id: exec_af417afb25e5_1769204276
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:37:56.597417
ended_at: 2026-01-23 21:37:56.801562
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8560340404510498, "method": "direct_template"}


execution_id: exec_af417afb25e5_1769204276
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:37:59.524037
ended_at: 2026-01-23 21:38:01.899573
output_json:
  {"clicked_at": {"x": 830, "y": 193}, "mode": "debug", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_da5fc3eab359_1769204412
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:40:12.617670
ended_at: 2026-01-23 21:40:12.849310
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8479530215263367, "method": "direct_template"}


execution_id: exec_da5fc3eab359_1769204412
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:40:15.628107
ended_at: 2026-01-23 21:40:15.861632
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8703793287277222, "method": "direct_template"}


execution_id: exec_0d7da6d8d9db_1769204756
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:46:03.151653
ended_at: 2026-01-23 21:46:08.954147
output_json:
  {"analysis": "Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration d'OCR (Optical Character Recognition) 1B-param\u00e9trique, optimis\u00e9 pour la conversion de documents en images (PDF) en langage visuel. LightOnOCR-2 est disponible sous licence Apache 2.0 et est con\u00e7u pour les applications OCR-focused et bbox-capables, avec des checkpoints (points de base) l\u00e9gers et des applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_010a86301d5b_1769204770
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:46:17.296128
ended_at: 2026-01-23 21:46:32.231825
output_json:
  {"analysis": "Traduction en fran\u00e7ais :\n\nNous sommes heureux de vous annoncer la sortie de LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration d'OCR (Optical Character Recognition) 1B-param\u00e9trique, optimis\u00e9 pour la conversion de documents en langue visuelle. Ce mod\u00e8le est optimis\u00e9 pour la conversion de documents en PDF en rendant les pages en images ou en texte. Il peut \u00e9galement fournir des bo\u00eetes de bordure pour les figures et les images. LightOnOCR-2 est disponible sous licence Apache 2.0 et est con\u00e7u pour \u00eatre utilis\u00e9 par la communaut\u00e9 pour la fine-tuning, la dommification et l'adaptation, et les applications orient\u00e9es par la structure.\n\nR\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2.1B est une nouvelle version d'OCR 1B-param\u00e9trique optimis\u00e9e pour la conversion de documents en langue visuelle.\n2. Il peut convertir des pages en images ou en texte et fournir des bo\u00eetes de bordure pour les figures et les images.\n3. Disponible sous licence Apache 2.0, il est con\u00e7u pour \u00eatre utilis\u00e9 par la communaut\u00e9 pour la fine-tuning, la dommification et l'adaptation, et les applications orient\u00e9es par la structure.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_b778a7a9341f_1769204808
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:46:54.818280
ended_at: 2026-01-23 21:47:08.894414
output_json:
  {"analysis": "Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration d'OCR (Optical Character Recognition) 1B-param\u00e8tre, avec une fin de ligne visuelle. C'est une version optimis\u00e9e pour la conversion de pages PDF documentaires (PDF renders) en texte ordonn\u00e9 et net sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. Elle g\u00e9n\u00e8re \u00e9galement des bordures pour les figures/ images int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous licence Apache 2.0, avec une famille de checkpoints (OCR-focused et bbox-capables) plus petites, utilis\u00e9e par la communaut\u00e9 pour la fine-tuning, la dommisation, et les applications orient\u00e9es par le layout.\n\nR\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2.1B est la deuxi\u00e8me g\u00e9n\u00e9ration d'OCR 1B-param\u00e8tre avec une fin de ligne visuelle.\n2. Il est optimis\u00e9 pour la conversion de pages PDF documentaires en texte ordonn\u00e9 et net sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n3. Il g\u00e9n\u00e8re des bordures pour les figures/images int\u00e9gr\u00e9es et est disponible sous licence Apache 2.0.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_b778a7a9341f_1769204808
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 21:47:19.448922
ended_at: 2026-01-23 21:47:20.052529
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\nTraduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8..."}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:47:47.599174
ended_at: 2026-01-23 21:47:47.918233
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "intelligent", "confidence": 0.7761169672012329, "method": "direct_template"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 21:47:48.235425
ended_at: 2026-01-23 21:47:49.686624
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "intelligent", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:47:49.691823
ended_at: 2026-01-23 21:47:49.868624
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "intelligent", "confidence": 0.8695372939109802, "method": "direct_template"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:47:55.652701
ended_at: 2026-01-23 21:48:10.298574
output_json:
  {"analysis": "Voici la traduction int\u00e9grale en fran\u00e7ais du texte :\n\n\"Nous sortons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration 1B-param\u00e8tre, OCR end-to-end vision-language OCR, mod\u00e8le optimis\u00e9 pour la conversion d'OCR de documents en texte ordonn\u00e9 sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. Il peut \u00e9galement produire des bo\u00eetes de bordure pour les figures/images int\u00e9gr\u00e9es. LightOnOCR-2 est sorti sous Apache 2.0 License, avec des variantes OCR-focused et bbox-capable, des checkpoints (OCR-focused et bbox-capables) bas\u00e9s sur un petit ensemble de checkpoints, utilis\u00e9s par la communaut\u00e9 pour la fine-tuning, adaptation de domaine et applications orient\u00e9es par le layout.\"\n\nVoici le r\u00e9sum\u00e9 en trois points cl\u00e9s :\n\n1. LightOnOCR-2.1B est une version optimis\u00e9e pour la conversion d'OCR de documents en texte ordonn\u00e9, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n2. Il produit des bo\u00eetes de bordure pour les figures/images int\u00e9gr\u00e9es et est sorti sous Apache 2.0 License.\n3. Il est utilis\u00e9 par la communaut\u00e9 pour la fine-tuning, adaptation de domaine et applications orient\u00e9es par le layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-23 21:48:10.311009
ended_at: 2026-01-23 21:48:10.519061
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "intelligent", "confidence": 0.801433801651001, "method": "direct_template"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 21:48:10.834570
ended_at: 2026-01-23 21:48:12.409830
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "intelligent", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_f869db4e5d5b_1769204867
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 21:48:22.423885
ended_at: 2026-01-23 21:48:23.051841
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\nVoici la traduction int\u00e9grale en fran\u00e7ais du texte :\n\n\"Nous sortons ..."}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:48:58.770740
ended_at: 2026-01-23 21:48:59.011313
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.7742404937744141, "method": "direct_template"}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:49:01.555333
ended_at: 2026-01-23 21:49:01.780981
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.86947101354599, "method": "direct_template"}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:49:07.698205
ended_at: 2026-01-23 21:49:32.752727
output_json:
  {"analysis": "Voici la traduction int\u00e9grale en fran\u00e7ais du texte :\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration d'OCR (outil d'OCR) 1B param\u00e9trique, avec une optimisation mod\u00e8le pour l'OCR de documents (PDF) en rendant les pages OCR en texte ordonn\u00e9 et sans relire, sans passer par des pipelines multi-\u00e9tapes. En outre, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bordures pour les figures/images int\u00e9gr\u00e9es, ce qui est utile pour les workflows qui n\u00e9cessitent des cotes de layout l\u00e9geres. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec des versions OCR-focused et bbox-capables, ainsi que des checkpoints de base l\u00e9gers (avec une famille ouverte de checkpoints OCR-focused et bbox-capables, plus bas\u00e9s sur des checkpoints de base l\u00e9gers) utilis\u00e9s par la communaut\u00e9 pour la fine-tuning, la dommification, et les applications orient\u00e9es par le layout.\n\nR\u00e9sum\u00e9 en 3 points cl\u00e9s :\n1. LightOnOCR-2.1B est la deuxi\u00e8me g\u00e9n\u00e9ration d'OCR 1B param\u00e9trique avec une optimisation mod\u00e8le pour les documents PDF.\n2. Il rend les pages OCR en texte ordonn\u00e9 et sans relire, sans passer par des pipelines multi-\u00e9tapes.\n3. Il g\u00e9n\u00e8re des bordures pour les figures/images int\u00e9gr\u00e9es, ce qui est utile pour les workflows avec des cotes de layout l\u00e9geres.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-23 21:49:32.764522
ended_at: 2026-01-23 21:49:33.041693
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8014438152313232, "method": "direct_template"}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 21:49:33.362661
ended_at: 2026-01-23 21:49:35.615312
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.3, "method": "static_fallback"}


execution_id: exec_f8d28c291ecb_1769204938
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 21:49:45.631339
ended_at: 2026-01-23 21:49:46.315785
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\nVoici la traduction int\u00e9grale en fran\u00e7ais du texte :\n\nNous lan\u00e7ons L..."}


execution_id: exec_a9b455060948_1769204999
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 21:49:59.605132
ended_at: 2026-01-23 21:49:59.823001
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.7794138193130493, "method": "direct_template"}


execution_id: exec_a9b455060948_1769204999
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 21:50:02.493801
ended_at: 2026-01-23 21:50:02.722078
output_json:
  {"clicked_at": {"x": 960, "y": 540}, "mode": "debug", "confidence": 0.8694751262664795, "method": "direct_template"}


execution_id: exec_a9b455060948_1769204999
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 21:50:08.651137
ended_at: 2026-01-23 21:50:26.041672
output_json:
  {"analysis": "Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration d'OCR (Optical Character Recognition) 1B-param\u00e8tre, avec une fin de ligne visuelle. Ce mod\u00e8le est optimis\u00e9 pour la conversion de documents PDF en texte ordonn\u00e9 et sans relire, sans passer par des pipelines multi-\u00e9tapes. Il peut \u00e9galement produire des bo\u00eetes de bordage pour les figures/images int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints (OCR-focused et bbox-capables) plus petites, utilis\u00e9e par la communaut\u00e9 pour la fine-tuning, la dommage et l'adaptation, ainsi que pour les applications orient\u00e9es par le layout.\n\nR\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2.1B est la deuxi\u00e8me g\u00e9n\u00e9ration d'OCR 1B-param\u00e8tre avec une fin de ligne visuelle.\n2. Il est optimis\u00e9 pour la conversion de documents PDF en texte ordonn\u00e9 et sans relire, sans passer par des pipelines multi-\u00e9tapes.\n3. Il peut produire des bo\u00eetes de bordage pour les figures/images int\u00e9gr\u00e9es et est disponible sous la licence Apache 2.0.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_9bf12a4e76b0_1769206151
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 22:09:18.097628
ended_at: 2026-01-23 22:09:40.297051
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e8tre, optimis\u00e9 pour la conversion d'art de pointe, de pages document (PDF) en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour des figures/ images d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille petite de checkpoints ouverts l\u00e9gers (variants OCR-focused et bbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   1. **Optimisation du mod\u00e8le OCR 1B :** LightOnOCR-2 est une version am\u00e9lior\u00e9e du mod\u00e8le OCR 1B, con\u00e7u pour la conversion d'art de pointe et la transcription de pages document en texte ordonn\u00e9 naturellement.\n   2. **Fonctionnalit\u00e9s suppl\u00e9mentaires :** Outre la transcription, LightOnOCR-2 peut produire des bo\u00eetes de bordure pour des figures/images d'embedd\u00e9s, ce qui est utile pour les workflows n\u00e9cessitant des layouts l\u00e9gers.\n   3. **Licence et utilisation :** LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille petite de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_9bf12a4e76b0_1769206151
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 22:09:50.848606
ended_at: 2026-01-23 22:09:51.497805
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. **Traduction en fran\u00e7ais :**\n   Nous lan\u00e7ons LightOnOCR-2-1B, not..."}


execution_id: exec_682a9956208f_1769206293
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 22:11:34.003429
ended_at: 2026-01-23 22:11:34.759384
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.9999995231628418, "method": "direct_template"}


execution_id: exec_682a9956208f_1769206293
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:11:35.080437
ended_at: 2026-01-23 22:11:35.596560
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7877556085586548, "method": "direct_template"}


execution_id: exec_682a9956208f_1769206293
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 22:11:44.014377
ended_at: 2026-01-23 22:12:04.651999
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique, optimis\u00e9 pour la conversion d'art de pointe, de pages documentaires (PDF) en texte ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement extraire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focused et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique optimis\u00e9 pour la conversion d'art de pointe de pages documentaires en texte ordonn\u00e9 naturellement.\n2. Il peut \u00e9galement extraire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es.\n3. Disponible sous la licence Apache 2.0, il est accompagn\u00e9 d'une famille de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_682a9956208f_1769206293
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-23 22:12:04.677962
ended_at: 2026-01-23 22:12:05.044558
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.9999999403953552, "method": "direct_template"}


execution_id: exec_682a9956208f_1769206293
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 22:12:05.362377
ended_at: 2026-01-23 22:12:05.823760
output_json:
  {"clicked_at": {"x": 902, "y": 392}, "mode": "debug", "confidence": 0.8731901049613953, "method": "direct_template"}


execution_id: exec_682a9956208f_1769206293
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 22:12:15.841011
ended_at: 2026-01-23 22:12:16.627837
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deu..."}


execution_id: exec_334b5a1afb7a_1769206385
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 22:13:05.772928
ended_at: 2026-01-23 22:13:06.105026
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 1.0, "method": "direct_template"}


execution_id: exec_334b5a1afb7a_1769206385
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:13:06.428058
ended_at: 2026-01-23 22:13:06.924891
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.78508460521698, "method": "direct_template"}


execution_id: exec_334b5a1afb7a_1769206385
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 22:13:15.294055
ended_at: 2026-01-23 22:13:34.493588
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art documentaire de pointe, en rendant les pages PDF (PDF rendus) en texte ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focusedes et bbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre optimis\u00e9 pour la conversion d'art documentaire de pointe.\n2. Il peut convertir les pages PDF en texte ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n3. Il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_334b5a1afb7a_1769206385
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 22:13:35.195582
ended_at: 2026-01-23 22:13:35.594538
output_json:
  {"clicked_at": {"x": 902, "y": 392}, "mode": "debug", "confidence": 0.8738170266151428, "method": "direct_template"}


execution_id: exec_c517a22665ce_1769206495
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:14:56.919847
ended_at: 2026-01-23 22:14:57.383447
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7874513268470764, "method": "direct_template"}


execution_id: exec_c517a22665ce_1769206495
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 22:15:05.725836
ended_at: 2026-01-23 22:15:27.863335
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique, optimis\u00e9 pour la conversion d'art d'\u00c9tat de l'art de pages documentaires (PDF rendus) en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focused et bbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fine-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique optimis\u00e9 pour la conversion d'art d'\u00c9tat de l'art de pages documentaires en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n\n2. LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es.\n\n3. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fine-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_c517a22665ce_1769206495
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 22:15:28.569711
ended_at: 2026-01-23 22:15:28.990112
output_json:
  {"clicked_at": {"x": 902, "y": 392}, "mode": "debug", "confidence": 0.8740014433860779, "method": "direct_template"}


execution_id: exec_db0a034da25f_1769207607
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 22:33:27.429169
ended_at: 2026-01-23 22:33:28.707494
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.9999998807907104, "method": "direct_template"}


execution_id: exec_db0a034da25f_1769207607
step_id: step_957fe56946d0_1769200014
status: error
started_at: 2026-01-23 22:33:30.119249
ended_at: 2026-01-23 22:33:32.521122
output_json: {}
error_message:
  Ancre non trouvée à l'écran (confiance: 0.28). Confiance trop faible pour utiliser les coordonnées statiques


execution_id: exec_1fc93b017f14_1769207706
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:35:07.621547
ended_at: 2026-01-23 22:35:08.608327
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7874511480331421, "method": "direct_template"}


execution_id: exec_f8a414f196fd_1769208068
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:41:09.933298
ended_at: 2026-01-23 22:41:10.984994
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7858930230140686, "method": "direct_template"}


execution_id: exec_67fab3bd2607_1769209133
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 22:58:53.404765
ended_at: 2026-01-23 22:58:56.192619
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.9999997615814209, "method": "direct_template"}


execution_id: exec_67fab3bd2607_1769209133
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 22:58:56.528529
ended_at: 2026-01-23 22:58:58.968895
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7858936190605164, "method": "direct_template"}


execution_id: exec_a03232c13907_1769209679
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 23:08:05.785784
ended_at: 2026-01-23 23:08:24.711799
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique, optimis\u00e9 pour l'OCR de document pages (PDF rendus) en texte naturellement ordonn\u00e9 sans d\u00e9pendance \u00e0 un pipeline multi-\u00e9tapes. Il peut \u00e9galement extraire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (OCR-focused et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n1. LightOnOCR-2-1B est un mod\u00e8le OCR 1B param\u00e9trique optimis\u00e9 pour la conversion de document pages en texte naturellement ordonn\u00e9, sans d\u00e9pendance \u00e0 un pipeline multi-\u00e9tapes.\n2. Il peut extraire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es.\n3. Disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_a03232c13907_1769209679
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 23:08:35.266385
ended_at: 2026-01-23 23:08:35.891375
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. Traduction en fran\u00e7ais :\nNous lan\u00e7ons LightOnOCR-2-1B, notre deux..."}


execution_id: exec_430db49f80df_1769210971
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 23:29:31.718225
ended_at: 2026-01-23 23:29:35.997999
output_json:
  {"clicked_at": {"x": 33, "y": 1045}, "mode": "debug", "confidence": 0.7578654289245605, "method": "template_matching"}


execution_id: exec_430db49f80df_1769210971
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 23:29:36.335118
ended_at: 2026-01-23 23:29:40.544216
output_json:
  {"clicked_at": {"x": 543, "y": 395}, "mode": "debug", "confidence": 0.6776206493377686, "method": "template_matching"}


execution_id: exec_9166261a3425_1769211667
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 23:41:14.037665
ended_at: 2026-01-23 23:41:31.909982
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous d\u00e9voilons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de l'art, le rendu des pages documentaires (PDF) en texte naturellement ordonn\u00e9 sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focusedes et bbbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-oriented.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   1. **Optimisation du mod\u00e8le OCR 1B-param\u00e8tre :** LightOnOCR-2-1B est un mod\u00e8le OCR 1B-param\u00e8tre optimis\u00e9 pour la conversion d'art de l'art et le rendu des pages documentaires en texte naturellement ordonn\u00e9.\n   2. **Fonctionnalit\u00e9s suppl\u00e9mentaires :** En plus de la transcription, LightOnOCR-2 peut produire des bo\u00eetes de bordure pour les images/figures int\u00e9gr\u00e9es.\n   3. **Licence et utilisation :** LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-oriented.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_9166261a3425_1769211667
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-23 23:41:42.471835
ended_at: 2026-01-23 23:41:43.110171
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. **Traduction en fran\u00e7ais :**\n   Nous d\u00e9voilons LightOnOCR-2-1B, n..."}


execution_id: exec_571f83038294_1769211902
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 23:45:05.448012
ended_at: 2026-01-23 23:45:07.846231
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7856922149658203, "method": "direct_template"}


execution_id: exec_4c2f424fac58_1769212324
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 23:52:05.042793
ended_at: 2026-01-23 23:52:09.252923
output_json:
  {"clicked_at": {"x": 33, "y": 1044}, "mode": "debug", "confidence": 0.7160431146621704, "method": "template_matching"}


execution_id: exec_4c2f424fac58_1769212324
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 23:52:09.589673
ended_at: 2026-01-23 23:52:13.865278
output_json:
  {"clicked_at": {"x": 542, "y": 395}, "mode": "debug", "confidence": 0.6741790175437927, "method": "template_matching"}


execution_id: exec_b80fbfaf5c79_1769212512
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 23:55:12.578007
ended_at: 2026-01-23 23:55:16.840143
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.6901190280914307, "method": "template_matching"}


execution_id: exec_b80fbfaf5c79_1769212512
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 23:55:17.180593
ended_at: 2026-01-23 23:55:21.361197
output_json:
  {"clicked_at": {"x": 548, "y": 579}, "mode": "debug", "confidence": 0.6715579628944397, "method": "template_matching"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-23 23:57:32.824145
ended_at: 2026-01-23 23:57:48.902518
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.9934886886881167, "method": "clip_embedding"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-23 23:57:49.237855
ended_at: 2026-01-23 23:57:58.416631
output_json:
  {"clicked_at": {"x": 999, "y": 78}, "mode": "debug", "confidence": 0.530487498529437, "method": "clip_embedding"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-23 23:57:58.426798
ended_at: 2026-01-23 23:58:05.166859
output_json:
  {"clicked_at": {"x": 993, "y": 193}, "mode": "debug", "confidence": 0.5228413404355092, "method": "clip_embedding"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-23 23:58:10.977226
ended_at: 2026-01-23 23:58:31.011164
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique, optimis\u00e9 pour la conversion d'art de pointe, de pages PDF en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 un pipeline multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images embedd\u00e9es qui n\u00e9cessitent une layout de type cue. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille petite de checkpoints ouverts (variantes OCR-focused et bbox-capables, plus de checkpoints de base) utilisables pour la fin-tuning, l'adaptation de domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n1. LightOnOCR-2-1B est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique optimis\u00e9 pour la conversion d'art de pointe.\n2. Il peut convertir des pages PDF en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 un pipeline multi-\u00e9tapes.\n3. Il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images embedd\u00e9es qui n\u00e9cessitent une layout de type cue.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-23 23:58:31.036668
ended_at: 2026-01-23 23:58:41.677763
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9897915177028853, "method": "clip_embedding"}


execution_id: exec_f2ca09c3755c_1769212652
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-23 23:58:42.014758
ended_at: 2026-01-23 23:58:50.817437
output_json:
  {"clicked_at": {"x": 907, "y": 399}, "mode": "debug", "confidence": 0.573372862593895, "method": "clip_embedding"}


execution_id: exec_3b7537e24a67_1769213560
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 00:12:40.546133
ended_at: 2026-01-24 00:12:42.678896
output_json:
  {"clicked_at": {"x": 32, "y": 1046.0}, "mode": "debug", "confidence": 0.9999958276748657, "method": "zoned_template"}


execution_id: exec_3b7537e24a67_1769213560
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:12:43.018380
ended_at: 2026-01-24 00:12:45.151925
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7741063237190247, "method": "zoned_template"}


execution_id: exec_4514313fa2b5_1769213590
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:13:13.377154
ended_at: 2026-01-24 00:13:15.519960
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7724428176879883, "method": "zoned_template"}


execution_id: exec_25ce143a2ddb_1769213607
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:13:30.163442
ended_at: 2026-01-24 00:13:32.286450
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7718586325645447, "method": "zoned_template"}


execution_id: exec_7d7e7379e564_1769213955
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:19:18.704559
ended_at: 2026-01-24 00:19:20.840833
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7741416096687317, "method": "zoned_template"}


execution_id: exec_95762ad2180d_1769214023
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:20:25.783098
ended_at: 2026-01-24 00:20:27.900614
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7719725370407104, "method": "zoned_template"}


execution_id: exec_ecfea6dc2c1a_1769214086
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:21:29.656238
ended_at: 2026-01-24 00:21:31.774919
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.770013689994812, "method": "zoned_template"}


execution_id: exec_a7192c932ed7_1769214160
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:22:43.422441
ended_at: 2026-01-24 00:22:45.540633
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7715970277786255, "method": "zoned_template"}


execution_id: exec_565512faceba_1769214186
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:23:09.322987
ended_at: 2026-01-24 00:23:11.441108
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7741491198539734, "method": "zoned_template"}


execution_id: exec_f15886260893_1769214846
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 00:34:07.259808
ended_at: 2026-01-24 00:34:09.800140
output_json:
  {"clicked_at": {"x": 32, "y": 1046.0}, "mode": "debug", "confidence": 0.9999961853027344, "method": "zoned_template"}


execution_id: exec_f15886260893_1769214846
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:34:10.127018
ended_at: 2026-01-24 00:34:12.251514
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7740614414215088, "method": "zoned_template"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 00:36:26.841216
ended_at: 2026-01-24 00:36:33.808823
output_json:
  {"clicked_at": {"x": 32, "y": 1043}, "mode": "debug", "confidence": 0.9914916106416283, "method": "clip"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:36:34.138030
ended_at: 2026-01-24 00:36:40.095865
output_json:
  {"clicked_at": {"x": 999, "y": 77}, "mode": "debug", "confidence": 0.5265238890404056, "method": "clip"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-24 00:36:40.101860
ended_at: 2026-01-24 00:36:45.157833
output_json:
  {"clicked_at": {"x": 829, "y": 78}, "mode": "debug", "confidence": 0.5113589039234205, "method": "clip"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 00:36:50.896222
ended_at: 2026-01-24 00:37:06.585171
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de pointe, de pages documentaires (PDF) en texte ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 un pipeline multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les figures/images d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec un petit ensemble de checkpoints ouverts (variantes OCR-focusedes et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est une nouvelle version de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de pointe de pages documentaires en texte ordonn\u00e9 naturellement.\n2. Le mod\u00e8le peut g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les figures/images d'embedd\u00e9s.\n3. Il est disponible sous la licence Apache 2.0 avec un petit ensemble de checkpoints ouverts utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 00:37:06.605180
ended_at: 2026-01-24 00:37:13.458308
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9897915177028853, "method": "clip"}


execution_id: exec_ccd0b272f9f1_1769214986
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-24 00:37:13.773492
ended_at: 2026-01-24 00:37:19.872231
output_json:
  {"clicked_at": {"x": 907, "y": 398}, "mode": "debug", "confidence": 0.5713946177161995, "method": "clip"}


execution_id: exec_6f53eed70188_1769215825
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 00:50:25.771142
ended_at: 2026-01-24 00:50:33.010646
output_json:
  {"clicked_at": {"x": 31, "y": 1046}, "mode": "debug", "confidence": 0.9942133136495693, "method": "clip"}


execution_id: exec_6f53eed70188_1769215825
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 00:50:33.337087
ended_at: 2026-01-24 00:50:39.243773
output_json:
  {"clicked_at": {"x": 903.0, "y": 405}, "mode": "debug", "confidence": 0.7741909623146057, "method": "zoned_template"}


execution_id: exec_f7e643c5e609_1769215928
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 00:52:08.442533
ended_at: 2026-01-24 00:52:17.928478
output_json:
  {"clicked_at": {"x": 33, "y": 1045}, "mode": "debug", "confidence": 0.9936697323146149, "method": "clip"}


execution_id: exec_5b20a319feb1_1769216413
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 01:00:13.826801
ended_at: 2026-01-24 01:00:20.743655
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9898977374801576, "method": "clip"}


execution_id: exec_5b20a319feb1_1769216413
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 01:00:21.069815
ended_at: 2026-01-24 01:00:27.321828
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.7875744104385376, "method": "direct_template"}


execution_id: exec_10680708db66_1769216540
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 01:02:20.871214
ended_at: 2026-01-24 01:02:27.688610
output_json:
  {"clicked_at": {"x": 32, "y": 1043}, "mode": "debug", "confidence": 0.9887800329846634, "method": "clip"}


execution_id: exec_10680708db66_1769216540
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 01:02:28.014027
ended_at: 2026-01-24 01:02:33.881184
output_json:
  {"clicked_at": {"x": 543, "y": 403}, "mode": "debug", "confidence": 0.785893440246582, "method": "direct_template"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 01:04:03.185963
ended_at: 2026-01-24 01:04:10.156873
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.9982145428657532, "method": "clip"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 01:04:10.484612
ended_at: 2026-01-24 01:04:16.354806
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7877290844917297, "method": "static_fallback"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-24 01:04:16.360302
ended_at: 2026-01-24 01:04:22.952825
output_json:
  {"clicked_at": {"x": 830, "y": 194}, "mode": "debug", "confidence": 0.9916513142183346, "method": "clip"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 01:04:28.697414
ended_at: 2026-01-24 01:04:42.598611
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion de texte en images d'art de pointe, rendant les pages documentaires (PDF) en texte naturellement ordonn\u00e9 sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour les images/figures d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variants OCR-focused et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n1. LightOnOCR-2-1B est une version optimis\u00e9e de 1B-param\u00e8tre pour la conversion de texte en images d'art de pointe.\n2. Il peut convertir les pages documentaires en texte naturellement ordonn\u00e9 sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n3. Il peut \u00e9galement produire des bo\u00eetes de bordure pour les images/figures d'embedd\u00e9s.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 01:04:42.614278
ended_at: 2026-01-24 01:04:51.309344
output_json:
  {"clicked_at": {"x": 32, "y": 1047}, "mode": "debug", "confidence": 0.9894511045540864, "method": "clip"}


execution_id: exec_daf00a0a07b3_1769216642
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-24 01:04:51.623819
ended_at: 2026-01-24 01:04:57.566668
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8738175630569458, "method": "static_fallback"}


execution_id: exec_c8851678e942_1769218490
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 01:34:50.869475
ended_at: 2026-01-24 01:34:57.560409
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9895028692302147, "method": "clip"}


execution_id: exec_c8851678e942_1769218490
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 01:34:57.885819
ended_at: 2026-01-24 01:35:04.787668
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7860259413719177, "method": "static_fallback"}


execution_id: exec_c8851678e942_1769218490
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 01:35:17.132512
ended_at: 2026-01-24 01:35:32.649467
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous d\u00e9voilons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de document pages (PDF) en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focusedes et bbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   - **LightOnOCR-2-1B :** Mod\u00e8le OCR 1B-param\u00e8tre de deuxi\u00e8me g\u00e9n\u00e9ration optimis\u00e9 pour la conversion d'art de document pages en texte naturellement ordonn\u00e9.\n   - **G\u00e9n\u00e9ration de bo\u00eetes de bordure :** Capacit\u00e9 \u00e0 g\u00e9n\u00e9rer des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s.\n   - **Licence Apache 2.0 :** Disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_c8851678e942_1769218490
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 01:35:32.658096
ended_at: 2026-01-24 01:35:41.198478
output_json:
  {"clicked_at": {"x": 32, "y": 1043}, "mode": "debug", "confidence": 0.9871604569223292, "method": "clip"}


execution_id: exec_c8851678e942_1769218490
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-24 01:35:41.512622
ended_at: 2026-01-24 01:35:47.361218
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8740014433860779, "method": "static_fallback"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 01:39:15.375489
ended_at: 2026-01-24 01:39:24.842588
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.9915465285459742, "method": "clip"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 01:39:25.168836
ended_at: 2026-01-24 01:39:31.187750
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7876107096672058, "method": "static_fallback"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-24 01:39:31.193312
ended_at: 2026-01-24 01:39:39.815314
output_json:
  {"clicked_at": {"x": 807, "y": 159}, "mode": "debug", "confidence": 0.5765435938619988, "method": "clip"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 01:39:45.540657
ended_at: 2026-01-24 01:40:00.115961
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   \"Nous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique, optimis\u00e9 pour la conversion d'art de pointe, de pages documentaires (PDF) en texte ordonn\u00e9 naturellement sans d\u00e9pendre de pipelines multi-\u00e9tapes. En plus de la transcription, il peut \u00e9galement produire des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille petite de checkpoints ouverts l\u00e9gers (variantes OCR-focused et bbbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\"\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   - **LightOnOCR-2-1B :** Nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B param\u00e9trique optimis\u00e9 pour la conversion d'art de pointe et la transcription de pages documentaires.\n   - **Fonctionnalit\u00e9s :** Produit des bo\u00eetes de bordure pour les figures/images d'embedd\u00e9s, disponible sous la licence Apache 2.0.\n   - **Utilisation :** Utilisable par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 01:40:00.132882
ended_at: 2026-01-24 01:40:08.343048
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.987201046009644, "method": "clip"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-24 01:40:08.657912
ended_at: 2026-01-24 01:40:14.454841
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8738173246383667, "method": "static_fallback"}


execution_id: exec_9f7bfd386b47_1769218755
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-24 01:40:24.468361
ended_at: 2026-01-24 01:40:25.043760
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. **Traduction en fran\u00e7ais :**\n   \"Nous lan\u00e7ons LightOnOCR-2-1B, no..."}


execution_id: exec_56aaca84ec43_1769249506
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 10:11:46.552449
ended_at: 2026-01-24 10:11:56.083510
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.99146564043336, "method": "clip"}


execution_id: exec_56aaca84ec43_1769249506
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 10:11:56.408358
ended_at: 2026-01-24 10:12:02.478489
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7858427166938782, "method": "static_fallback"}


execution_id: exec_56aaca84ec43_1769249506
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 10:12:14.597886
ended_at: 2026-01-24 10:12:35.909850
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion de texte en images de haute qualit\u00e9, avec une conversion de pages PDF (PDF render) en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordage pour les images/figures d'embeds, les workflows qui n\u00e9cessitent une layout OCR l\u00e9ger. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers (OCR-focused et bbox-capable, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est un mod\u00e8le OCR 1B-param\u00e8tre optimis\u00e9 pour la conversion de texte en images de haute qualit\u00e9, avec une conversion de pages PDF en texte ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n2. LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bordage pour les images/figures d'embeds, les workflows qui n\u00e9cessitent une layout OCR l\u00e9ger.\n3. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_56aaca84ec43_1769249506
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 10:12:35.924189
ended_at: 2026-01-24 10:12:44.673113
output_json:
  {"clicked_at": {"x": 33, "y": 1046}, "mode": "debug", "confidence": 0.9921684171059044, "method": "clip"}


execution_id: exec_af679c20dee4_1769252598
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 11:03:25.482877
ended_at: 2026-01-24 11:04:00.371487
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre mod\u00e8le OCR 1B g\u00e9n\u00e9rations optimis\u00e9 pour la conversion d'art de l'art en texte naturellement ordonn\u00e9 et sans d\u00e9pendance \u00e0 un pipeline de plusieurs \u00e9tapes pour convertir des pages PDF en texte clair, sans d\u00e9pendance \u00e0 un pipeline de plusieurs \u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bords pour les images/figures n\u00e9cessitant une layout l\u00e9g\u00e8re. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focused et bbox-capable, plus de checkpoints bas\u00e9s sur des checkpoints) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2 est une version 1B g\u00e9n\u00e9r\u00e9e de LightOnOCR, un mod\u00e8le OCR 1B g\u00e9n\u00e9rations optimis\u00e9 pour la conversion d'art de l'art en texte naturellement ordonn\u00e9 et sans d\u00e9pendance \u00e0 un pipeline de plusieurs \u00e9tapes.\n2. LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de bords pour les images/figures n\u00e9cessitant une layout l\u00e9g\u00e8re.\n3. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_af679c20dee4_1769252598
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-24 11:04:10.915955
ended_at: 2026-01-24 11:04:11.495780
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre mod..."}


execution_id: exec_63ec7fcacbd7_1769252698
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-24 11:04:58.705254
ended_at: 2026-01-24 11:05:00.840273
output_json:
  {"clicked_at": {"x": 32, "y": 1046.0}, "mode": "debug", "confidence": 1.0, "method": "zoned_template"}


execution_id: exec_63ec7fcacbd7_1769252698
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-24 11:05:01.155450
ended_at: 2026-01-24 11:05:04.680780
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7847930788993835, "method": "static_fallback"}


execution_id: exec_63ec7fcacbd7_1769252698
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-24 11:05:04.686013
ended_at: 2026-01-24 11:05:06.797231
output_json:
  {"clicked_at": {"x": 830.0, "y": 193.0}, "mode": "debug", "confidence": 0.999999463558197, "method": "zoned_template"}


execution_id: exec_63ec7fcacbd7_1769252698
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-24 11:05:12.506561
ended_at: 2026-01-24 11:05:15.615402
output_json:
  {"analysis": "1. Traduction en fran\u00e7ais :\n\nNous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de l'art, de pages PDF en texte nettoy\u00e9, ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers (variants OCR-focused et bbox-capables, plus de checkpoints bas\u00e9s sur des checkpoints) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\n\n2. R\u00e9sum\u00e9 en 3 points cl\u00e9s :\n\n1. LightOnOCR-2-1B est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de l'art de pages PDF en texte nettoy\u00e9 et ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n2. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\n3. LightOnOCR-2 est con\u00e7u pour \u00eatre utilis\u00e9 avec des workflows que les utilisateurs peuvent personnaliser, comme les pipelines RLL et RLLR.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_63ec7fcacbd7_1769252698
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-24 11:05:15.624489
ended_at: 2026-01-24 11:05:17.732953
output_json:
  {"clicked_at": {"x": 34, "y": 1045.0}, "mode": "debug", "confidence": 1.0, "method": "zoned_template"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-26 17:30:15.643628
ended_at: 2026-01-26 17:30:24.805302
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.9901528690631699, "method": "clip"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-26 17:30:25.131047
ended_at: 2026-01-26 17:30:31.637113
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7876390218734741, "method": "static_fallback"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-26 17:30:31.642537
ended_at: 2026-01-26 17:30:38.297476
output_json:
  {"clicked_at": {"x": 830, "y": 195}, "mode": "debug", "confidence": 0.9901882370972457, "method": "clip"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-26 17:30:44.011780
ended_at: 2026-01-26 17:30:49.615785
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous lan\u00e7ons LightOnOCR-2-1B, notre mod\u00e8le OCR de deuxi\u00e8me g\u00e9n\u00e9ration 1B param\u00e8tres, optimis\u00e9 pour la conversion d'art d'art en texte nettoy\u00e9, textes ordonn\u00e9s naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement produire des bo\u00eetes de bordure pour des figures/images pour des workflows qui n\u00e9cessitent une layout de type l\u00e9ger. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers (variantes OCR-focused et bbox-capable, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   1. **Optimisation pour la conversion d'art en texte :** LightOnOCR-2 est un mod\u00e8le OCR de deuxi\u00e8me g\u00e9n\u00e9ration 1B param\u00e8tres optimis\u00e9 pour convertir des pages PDF en texte nettoy\u00e9 et textes ordonn\u00e9s naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n   2. **Capacit\u00e9 de traitement de figures/images :** En plus de la transcription, LightOnOCR-2 peut produire des bo\u00eetes de bordure pour des figures/images pour des workflows qui n\u00e9cessitent une layout de type l\u00e9ger.\n   3. **Licence et communaut\u00e9 :** LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications layout-orient\u00e9es.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-26 17:30:49.625273
ended_at: 2026-01-26 17:30:57.398152
output_json:
  {"clicked_at": {"x": 33, "y": 1044}, "mode": "debug", "confidence": 0.9882345422949055, "method": "clip"}


execution_id: exec_1497ee6673fa_1769448615
step_id: step_3f55d65818b3_1769435138
status: error
started_at: 2026-01-26 17:31:13.733556
ended_at: 2026-01-26 17:31:13.744752
output_json: {}
error_message:
  Contrat violé: Contrat violé pour 'click_anchor': Paramètre obligatoire 'visual_anchor' manquant pour l'action 'click_anchor'


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-26 17:38:54.311811
ended_at: 2026-01-26 17:39:03.213191
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.9910466708471292, "method": "clip"}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-26 17:39:03.529149
ended_at: 2026-01-26 17:39:08.770878
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7876423001289368, "method": "static_fallback"}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-26 17:39:08.776062
ended_at: 2026-01-26 17:39:17.878313
output_json:
  {"clicked_at": {"x": 842, "y": 131}, "mode": "debug", "confidence": 0.5083206218683376, "method": "clip"}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_f6cdd716f062_1769200383
status: success
started_at: 2026-01-26 17:39:22.891796
ended_at: 2026-01-26 17:39:23.628404
output_json:
  {"typed": "The Superior-Reasoning-SFT-gpt-oss-120b dataset is a high-quality, open-source collection containing..."}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-26 17:39:23.633397
ended_at: 2026-01-26 17:39:26.837619
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous d\u00e9voilons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de l'art en texte nettoy\u00e9, ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes pour les pages PDF (rendus PDF). En plus de la transcription, LightOnOCR-2 est disponible sous la licence Apache 2.0, avec un ensemble de checkpoints l\u00e9gers (variants OCR-focused et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   - **Optimisation de l'OCR 1B-param\u00e8tre :** LightOnOCR-2-1B est un mod\u00e8le OCR 1B-param\u00e8tre optimis\u00e9 pour la conversion d'art de l'art en texte nettoy\u00e9, ordonn\u00e9 naturellement.\n   - **Licence Apache 2.0 :** Le mod\u00e8le est disponible sous la licence Apache 2.0, ce qui facilite son utilisation et la collaboration.\n   - **Utilisation par la communaut\u00e9 :** Les checkpoints l\u00e9gers peuvent \u00eatre utilis\u00e9s par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-26 17:39:26.846372
ended_at: 2026-01-26 17:39:36.417958
output_json:
  {"clicked_at": {"x": 33, "y": 1045}, "mode": "debug", "confidence": 0.9933956099709296, "method": "clip"}


execution_id: exec_9ebb04f1878d_1769449134
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-26 17:39:36.732036
ended_at: 2026-01-26 17:39:42.414923
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.874001681804657, "method": "static_fallback"}


execution_id: exec_58f999954f17_1769450980
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-26 18:09:40.466691
ended_at: 2026-01-26 18:09:49.689386
output_json:
  {"clicked_at": {"x": 33, "y": 1045}, "mode": "debug", "confidence": 0.9888850587466911, "method": "clip"}


execution_id: exec_58f999954f17_1769450980
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-26 18:09:50.003958
ended_at: 2026-01-26 18:09:55.523227
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7846450805664062, "method": "static_fallback"}


execution_id: exec_58f999954f17_1769450980
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-26 18:09:55.528809
ended_at: 2026-01-26 18:10:01.738738
output_json:
  {"clicked_at": {"x": 830, "y": 195}, "mode": "debug", "confidence": 0.9902026552767703, "method": "clip"}


execution_id: exec_58f999954f17_1769450980
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-26 18:10:07.430863
ended_at: 2026-01-26 18:10:10.659176
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour l'conversion d'art de l'art en texte clair, ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les figures/ images avec des tailles de formatage l\u00e9g\u00e8res. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints ouverts l\u00e9gers (variantes OCR-focused et bbox-capables, plus des checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   - LightOnOCR-2 est une nouvelle g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre optimis\u00e9 pour la conversion d'art de l'art en texte clair et naturellement ordonn\u00e9, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n   - Il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les figures/images avec des tailles de formatage l\u00e9g\u00e8res.\n   - Disponible sous la licence Apache 2.0, il est utilis\u00e9 par la communaut\u00e9 pour la fin-tuning, l'adaptation du domaine et les applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_58f999954f17_1769450980
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-26 18:10:10.669287
ended_at: 2026-01-26 18:10:18.573139
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.990872774287267, "method": "clip"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 09:30:23.326183
ended_at: 2026-01-29 09:30:29.344448
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9890293833347158, "method": "clip"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 09:30:29.670384
ended_at: 2026-01-29 09:30:35.995617
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7877270579338074, "method": "static_fallback"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 09:30:36.001038
ended_at: 2026-01-29 09:30:41.880745
output_json:
  {"clicked_at": {"x": 829, "y": 194}, "mode": "debug", "confidence": 0.9916606708645163, "method": "clip"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-29 09:30:47.566270
ended_at: 2026-01-29 09:30:53.541033
output_json:
  {"analysis": "1. **Traduction en fran\u00e7ais :**\n   Nous lan\u00e7ons LightOnOCR-2-1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR 1B-param\u00e8tre, optimis\u00e9 pour la conversion d'art de l'art en texte clair, ordonn\u00e9 naturellement sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes. En plus de la transcription, LightOnOCR-2 peut \u00e9galement extraire des bo\u00eetes de bords pour des figures/ images avec des besoins de layout l\u00e9ger. LightOnOCR-2 est disponible sous la licence Apache 2.0, avec une famille de checkpoints l\u00e9gers (variants OCR-focused et bbox-capables, plus de checkpoints de base) utilisables par la communaut\u00e9 pour la fin-tuning, l'adaptation de domaine et les applications orient\u00e9es layout.\n\n2. **R\u00e9sum\u00e9 en 3 points cl\u00e9s :**\n   1. **Optimisation de la conversion d'art de l'art en texte clair :** LightOnOCR-2 est optimis\u00e9 pour convertir des pages PDF en texte clair, ordonn\u00e9 naturellement, sans d\u00e9pendance \u00e0 des pipelines multi-\u00e9tapes.\n   2. **Extraction de bo\u00eetes de bords pour figures/images :** Le mod\u00e8le peut extraire des bo\u00eetes de bords pour des figures/images avec des besoins de layout l\u00e9ger.\n   3. **Licence Apache 2.0 et checkpoints l\u00e9gers :** LightOnOCR-2 est disponible sous la licence Apache 2.0 et avec une famille de checkpoints l\u00e9gers pour la fin-tuning, l'adaptation de domaine et les applications orient\u00e9es layout.", "variable": "resultat_analyse", "model": "qwen2.5vl:3b"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 09:30:53.550011
ended_at: 2026-01-29 09:31:01.435608
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9902942077500478, "method": "clip"}


execution_id: exec_e97b8b1de0f8_1769679023
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 09:31:01.750730
ended_at: 2026-01-29 09:31:07.506623
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8731901049613953, "method": "static_fallback"}


execution_id: exec_cb5510113300_1769693982
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 13:39:42.549654
ended_at: 2026-01-29 13:39:52.887507
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.9931637644767761, "method": "clip"}


execution_id: exec_cb5510113300_1769693982
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 13:39:53.210334
ended_at: 2026-01-29 13:39:59.111681
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7856346368789673, "method": "static_fallback"}


execution_id: exec_cb5510113300_1769693982
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 13:40:23.773761
ended_at: 2026-01-29 13:40:31.799705
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9899560628730494, "method": "clip"}


execution_id: exec_cb5510113300_1769693982
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 13:40:32.113945
ended_at: 2026-01-29 13:40:37.664771
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8738170266151428, "method": "static_fallback"}


execution_id: exec_19aa39e39586_1769694473
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 13:47:53.528332
ended_at: 2026-01-29 13:47:59.982470
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9894458097034202, "method": "clip"}


execution_id: exec_19aa39e39586_1769694473
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 13:48:00.307585
ended_at: 2026-01-29 13:48:06.808173
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7856640815734863, "method": "static_fallback"}


execution_id: exec_19aa39e39586_1769694473
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 13:48:06.813458
ended_at: 2026-01-29 13:48:13.018212
output_json:
  {"clicked_at": {"x": 828, "y": 195}, "mode": "debug", "confidence": 0.9772058906260338, "method": "clip"}


execution_id: exec_19aa39e39586_1769694473
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 13:48:27.965376
ended_at: 2026-01-29 13:48:36.170837
output_json:
  {"clicked_at": {"x": 31, "y": 1045}, "mode": "debug", "confidence": 0.9879442053281116, "method": "clip"}


execution_id: exec_19aa39e39586_1769694473
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 13:48:36.485211
ended_at: 2026-01-29 13:48:42.166095
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8731898665428162, "method": "static_fallback"}


execution_id: exec_bde78b5eefc3_1769694728
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 13:52:08.765102
ended_at: 2026-01-29 13:52:19.463604
output_json:
  {"clicked_at": {"x": 33, "y": 1046}, "mode": "debug", "confidence": 0.9907664101646504, "method": "clip"}


execution_id: exec_bde78b5eefc3_1769694728
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 13:52:19.780491
ended_at: 2026-01-29 13:52:25.682101
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7877200841903687, "method": "static_fallback"}


execution_id: exec_bde78b5eefc3_1769694728
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 13:52:46.930051
ended_at: 2026-01-29 13:52:55.137252
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9886462983146637, "method": "clip"}


execution_id: exec_d7dac10d42e2_1769694843
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 13:54:04.265501
ended_at: 2026-01-29 13:54:14.967870
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "debug", "confidence": 0.994706928730011, "method": "clip"}


execution_id: exec_d7dac10d42e2_1769694843
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 13:54:15.284230
ended_at: 2026-01-29 13:54:21.027319
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7880121469497681, "method": "static_fallback"}


execution_id: exec_d7dac10d42e2_1769694843
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 13:54:21.033082
ended_at: 2026-01-29 13:54:27.479177
output_json:
  {"clicked_at": {"x": 829, "y": 194}, "mode": "debug", "confidence": 0.9921262930613053, "method": "clip"}


execution_id: exec_bba32f32f6f6_1769695278
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 14:01:18.877085
ended_at: 2026-01-29 14:01:29.471868
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9911280433333637, "method": "clip"}


execution_id: exec_bba32f32f6f6_1769695278
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 14:01:29.805251
ended_at: 2026-01-29 14:01:35.798072
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7855830192565918, "method": "static_fallback"}


execution_id: exec_bba32f32f6f6_1769695278
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 14:01:35.803628
ended_at: 2026-01-29 14:01:42.305531
output_json:
  {"clicked_at": {"x": 829, "y": 195}, "mode": "debug", "confidence": 0.9893700808765813, "method": "clip"}


execution_id: exec_8a884ad98281_1769695551
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 14:05:51.520600
ended_at: 2026-01-29 14:06:01.812176
output_json:
  {"clicked_at": {"x": 32, "y": 1047}, "mode": "debug", "confidence": 0.9911190039908798, "method": "clip"}


execution_id: exec_8a884ad98281_1769695551
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 14:06:02.136994
ended_at: 2026-01-29 14:06:07.879184
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7876448631286621, "method": "static_fallback"}


execution_id: exec_8a884ad98281_1769695551
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 14:06:07.884371
ended_at: 2026-01-29 14:06:14.571288
output_json:
  {"clicked_at": {"x": 829, "y": 194}, "mode": "debug", "confidence": 0.9751504813278149, "method": "clip"}


execution_id: exec_3ebddec63ab4_1769695658
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 14:07:39.077082
ended_at: 2026-01-29 14:07:49.523495
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9920046811462239, "method": "clip"}


execution_id: exec_3ebddec63ab4_1769695658
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 14:07:55.566062
ended_at: 2026-01-29 14:08:02.265327
output_json:
  {"clicked_at": {"x": 828, "y": 194}, "mode": "debug", "confidence": 0.9748097461889519, "method": "clip"}


execution_id: exec_3ebddec63ab4_1769695658
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 14:08:25.498324
ended_at: 2026-01-29 14:08:31.001460
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "debug", "confidence": 0.8731904029846191, "method": "static_fallback"}


execution_id: exec_6da912c2b115_1769696214
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 14:16:55.071271
ended_at: 2026-01-29 14:17:02.029252
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9871163625248306, "method": "clip"}


execution_id: exec_6da912c2b115_1769696214
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 14:17:02.354484
ended_at: 2026-01-29 14:17:10.263580
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7855349779129028, "method": "static_fallback"}


execution_id: exec_6da912c2b115_1769696214
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 14:17:31.716395
ended_at: 2026-01-29 14:17:40.387583
output_json:
  {"clicked_at": {"x": 31, "y": 1045}, "mode": "debug", "confidence": 0.9875810799760831, "method": "clip"}


execution_id: exec_fb001dab4e80_1769718483
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 20:28:03.351321
ended_at: 2026-01-29 20:28:10.054130
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9897540303574888, "method": "clip"}


execution_id: exec_fb001dab4e80_1769718483
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 20:28:10.378843
ended_at: 2026-01-29 20:28:17.187335
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7857185006141663, "method": "static_fallback"}


execution_id: exec_fb001dab4e80_1769718483
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-29 20:28:30.970775
ended_at: 2026-01-29 20:28:41.513089
output_json:
  {"analysis": "Okay, let's tackle this request. The user provided a text in English about LightOnOCR-2.1B and wants two things: a full French translation and a 3-point summary.\n\nFirst, I need to translate the entire text into French. Let me read through the original to understand the content. The text is about a new OCR model called LightOnOCR-2.1B, which is a second-generation 1B-parameter model for converting PDF pages into clean text. It mentions it's end-to-end, optimized for document pages, outputs bounding boxes for images, and is under Apache 2.0 license. There's also an update about the paper being out with details on training recipe.\n\nI should make sure to translate technical terms correctly. For example, \"end-to-end vision-language OCR model\" becomes \"mod\u00e8le OCR vision-langue end-to-end\". Terms like \"bounding boxes\" are \"bo\u00eetes de d\u00e9limitation\" in French. The license is \"Apache 2.0 license\", which stays the same but translated as \"licence Apache 2.0\".\n\nNext, the 01/26 UPDATE part: \"The paper is now out!\" translates to \"L'article est d\u00e9sormais disponible !\". The phrase \"data/normalization pipeline\" becomes \"pipeline de donn\u00e9es/normalisation\".\n\nNow, for the summary in 3 key points. Let me identify the main points:\n\n1. Release of LightOnOCR-2.1B: second-gen, 1B parameters, end-to-end, converts PDF pages to clean text, outputs bounding boxes for images, Apache 2.0 license.\n\n2. The update: paper released with training recipe details (data pipeline, RLVR, merging).\n\n3. Checkpoints: open-weight variants for fine-tuning, domain adaptation, layout-oriented apps.\n\nWait, the original text says \"a small family of open-weight checkpoints (OCR-focused and bbox-capable variants, plus base checkpoints) that can be used by the community for fine-tuning, domain adaptation, and layout-oriented applications.\"\n\nSo the third point should mention the checkpoints and their uses.\n\nLet me structure the summary points clearly.\n\nCheck for any nuances. For example, \"naturally ordered text without relying on multi-stage pipelines\" translates to \"texte naturellement ordonn\u00e9 sans d\u00e9pendre de pipelines multi-\u00e9tapes\".\n\nAlso, \"alongside transcription, it can also output bounding boxes...\" becomes \"en plus de la transcription, il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation...\".\n\nI need to ensure the translation is accurate and natural in French. Let me check some terms:\n\n- \"end-to-end vision-language OCR model\" \u2192 \"mod\u00e8le OCR vision-langue end-to-end\"\n\n- \"PDF renderers\" \u2192 \"rendus PDF\" (but maybe \"rendus PDF\" is correct here)\n\n- \"bounding boxes for embedded figures/images\" \u2192 \"bo\u00eetes de d\u00e9limitation pour les figures/ images int\u00e9gr\u00e9es\"\n\n- \"Apache 2.0 license\" \u2192 \"licence Apache 2.0\"\n\n- \"open-weight checkpoints\" \u2192 \"checkpoints \u00e0 poids ouverts\"\n\n- \"fine-tuning, domain adaptation, and layout-oriented applications\" \u2192 \"le fine-tuning, l'adaptation de domaine et les applications orient\u00e9es mise en page\"\n\nWait, \"layout-oriented\" is \"orient\u00e9es mise en page\" in French. Maybe \"applications orient\u00e9es mise en page\" is correct.\n\nNow, translating the entire text:\n\nOverview\n\nNous lan\u00e7ons LightOnOCR-2.1B, notre deuxi\u00e8me g\u00e9n\u00e9ration de mod\u00e8le OCR \u00e0 1B de param\u00e8tres, optimis\u00e9 pour la conversion end-to-end de pages de documents (rendus PDF) en texte net, naturellement ordonn\u00e9 sans d\u00e9pendre de pipelines multi-\u00e9tapes. En plus de la transcription, il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les figures/ images int\u00e9gr\u00e9es dans les workflows n\u00e9cessitant des indices de mise en page l\u00e9gers. LightOnOCR-2.1B est publi\u00e9 sous licence Apache 2.0, accompagn\u00e9 d'une petite famille de checkpoints \u00e0 poids ouverts (variantes ax\u00e9es sur l'OCR et capables de g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation, plus les checkpoints de base) qui peuvent \u00eatre utilis\u00e9s par la communaut\u00e9 pour le fine-tuning, l'adaptation de domaine et les applications orient\u00e9es mise en page.\n\n01/26 UPDATE : L'article est d\u00e9sormais disponible ! Il inclut la recette compl\u00e8te de formation comprenant la pipeline de donn\u00e9es/normalisation, RLVR et les d\u00e9tails de fusion. Lire ici\n\nWait, \"RLVR\" is probably an acronym, so it stays as is. \"Read it here\" becomes \"Lire ici\".\n\nNow, the summary in 3 points:\n\n1. Pr\u00e9sent", "variable": "resultat_analyse", "model": "qwen3-vl:8b"}


execution_id: exec_fb001dab4e80_1769718483
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 20:28:41.518814
ended_at: 2026-01-29 20:28:49.891066
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9897168872283431, "method": "clip"}


execution_id: exec_fb001dab4e80_1769718483
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 20:29:06.448057
ended_at: 2026-01-29 20:29:07.676803
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\nOkay, let's tackle this request. The user provided a text in English..."}


execution_id: exec_5665321c9e9f_1769718627
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 20:30:27.671921
ended_at: 2026-01-29 20:30:37.204451
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9863613081138012, "method": "clip"}


execution_id: exec_5665321c9e9f_1769718627
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 20:30:37.521465
ended_at: 2026-01-29 20:30:43.478297
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7879996299743652, "method": "static_fallback"}


execution_id: exec_5665321c9e9f_1769718627
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-29 20:30:55.780806
ended_at: 2026-01-29 20:31:10.928892
output_json:
  {"analysis": "3. \u00c9crivez un texte descriptif sur le th\u00e8me \"L'importance de la diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n4. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n5. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n6. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n7. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n8. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n9. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n10. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n11. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n12. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n13. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n14. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n15. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n16. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n17. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n18. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n19. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n20. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n21. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n22. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n23. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n24. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n25. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n26. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n27. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n28. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n29. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n30. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n31. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n32. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n33. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n34. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n35. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n36. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n37. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n38. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n39. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n40. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n41. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culturelle dans la soci\u00e9t\u00e9 fran\u00e7aise\"\n42. \u00c9crivez un texte descriptif sur le th\u00e8me \"La diversit\u00e9 culture", "variable": "resultat_analyse", "model": "deepseek-ocr:latest"}


execution_id: exec_5665321c9e9f_1769718627
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 20:31:10.934387
ended_at: 2026-01-29 20:31:18.737061
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.990699222126323, "method": "clip"}


execution_id: exec_5665321c9e9f_1769718627
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 20:31:35.077918
ended_at: 2026-01-29 20:31:36.190002
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n3. \u00c9crivez un texte descriptif sur le th\u00e8me \"L'importance de la dive..."}


execution_id: exec_05bda34c6c9d_1769719201
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 20:40:02.288704
ended_at: 2026-01-29 20:40:12.014679
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9914060625841011, "method": "clip"}


execution_id: exec_05bda34c6c9d_1769719201
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 20:40:12.338695
ended_at: 2026-01-29 20:40:18.077793
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.785893440246582, "method": "static_fallback"}


execution_id: exec_05bda34c6c9d_1769719201
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-29 20:40:31.615007
ended_at: 2026-01-29 20:40:49.877337
output_json:
  {"analysis": "Okay, let's tackle this query. The user wants me to analyze the given text and perform two tasks: translate it entirely into French and create a 3-point summary.\n\nFirst, I need to understand the original text. It's an overview of a new OCR model called LightOnOCR-2-1B. The key points are that it's a second-gen 1B-parameter model for converting document pages (like PDFs) into clean text without multi-stage pipelines. It also outputs bounding boxes for figures/images. It's released under Apache 2.0 with some checkpoints. There's an update about the paper being out with training details.\n\nFor the translation, I need to make sure technical terms are correctly translated. Terms like \"end-to-end vision-language OCR model\" should be precise. \"Bounding boxes\" is \"bo\u00eetes englobantes\" in French. Also, \"Apache 2.0 license\" becomes \"licence Apache 2.0\". I should check if \"PDF renders\" is correctly translated as \"rendus PDF\" or maybe \"fichiers PDF\". The phrase \"lightweight layout cues\" might be \"indices de mise en page l\u00e9gers\".\n\nNext, the summary needs three key points. Let me identify the main ideas: 1) The release of the new OCR model with its features. 2) The license and checkpoints available. 3) The update about the paper with training details.\n\nWait, the user said \"3 points cl\u00e9s\" so each point should be concise. Let me structure them:\n\n1. Presentation of LightOnOCR-2-1B as a new OCR model with specific capabilities.\n2. Licensing and resources provided (Apache 2.0, checkpoints).\n3. Update on the paper's release with training details.\n\nI need to make sure each point is a separate key point without overlapping. Let me check the original text again to confirm.\n\nThe first paragraph talks about the model's features, the license, and the checkpoints. The second paragraph is the update about the paper. So the three points would be:\n\n1. The model's release and its main features (end-to-end, 1B parameters, converts PDF to text, bounding boxes).\n2. The licensing (Apache 2.0) and availability of checkpoints for fine-tuning.\n3. The update about the paper being published with training details.\n\nYes, that makes sense. Now, translating the text accurately. Let me go step by step.\n\nOriginal: \"We\u2019re releasing LightOnOCR-2-1B, our second-generation 1B-parameter, end-to-end vision-language OCR model optimized for state-of-the-art conversion of document pages (PDF renders) into clean, naturally ordered text without relying on multi-stage pipelines.\"\n\nTranslation: \"Nous lan\u00e7ons LightOnOCR-2-1B, notre mod\u00e8le OCR vision-langage end-to-end de deuxi\u00e8me g\u00e9n\u00e9ration avec 1 milliard de param\u00e8tres, optimis\u00e9 pour la conversion \u00e0 l'\u00e9tat de l'art de pages de documents (rendus PDF) en texte propre et naturellement ordonn\u00e9, sans d\u00e9pendre de pipelines multi-\u00e9tapes.\"\n\nCheck \"1B-parameter\" as \"1 milliard de param\u00e8tres\" which is correct. \"End-to-end\" is often kept in English in French tech contexts, but maybe \"de bout en bout\" is better. Wait, the user might prefer \"end-to-end\" as is, but in French, it's \"de bout en bout\". Let me confirm. In French tech writing, sometimes they keep \"end-to-end\" but it's better to translate. So \"mod\u00e8le OCR vision-langage de bout en bout\".\n\n\"PDF renders\" as \"rendus PDF\" is okay. \"Without relying on multi-stage pipelines\" becomes \"sans d\u00e9pendre de pipelines multi-\u00e9tapes\".\n\nNext sentence: \"Alongside transcription, it can also output bounding boxes for embedded figures/images for workflows that need lightweight layout cues.\"\n\nTranslation: \"En plus de la transcription, il peut \u00e9galement g\u00e9n\u00e9rer des bo\u00eetes englobantes pour les figures/images int\u00e9gr\u00e9es, destin\u00e9es aux workflows n\u00e9cessitant des indices de mise en page l\u00e9gers.\"\n\n\"Lightweight layout cues\" as \"indices de mise en page l\u00e9gers\" seems correct.\n\n\"LightOnOCR-2 is released under the Apache 2.0 license, together with a small family of open-weight checkpoints (OCR-focused and bbox-capable variants, plus base checkpoints) that can be used by the community for fine-tuning, domain adaptation, and layout-oriented applications.\"\n\nTranslation: \"LightOnOCR-2 est publi\u00e9 sous licence Apache 2.0, accompagn\u00e9 d'une petite famille de checkpoints \u00e0 poids ouverts (variantes ax\u00e9es sur l'OCR et capables de g\u00e9rer les bo\u00eetes englobantes, ainsi que des checkpoints de base) pouvant \u00eatre utilis\u00e9s par la communaut\u00e9 pour l'", "variable": "resultat_analyse", "model": "qwen3-vl:235b-cloud"}


execution_id: exec_05bda34c6c9d_1769719201
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 20:40:49.883069
ended_at: 2026-01-29 20:40:57.708113
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9875750645417444, "method": "clip"}


execution_id: exec_05bda34c6c9d_1769719201
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 20:41:13.981396
ended_at: 2026-01-29 20:41:15.220400
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\nOkay, let's tackle this query. The user wants me to analyze the give..."}


execution_id: exec_a5c2341fecff_1769719718
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 20:48:38.998978
ended_at: 2026-01-29 20:48:48.476885
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9863443080247399, "method": "clip"}


execution_id: exec_a5c2341fecff_1769719718
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 20:48:48.801485
ended_at: 2026-01-29 20:48:54.499524
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7876451015472412, "method": "static_fallback"}


execution_id: exec_a5c2341fecff_1769719718
step_id: step_f6cdd716f062_1769200383
status: success
started_at: 2026-01-29 20:49:06.087651
ended_at: 2026-01-29 20:49:06.800794
output_json:
  {"typed": "Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on ..."}


execution_id: exec_a5c2341fecff_1769719718
step_id: step_0c7fba2458fe_1769201174
status: success
started_at: 2026-01-29 20:49:06.806034
ended_at: 2026-01-29 20:49:17.861582
output_json:
  {"analysis": "Okay, let's tackle this request. The user provided a text in English about LightOnOCR-2.1B and wants two things: a full French translation and a 3-point summary.\n\nFirst, I need to translate the entire text into French. Let me read through the original to understand the content. The main points are the release of LightOnOCR-2.1B, its features (1B-parameter, end-to-end vision-language OCR, converting PDF pages to clean text, bounding boxes for images), license (Apache 2.0), and the update about the paper.\n\nI should make sure technical terms are correctly translated. For example, \"end-to-end vision-language OCR model\" becomes \"mod\u00e8le OCR vision-langue end-to-end\". Also, check terms like \"bounding boxes\" which is \"bo\u00eetes de d\u00e9limitation\" in French.\n\nNext, the summary in three key points. The user wants concise points. Let me identify the main aspects:\n\n1. Release of LightOnOCR-2.1B with its specifications (1B parameters, end-to-end, PDF to text conversion, bounding boxes for images).\n2. Licensing and availability of checkpoints for fine-tuning, domain adaptation, etc.\n3. The 01/26 update about the paper including training recipe details.\n\nWait, the original text mentions \"01/26 UPDATE: The paper is now out!\" so the third point should be about the paper release with details on data pipeline, LVRV, merging.\n\nLet me structure the summary points:\n\n1. Pr\u00e9sentation du mod\u00e8le LightOnOCR-2.1B : 1B param\u00e8tres, conversion PDF vers texte net, bo\u00eetes de d\u00e9limitation pour images.\n2. Licence Apache 2.0 et checkpoints ouverts pour adaptation et applications.\n3. Mise \u00e0 jour du 01/26 : publication de l'article avec d\u00e9tails sur la recette de formation.\n\nWait, the user said \"3 points cl\u00e9s\", so each point should be a key takeaway. Let me check the original text again.\n\nOriginal text:\n\n- Overview: Release of LightOnOCR-2.1B, second-gen 1B-parameter, end-to-end OCR for PDF to clean text, bounding boxes for images. Released under Apache 2.0, with checkpoints for fine-tuning, etc.\n\n- 01/26 UPDATE: Paper out, includes training recipe, data pipeline, LVRV, merging details.\n\nSo the three key points would be:\n\n1. Pr\u00e9sentation du mod\u00e8le LightOnOCR-2.1B : mod\u00e8le OCR vision-langue end-to-end de 1B param\u00e8tres, optimis\u00e9 pour convertir les pages de documents PDF en texte net et g\u00e9n\u00e9rer des bo\u00eetes de d\u00e9limitation pour les images int\u00e9gr\u00e9es.\n\n2. Disponibilit\u00e9 sous licence Apache 2.0 avec des checkpoints ouverts (OCR et bo\u00eetes de d\u00e9limitation) pour la finetuning, adaptation de domaine et applications orient\u00e9es mise en page.\n\n3. Mise \u00e0 jour du 01/26 : publication de l'article avec la recette compl\u00e8te de formation, pipeline de donn\u00e9es, d\u00e9tails sur LVRV et fusion.\n\nWait, the user wants a summary in 3 points. Let me make sure each point is distinct and captures the main ideas.\n\nFirst point: Model details (1B parameters, purpose, features).\n\nSecond point: Licensing and checkpoints.\n\nThird point: The update about the paper.\n\nYes, that makes sense.\n\nNow, translating the text into French. Let me check some terms:\n\n\"end-to-end vision-language OCR model\" \u2192 \"mod\u00e8le OCR vision-langue end-to-end\"\n\n\"PDF renderers\" \u2192 \"rendus PDF\"\n\n\"naturally ordered text\" \u2192 \"texte naturellement ordonn\u00e9\"\n\n\"bounding boxes for embedded figures/images\" \u2192 \"bo\u00eetes de d\u00e9limitation pour les figures/images int\u00e9gr\u00e9es\"\n\n\"Apache 2.0 license\" \u2192 \"licence Apache 2.0\"\n\n\"fine-tuning, domain adaptation, and layout-oriented applications\" \u2192 \"la finetuning, l'adaptation de domaine et les applications orient\u00e9es mise en page\"\n\n\"01/26 UPDATE\" \u2192 \"MISE \u00c0 JOUR 01/26\"\n\n\"training recipe\" \u2192 \"recette de formation\"\n\n\"data normalization pipeline\" \u2192 \"pipeline de normalisation des donn\u00e9es\"\n\n\"LVRV\" \u2192 \"LVRV\" (probably an acronym, so keep as is)\n\n\"merging details\" \u2192 \"d\u00e9tails sur la fusion\"\n\nLet me translate the entire text step by step.\n\nOriginal:\n\nOverview\n\nWe\u2019re releasing LightOnOCR-2.1B, our second-generation 1B-parameter, end-to-end vision-language OCR model optimized for state-of-the-art conversion of document pages", "variable": "resultat_analyse", "model": "qwen3-vl:8b"}


execution_id: exec_a5c2341fecff_1769719718
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 20:49:17.867167
ended_at: 2026-01-29 20:49:26.087888
output_json:
  {"clicked_at": {"x": 31, "y": 1047}, "mode": "debug", "confidence": 0.9822034454820356, "method": "clip"}


execution_id: exec_f8470ae36d3a_1769723664
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 21:54:24.372196
ended_at: 2026-01-29 21:54:30.845765
output_json:
  {"clicked_at": {"x": 32, "y": 1043}, "mode": "debug", "confidence": 0.9874683654879413, "method": "clip"}


execution_id: exec_f8470ae36d3a_1769723664
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 21:54:31.161504
ended_at: 2026-01-29 21:54:38.320665
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7854077219963074, "method": "static_fallback"}


execution_id: exec_f8470ae36d3a_1769723664
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 21:54:50.413063
ended_at: 2026-01-29 21:55:48.609825
output_json:
  {"analysis": "**Analyse et correction du texte original**\n\n> **Kimi\u202fK2.5** est un mod\u00e8le agentique multimodal natif open\u2011source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ **15\u202ftrillions de tokens visuels et textuels** combin\u00e9s, en s\u2019appuyant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes \u00ab\u202finstantan\u00e9\u202f\u00bb et \u00ab\u202fpens\u00e9e\u202f\u00bb, ainsi que des paradigmes conversationnels et agentiques.\n\n> **Caract\u00e9ristiques cl\u00e9s**  \n> \u2022 **Multimodalit\u00e9 native**\u202f: pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle en connaissance visuelle, raisonnement inter\u2011modal et utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n> \u2022 **Codage visuel**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, workflows vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n> \u2022 **Mouvement d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cialis\u00e9s par domaine.\n\n---\n\n## Traduction en fran\u00e7ais\n\n**Kimi\u202fK2.5** est un mod\u00e8le agentique multimodal natif open\u2011source, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ **15\u202ftrillions de tokens visuels et textuels** combin\u00e9s, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes \u00ab\u202finstantan\u00e9\u202f\u00bb et \u00ab\u202fpens\u00e9e\u202f\u00bb, ainsi que des paradigmes conversationnels et agentiques.\n\n### Caract\u00e9ristiques principales\n- **Multimodalit\u00e9 native**\u202f: pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle en connaissance visuelle, raisonnement inter\u2011modal et utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage visuel**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, workflows vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Essaim d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cialis\u00e9s par domaine.\n\n---\n\n## Traduction en chinois\n\n**Kimi\u202fK2.5** \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15 \u4e07\u4ebf\u4e2a\u89c6\u89c9\u4e0e\u6587\u672c\u6df7\u5408 token \u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u4e86\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n### \u5173\u952e\u7279\u6027\n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9-\u8bed\u8a00 token \u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9886\u57df\u7279\u5b9a\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_f8470ae36d3a_1769723664
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 21:55:48.615623
ended_at: 2026-01-29 21:55:56.699731
output_json:
  {"clicked_at": {"x": 31, "y": 1046}, "mode": "debug", "confidence": 0.9853567408685221, "method": "clip"}


execution_id: exec_f8470ae36d3a_1769723664
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 21:56:12.980493
ended_at: 2026-01-29 21:56:13.856588
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse et correction du texte original**\n\n> **Kimi\u202fK2.5** est un ..."}


execution_id: exec_b0e77c790318_1769723859
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 21:57:39.587662
ended_at: 2026-01-29 21:57:49.799582
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9905374531346313, "method": "clip"}


execution_id: exec_b0e77c790318_1769723859
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 21:58:08.110847
ended_at: 2026-01-29 21:58:16.530775
output_json:
  {"analysis": "**Analyse du texte (en fran\u00e7ais)**  \n\nLe texte pr\u00e9sente **Kimi\u202fK2.5**, un mod\u00e8le d\u2019intelligence artificielle multimodal \u00ab\u202fopen\u2011source\u202f\u00bb qui combine vision et langage. Il a \u00e9t\u00e9 entra\u00een\u00e9 de fa\u00e7on continue sur environ **15\u202ftrillions** de tokens m\u00ealant images et texte, en partant du mod\u00e8le de base **Kimi\u2011K2\u2011Base**.  \n\nLes points forts soulign\u00e9s sont\u202f:  \n\n1. **Multimodalit\u00e9 native** \u2013 le mod\u00e8le a \u00e9t\u00e9 pr\u00e9\u2011entra\u00een\u00e9 sur des paires vision\u2011texte, ce qui lui permet d\u2019exceller dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils \u00ab\u202fagentic\u202f\u00bb (c\u2019est\u2011\u00e0\u2011dire capables d\u2019agir de fa\u00e7on autonome) \u00e0 partir d\u2019entr\u00e9es visuelles.  \n2. **Codage \u00e0 partir de la vision** \u2013 il peut g\u00e9n\u00e9rer du code \u00e0 partir de sp\u00e9cifications visuelles (maquettes d\u2019interface, flux vid\u00e9o, etc.) et orchestrer de fa\u00e7on autonome les outils n\u00e9cessaires au traitement des donn\u00e9es visuelles.  \n3. **Essaim d\u2019agents** \u2013 au lieu de se limiter \u00e0 un seul agent, K2.5 adopte une architecture \u00ab\u202fswarm\u202f\u00bb\u202f: il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e9lisables, chaque sous\u2011t\u00e2che \u00e9tant prise en charge par un agent sp\u00e9cialis\u00e9 cr\u00e9\u00e9 dynamiquement.  \n\nEn r\u00e9sum\u00e9, Kimi\u202fK2.5 se veut un mod\u00e8le polyvalent capable de comprendre et de raisonner sur du contenu visuel et textuel, de produire du code \u00e0 partir d\u2019images et de g\u00e9rer des t\u00e2ches complexes gr\u00e2ce \u00e0 une coop\u00e9ration d\u2019agents autonomes.\n\n---\n\n### Version anglaise corrig\u00e9e et clarifi\u00e9e  \n\n**Kimi\u202fK2.5** is an open\u2011source, native multimodal agentic model built by continual pre\u2011training on roughly **15\u202ftrillion** mixed visual\u2011and\u2011text tokens, based on **Kimi\u2011K2\u2011Base**. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering both instant\u2011response and deliberative (thinking) modes, as well as conversational and agentic interaction paradigms.\n\n**Key Features**  \n\n- **Native Multimodality** \u2013 Pre\u2011trained on vision\u2011language token pairs, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision** \u2013 K2.5 can generate code from visual specifications (UI designs, video workflows) and autonomously orchestrate tools for visual\u2011data processing.  \n- **Agent Swarm** \u2013 K2.5 moves beyond single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks that are handled by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n### Traduction fran\u00e7aise  \n\n**Kimi\u202fK2.5** est un mod\u00e8le agentique multimodal natif, open\u2011source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ **15\u202ftrillions** de tokens mixtes (visuels et textuels), \u00e0 partir de **Kimi\u2011K2\u2011Base**. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, proposant \u00e0 la fois des modes de r\u00e9ponse instantan\u00e9e et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s principales**  \n\n- **Multimodalit\u00e9 native** \u2013 Pr\u00e9\u2011entra\u00een\u00e9 sur des paires de tokens vision\u2011texte, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans des entr\u00e9es visuelles.  \n- **Codage \u00e0 partir de la vision** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (maquettes d\u2019interface, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils n\u00e9cessaires au traitement des donn\u00e9es visuelles.  \n- **Essaim d\u2019agents** \u2013 K2.5 passe du simple agrandissement d\u2019un agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9, semblable \u00e0 un essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents sp\u00e9cialis\u00e9s cr\u00e9\u00e9s dynamiquement.\n\n---\n\n### \u4e2d\u6587\u7ffb\u8bd1\uff08\u7b80\u4f53\uff09  \n\n**Kimi\u202fK2.5** \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u539f\u751f\u591a\u6a21\u6001\u667a\u80fd\u4f53\u6a21\u578b\uff0c\u57fa\u4e8e **Kimi\u2011K2\u2011Base**\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 **15 \u4e07\u4ebf** \u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u7684 token \u6784\u5efa\u800c\u6210\u3002\u5b83\u80fd\u591f\u65e0\u7f1d\u878d\u5408\u89c6\u89c9\u548c\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u9ad8\u7ea7\u667a\u80fd\u4f53\u80fd\u529b\uff0c\u63d0\u4f9b\u5373\u65f6\u54cd\u5e94\u6a21\u5f0f\u548c\u601d\u8003\uff08\u63a8\u7406\uff09\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u667a\u80fd\u4f53\u5f0f\u7684\u4ea4\u4e92\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**  \n\n- **\u539f\u751f\u591a\u6a21\u6001** \u2013 \u901a\u8fc7\u5bf9\u89c6\u89c9\u2011\u8bed\u8a00 token \u5bf9\u8fdb\u884c\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u667a\u80fd\u4f53\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u9a71\u52a8\u7684\u4ee3\u7801\u751f\u6210** \u2013 K2.5 \u80fd\u591f\u6839\u636e\u89c6\u89c9\u89c4\u683c\uff08\u5982 UI \u8bbe\u8ba1\u7a3f\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u7528\u4e8e\u89c6\u89c9\u6570\u636e\u5904\u7406\u7684\u5de5\u5177\u3002  \n- **\u667a\u80fd\u4f53\u7fa4\u4f53\uff08Agent Swarm\uff09** \u2013 K2.5 \u8d85\u8d8a\u5355\u4e00\u667a\u80fd\u4f53\u7684\u89c4\u6a21\u5316\uff0c\u91c7\u7528\u81ea\u6211\u5bfc\u5411\u3001\u534f\u540c\u7684\u7fa4\u4f53\u6267\u884c\u673a\u5236\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u53ef\u5e76\u884c\u6267\u884c\u7684\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9762\u5411\u7279\u5b9a\u9886\u57df\u7684\u667a\u80fd\u4f53\u8d1f\u8d23\u5b8c\u6210\u3002", "variable": "resultat_analyse", "model": "gpt-oss:120b-cloud", "mode": "text"}


execution_id: exec_b0e77c790318_1769723859
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 21:58:40.994301
ended_at: 2026-01-29 21:58:42.173844
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte (en fran\u00e7ais)**  \n\nLe texte pr\u00e9sente **Kimi\u202fK2.5*..."}


execution_id: exec_a3cbf1686b5d_1769724344
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 22:05:44.941626
ended_at: 2026-01-29 22:05:51.659330
output_json:
  {"clicked_at": {"x": 31, "y": 1043}, "mode": "debug", "confidence": 0.9857983183877114, "method": "clip"}


execution_id: exec_a3cbf1686b5d_1769724344
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 22:05:51.984808
ended_at: 2026-01-29 22:05:59.134183
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7856348752975464, "method": "static_fallback"}


execution_id: exec_a3cbf1686b5d_1769724344
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 22:06:11.505666
ended_at: 2026-01-29 22:06:31.631918
output_json:
  {"analysis": "**Analyse du texte (en fran\u00e7ais)**  \nLe texte d\u00e9crit **Kimi\u202fK2.5**, un mod\u00e8le d\u2019agent\u202fmultimodal open\u2011source qui a \u00e9t\u00e9 continuellement pr\u00e9\u2011entra\u00een\u00e9 sur environ **15\u202fbillions** (en fait 15\u202ftrillions) de tokens combinant vision et texte, en partant de la version de base **Kimi\u2011K2\u2011Base**.  \n\nPoints forts\u202f:  \n1. **Multimodalit\u00e9 native** \u2013 le mod\u00e8le a d\u00e9j\u00e0 vu des paires image/texte, ce qui lui permet de raisonner entre les deux modalit\u00e9s et d\u2019utiliser des outils en se basant sur des entr\u00e9es visuelles.  \n2. **Codage \u00e0 partir de la vision** \u2013 il peut g\u00e9n\u00e9rer du code \u00e0 partir de sp\u00e9cifications visuelles (maquettes d\u2019interface, flux vid\u00e9o) et piloter de fa\u00e7on autonome les outils n\u00e9cessaires au traitement de ces donn\u00e9es.  \n3. **Essaim d\u2019agents** \u2013 au lieu de n\u2019\u00eatre qu\u2019un seul agent qui s\u2019agrandit, K2.5 fonctionne comme un petit essaim\u202f: il d\u00e9coupe les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e9lis\u00e9es, chaque sous\u2011t\u00e2che \u00e9tant prise en charge par un agent sp\u00e9cialis\u00e9 cr\u00e9\u00e9 \u00e0 la vol\u00e9e.  \n\nLe texte est globalement correct, mais on peut clarifier certaines formulations et corriger de petites fautes de ponctuation.\n\n---\n\n### Version corrig\u00e9e et rendue parfaitement compr\u00e9hensible (en anglais)\n\n**Kimi\u202fK2.5** is an open\u2011source, native multimodal agentic model that has been continuously pre\u2011trained on approximately **15\u202ftrillion** mixed visual\u2011and\u2011text tokens, building on top of **Kimi\u2011K2\u2011Base**. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering both *instant* and *thinking* modes, as well as conversational and agentic interaction paradigms.\n\n**Key Features**\n\n- **Native Multimodality** \u2013 Pre\u2011trained on vision\u2011language token pairs, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision** \u2013 K2.5 can generate code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrate the tools required for visual data processing.  \n- **Agent Swarm** \u2013 K2.5 moves beyond single\u2011agent scaling to a self\u2011directed, coordinated, swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks that are handled by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n### Traduction fran\u00e7aise\n\n**Kimi\u202fK2.5** est un mod\u00e8le d\u2019agent\u202fmultimodal natif, open\u2011source, entra\u00een\u00e9 de fa\u00e7on continue sur environ **15\u202ftrillions** de tokens mixtes (visuels et textuels), en s\u2019appuyant sur **Kimi\u2011K2\u2011Base**. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s d\u2019agent avanc\u00e9es, proposant \u00e0 la fois des modes *instantan\u00e9* et *r\u00e9flexion*, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s principales**\n\n- **Multimodalit\u00e9 native** \u2013 Pr\u00e9\u2011entra\u00een\u00e9 sur des paires image\u2011texte, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques fond\u00e9s sur des entr\u00e9es visuelles.  \n- **Codage \u00e0 partir de la vision** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (maquettes d\u2019interface, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils n\u00e9cessaires au traitement des donn\u00e9es visuelles.  \n- **Essaim d\u2019agents** \u2013 K2.5 passe du simple agrandissement d\u2019un agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution auto\u2011dirig\u00e9 et coordonn\u00e9, semblable \u00e0 un essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents sp\u00e9cialis\u00e9s, cr\u00e9\u00e9s dynamiquement selon le domaine.\n\n---\n\n### \u4e2d\u6587\u7ffb\u8bd1\n\n**Kimi\u202fK2.5** \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u539f\u751f\u591a\u6a21\u6001\u667a\u80fd\u4f53\u6a21\u578b\uff0c\u5728 **Kimi\u2011K2\u2011Base** \u7684\u57fa\u7840\u4e0a\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 **15\u202f\u4e07\u4ebf** \u6761\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u7684 token \u6784\u5efa\u800c\u6210\u3002\u5b83\u80fd\u591f\u65e0\u7f1d\u878d\u5408\u89c6\u89c9\u548c\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u667a\u80fd\u4f53\u80fd\u529b\uff0c\u63d0\u4f9b\u5373\u65f6\u6a21\u5f0f\u548c\u601d\u8003\u6a21\u5f0f\u4e24\u79cd\u4ea4\u4e92\u65b9\u5f0f\uff0c\u5e76\u652f\u6301\u5bf9\u8bdd\u5f0f\u548c\u667a\u80fd\u4f53\u5f0f\u7684\u4f7f\u7528\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**\n\n- **\u539f\u751f\u591a\u6a21\u6001** \u2013 \u901a\u8fc7\u5728\u89c6\u89c9\u2011\u8bed\u8a00 token \u5bf9\u4e0a\u8fdb\u884c\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u667a\u80fd\u4f53\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u9a71\u52a8\u7684\u7f16\u7801** \u2013 K2.5 \u80fd\u591f\u6839\u636e\u89c6\u89c9\u89c4\u683c\uff08\u5982 UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u7528\u4e8e\u89c6\u89c9\u6570\u636e\u5904\u7406\u7684\u5404\u79cd\u5de5\u5177\u3002  \n- **\u667a\u80fd\u4f53\u7fa4 swarm** \u2013 K2.5 \u8d85\u8d8a\u4e86\u5355\u4e00\u667a\u80fd\u4f53\u7684\u89c4\u6a21\u5316\uff0c\u91c7\u7528\u81ea\u6211\u5bfc\u5411\u3001\u534f\u540c\u7684\u7fa4\u4f53\u6267\u884c\u673a\u5236\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u5206\u4e3a\u5e76\u884c\u7684\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u521b\u5efa\u7684\u3001\u9762\u5411\u7279\u5b9a\u9886\u57df\u7684\u667a\u80fd\u4f53\u5e76\u884c\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:120b-cloud", "mode": "text"}


execution_id: exec_a3cbf1686b5d_1769724344
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 22:06:55.583939
ended_at: 2026-01-29 22:06:56.724066
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte (en fran\u00e7ais)**  \nLe texte d\u00e9crit **Kimi\u202fK2.5**, ..."}


execution_id: exec_c04def4b9e53_1769725354
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 22:22:46.072361
ended_at: 2026-01-29 22:22:51.871262
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "debug", "confidence": 0.7877274751663208, "method": "static_fallback"}


execution_id: exec_c04def4b9e53_1769725354
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 22:23:04.172397
ended_at: 2026-01-29 22:23:47.573893
output_json:
  {"analysis": "**Version corrig\u00e9e (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pre\u2011trained on roughly 15\u202ftrillion mixed vision\u2011and\u2011text tokens, building on the Kimi\u2011K2\u2011Base foundation. It seamlessly integrates visual and linguistic understanding with advanced agentic capabilities, offering instant\u2011response and \u201cthinking\u201d modes, as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native Multimodality**: Pre\u2011trained on vision\u2011language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision**: K2.5 can generate code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrate tools for visual data processing.  \n- **Agent Swarm**: K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks that are executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif open\u2011source, pr\u00e9\u2011entra\u00een\u00e9 de fa\u00e7on continue sur environ 15\u202fmilliards de tokens mixtes visuels et textuels, reposant sur la base Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, proposant des modes de r\u00e9ponse instantan\u00e9e et de \u00ab\u202fpens\u00e9e\u202f\u00bb, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s cl\u00e9s**  \n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage visuel**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de mani\u00e8re autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Masse d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 en mode essaim auto\u2011dirig\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s, sp\u00e9cifiques \u00e0 chaque domaine.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u57fa\u7840\u4e0a\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u5927\u7ea6 15 \u4e07\u4ebf\u4e2a\u89c6\u89c9\u4e0e\u6587\u672c\u6df7\u5408\u6807\u8bb0\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u63d0\u4f9b\u5373\u65f6\u54cd\u5e94\u548c\u201c\u601d\u8003\u201d\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08\u5982 UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u6307\u5bfc\u3001\u534f\u8c03\u4e00\u81f4\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u7528\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_c04def4b9e53_1769725354
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 22:23:47.594441
ended_at: 2026-01-29 22:23:55.494610
output_json:
  {"clicked_at": {"x": 33, "y": 1046}, "mode": "debug", "confidence": 0.9921729919316226, "method": "clip"}


execution_id: exec_c04def4b9e53_1769725354
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 22:24:11.977191
ended_at: 2026-01-29 22:24:12.827442
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Version corrig\u00e9e (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native..."}


execution_id: exec_2b244b195e74_1769726089
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 22:34:49.782293
ended_at: 2026-01-29 22:34:56.374954
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9873861279385269, "method": "clip"}


execution_id: exec_ac3f371ca73c_1769726962
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 22:49:29.308025
ended_at: 2026-01-29 22:51:22.621697
output_json:
  {"analysis": "**Analyse du texte**  \nLe passage est r\u00e9dig\u00e9 en anglais technique et est globalement coh\u00e9rent. Quelques points d\u2019am\u00e9lioration\u202f:  \n- Uniformiser la ponctuation et la mise en forme (par ex. ajouter des virgules apr\u00e8s les compl\u00e9ments de temps).  \n- Remplacer le terme \u00ab\u202fagentic\u202f\u00bb par \u00ab\u202fagent\u2011based\u202f\u00bb ou garder \u00ab\u202fagentic\u202f\u00bb si le public cible conna\u00eet ce jargon.  \n- Clarifier la phrase \u00ab\u202finstant and thinking modes\u202f\u00bb en indiquant qu\u2019il s\u2019agit de deux modes d\u2019op\u00e9ration.  \n- Mettre les titres de sections en majuscules ou en gras pour une meilleure lisibilit\u00e9.  \n- Utiliser \u00ab\u202fKimi\u2011K2\u2011Base\u202f\u00bb pour rester coh\u00e9rent avec le nom du mod\u00e8le de base.  \n\n**Texte corrig\u00e9 (anglais)**  \n```\nKimi K2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15 trillion mixed visual and text tokens, based on Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, and both conversational and agentic paradigms.\n\nKey Features\n- Native Multimodality: Pre\u2011trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.\n- Coding with Vision: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.\n- Agent Swarm: K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n```\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif open\u2011source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de jetons visuels et textuels, bas\u00e9 sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans couture la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9 et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**  \n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des jetons vision\u2011langage, K2.5 excelle en connaissance visuelle, raisonnement cross\u2011modal et utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec Vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement des donn\u00e9es visuelles.  \n- **Essaim d\u2019agents**\u202f: K2.5 passe d\u2019une mont\u00e9e en charge d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.\n\n**Traduction en chinois**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea615\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u548c\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u89c6\u89c9\u548c\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u6a21\u5f0f\u548c\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u548c\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u6838\u5fc3\u7279\u6027**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9-\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u8fc7\u6e21\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u5206\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u7279\u5b9a\u9886\u57df\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_ac3f371ca73c_1769726962
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 22:51:33.365177
ended_at: 2026-01-29 22:51:35.153239
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte**  \nLe passage est r\u00e9dig\u00e9 en anglais technique et..."}


execution_id: exec_3a18c108114a_1769727520
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 22:58:40.788803
ended_at: 2026-01-29 22:58:47.110969
output_json:
  {"clicked_at": {"x": 31, "y": 1043}, "mode": "intelligent", "confidence": 0.9838772608956932, "method": "clip"}


execution_id: exec_3a18c108114a_1769727520
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 22:58:47.541039
ended_at: 2026-01-29 22:58:54.351178
output_json:
  {"clicked_at": {"x": 994, "y": 199}, "mode": "intelligent", "confidence": 0.7874513268470764, "method": "static_fallback"}


execution_id: exec_3a18c108114a_1769727520
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 22:58:54.366262
ended_at: 2026-01-29 22:59:00.739027
output_json:
  {"clicked_at": {"x": 829, "y": 194}, "mode": "intelligent", "confidence": 0.9751504813278149, "method": "clip"}


execution_id: exec_3a18c108114a_1769727520
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 22:59:06.677877
ended_at: 2026-01-29 22:59:49.922858
output_json:
  {"analysis": "**Analyse et version corrig\u00e9e (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed visual and text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant\u2011response and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native Multimodality**: Pre\u2011trained on vision\u2011language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm**: K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source et natif, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de jetons mixtes visuels et textuels, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes de r\u00e9ponse instantan\u00e9e et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s cl\u00e9s**  \n- **Multimodalit\u00e9 native** : Pr\u00e9\u2011entra\u00een\u00e9 sur des jetons vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement intermodal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec vision** : K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils pour le traitement de donn\u00e9es visuelles.  \n- **Essaim d\u2019agents** : K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et autonome en essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents sp\u00e9cifiques au domaine instanci\u00e9s dynamiquement.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u3001\u539f\u751f\u7684\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u54cd\u5e94\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u5173\u952e\u7279\u6027**  \n- **\u539f\u751f\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9-\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u5206\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u7279\u5b9a\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_3a18c108114a_1769727520
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 22:59:49.937180
ended_at: 2026-01-29 22:59:57.570352
output_json:
  {"clicked_at": {"x": 32, "y": 1046}, "mode": "intelligent", "confidence": 0.9883453399777745, "method": "clip"}


execution_id: exec_3a18c108114a_1769727520
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 22:59:57.986753
ended_at: 2026-01-29 23:00:04.409662
output_json:
  {"clicked_at": {"x": 992, "y": 191}, "mode": "intelligent", "confidence": 0.8738128542900085, "method": "static_fallback"}


execution_id: exec_615225073e75_1769728093
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 23:08:20.967840
ended_at: 2026-01-29 23:08:25.548432
output_json:
  {"clicked_at": {"x": 993, "y": 194}, "mode": "debug", "confidence": 0.9591722836373903, "method": "clip"}


execution_id: exec_615225073e75_1769728093
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-29 23:08:37.671961
ended_at: 2026-01-29 23:09:20.787629
output_json:
  {"analysis": "**Texte corrig\u00e9 (anglais)\u202f:**\n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pre\u2011trained on approximately 15\u202ftrillion mixed vision\u2011and\u2011text tokens, building on Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, including instant\u2011response and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native multimodality** \u2013 Trained on vision\u2013language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with vision** \u2013 K2.5 can generate code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrate tools for visual data processing.  \n- **Agent swarm** \u2013 K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks that are executed by dynamically instantiated, domain\u2011specific agents.  \n\n---\n\n**Traduction fran\u00e7aise\u202f:**\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source et natif, entra\u00een\u00e9 de fa\u00e7on continue sur environ 15\u202fmilliards de tokens mixtes visuels et textuels, en s\u2019appuyant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de mani\u00e8re fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, incluant des modes de r\u00e9ponse instantan\u00e9e et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques principales**\n\n- **Multimodalit\u00e9 native** \u2013 Entra\u00een\u00e9 sur des tokens visuel\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques fond\u00e9s sur des entr\u00e9es visuelles.  \n- **Codage avec vision** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conception d\u2019IU, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils pour le traitement de donn\u00e9es visuelles.  \n- **Mouvement d\u2019escouade d\u2019agents** \u2013 K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et auto\u2011dirig\u00e9 en mode escouade. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s, sp\u00e9cifiques \u00e0 un domaine.  \n\n---\n\n**\u4e2d\u6587\u7ffb\u8bd1\uff1a**\n\nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u7684\u57fa\u7840\u4e0a\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u6784\u5efa\u800c\u6210\u3002\u5b83\u65e0\u7f1d\u6574\u5408\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u529f\u80fd\uff0c\u5305\u62ec\u5373\u65f6\u54cd\u5e94\u548c\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**\n\n- **\u672c\u5730\u591a\u6a21\u6001** \u2013 \u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u8fdb\u884c\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801** \u2013 K2.5 \u80fd\u591f\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08\u5982 UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53** \u2013 K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u6307\u5bfc\u3001\u534f\u8c03\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9886\u57df\u7279\u5b9a\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_615225073e75_1769728093
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-29 23:09:20.809093
ended_at: 2026-01-29 23:09:28.601629
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9904204706555142, "method": "clip"}


execution_id: exec_615225073e75_1769728093
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-29 23:09:29.416898
ended_at: 2026-01-29 23:09:34.121263
output_json:
  {"clicked_at": {"x": 994, "y": 196}, "mode": "debug", "confidence": 0.9673325898205558, "method": "clip"}


execution_id: exec_615225073e75_1769728093
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-29 23:09:44.134833
ended_at: 2026-01-29 23:09:44.938766
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Texte corrig\u00e9 (anglais)\u202f:**\n\nKimi\u202fK2.5 is an open\u2011source, native m..."}


execution_id: exec_71226dc73cb6_1769730177
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-29 23:42:57.717578
ended_at: 2026-01-29 23:43:07.854562
output_json:
  {"clicked_at": {"x": 31, "y": 1043}, "mode": "debug", "confidence": 0.9850609750629864, "method": "clip"}


execution_id: exec_71226dc73cb6_1769730177
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-29 23:43:08.703094
ended_at: 2026-01-29 23:43:15.552377
output_json:
  {"clicked_at": {"x": 993, "y": 193}, "mode": "debug", "confidence": 0.9580776005402112, "method": "clip"}


execution_id: exec_71226dc73cb6_1769730177
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-29 23:43:15.569316
ended_at: 2026-01-29 23:43:24.979110
output_json:
  {"clicked_at": {"x": 830, "y": 194}, "mode": "debug", "confidence": 0.9966341328238519, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-30 00:18:33.883173
ended_at: 2026-01-30 00:18:43.848153
output_json:
  {"clicked_at": {"x": 31, "y": 1044}, "mode": "debug", "confidence": 0.9884947813588505, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-30 00:18:44.672559
ended_at: 2026-01-30 00:18:49.374309
output_json:
  {"clicked_at": {"x": 994, "y": 195}, "mode": "debug", "confidence": 0.9668295592332471, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-30 00:18:49.379293
ended_at: 2026-01-30 00:18:57.303231
output_json:
  {"clicked_at": {"x": 807, "y": 159}, "mode": "debug", "confidence": 0.5781167572360525, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-30 00:19:03.326545
ended_at: 2026-01-30 00:20:10.692680
output_json:
  {"analysis": "**Analyse et version corrig\u00e9e en anglais**\n\nKimi\u2011K2.5 is an open\u2011source, native multimodal agentic model that has been continually pre\u2011trained on roughly 15\u202ftrillion mixed vision\u2011and\u2011text tokens, building upon the Kimi\u2011K2\u2011Base foundation. It seamlessly fuses vision and language understanding with advanced agentic capabilities, offering both instantaneous and deliberative modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native Multimodality**: Pre\u2011trained on vision\u2011language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision**: K2.5 generates code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm**: K2.5 evolves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**\n\nKimi\u2011K2.5 est un mod\u00e8le d\u2019agentic multimodal natif et open\u2011source, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de tokens mixtes visuels et textuels, reposant sur la base Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentic avanc\u00e9es, offrant des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentic.\n\n**Caract\u00e9ristiques cl\u00e9s**\n\n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle en connaissances visuelles, raisonnement cross\u2011modal et utilisation d\u2019outils agentic ancr\u00e9s dans des entr\u00e9es visuelles.  \n- **Codage avec la vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conception d\u2019interface, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils de traitement de donn\u00e9es visuelles.  \n- **Arm\u00e9e d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cialis\u00e9s dans un domaine.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**\n\nKimi\u2011K2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u8fdb\u884c\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15 \u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u4e0e\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u65e0\u7f1d\u878d\u5408\uff0c\u63d0\u4f9b\u5373\u65f6\u4e0e\u6df1\u601d\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**\n\n- **\u539f\u751f\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u4ece\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u540c\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u5c5e\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-30 00:20:10.698211
ended_at: 2026-01-30 00:20:18.856311
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9861190470973448, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-30 00:20:19.669958
ended_at: 2026-01-30 00:20:24.351685
output_json:
  {"clicked_at": {"x": 994, "y": 195}, "mode": "debug", "confidence": 0.9695447467160596, "method": "clip"}


execution_id: exec_ea59b8004fff_1769732313
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-30 00:20:34.365580
ended_at: 2026-01-30 00:20:35.169659
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse et version corrig\u00e9e en anglais**\n\nKimi\u2011K2.5 is an open\u2011sou..."}


execution_id: exec_14320be98673_1769734818
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-30 01:00:29.185641
ended_at: 2026-01-30 01:00:34.099055
output_json:
  {"clicked_at": {"x": 993, "y": 192}, "mode": "debug", "confidence": 0.9600715867135581, "method": "clip"}


execution_id: exec_14320be98673_1769734818
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-30 01:00:34.104731
ended_at: 2026-01-30 01:00:40.685348
output_json:
  {"clicked_at": {"x": 830, "y": 194}, "mode": "debug", "confidence": 0.9945844024462756, "method": "clip"}


execution_id: exec_14320be98673_1769734818
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-30 01:00:46.709364
ended_at: 2026-01-30 01:01:42.488684
output_json:
  {"analysis": "**Corrected English Version**\n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed visual\u2011and\u2011text tokens, based on Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, including real\u2011time and deliberative modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native Multimodality** \u2013 Pre\u2011trained on vision\u2013language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision** \u2013 K2.5 generates code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm** \u2013 K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open\u2011source, d\u00e9velopp\u00e9 par un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de tokens mixtes visuels et textuels, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, incluant des modes temps r\u00e9el et d\u00e9lib\u00e9ratifs, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s cl\u00e9s**\n\n- **Multimodalit\u00e9 native** \u2013 Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens visio\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage visuel** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (par ex., conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Arm\u00e9e d\u2019agents** \u2013 K2.5 passe d\u2019une mont\u00e9e en charge d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et auto\u2011dirig\u00e9 en mode essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.\n\n---\n\n**\u4e2d\u6587\u7ffb\u8bd1**\n\nKimi\u202fK2.5 \u662f\u4e00\u6b3e\u5f00\u6e90\u3001\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c token \u6784\u5efa\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u4e0e\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u65e0\u7f1d\u6574\u5408\uff0c\u5305\u62ec\u5b9e\u65f6\u548c\u6df1\u601d\u719f\u8651\u4e24\u79cd\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u529f\u80fd**\n\n- **\u539f\u751f\u591a\u6a21\u6001** \u2013 \u5728\u89c6\u89c9-\u8bed\u8a00 token \u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801** \u2013 K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08\u5982 UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53** \u2013 K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u5bfc\u5411\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9488\u5bf9\u7279\u5b9a\u9886\u57df\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_14320be98673_1769734818
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-30 01:01:42.508193
ended_at: 2026-01-30 01:01:48.893061
output_json:
  {"clicked_at": {"x": 33, "y": 1046}, "mode": "debug", "confidence": 0.9934484176938366, "method": "clip"}


execution_id: exec_14320be98673_1769734818
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-30 01:01:49.707756
ended_at: 2026-01-30 01:01:54.490331
output_json:
  {"clicked_at": {"x": 995, "y": 197}, "mode": "debug", "confidence": 0.9636299157819719, "method": "clip"}


execution_id: exec_14320be98673_1769734818
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-30 01:02:04.503647
ended_at: 2026-01-30 01:02:05.307604
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Corrected English Version**\n\nKimi\u202fK2.5 is an open\u2011source, native m..."}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-01-30 10:00:42.073564
ended_at: 2026-01-30 10:00:48.806524
output_json:
  {"clicked_at": {"x": 33, "y": 1047}, "mode": "intelligent", "confidence": 0.992071216912725, "method": "clip"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-01-30 10:00:49.622270
ended_at: 2026-01-30 10:00:54.427270
output_json:
  {"clicked_at": {"x": 995, "y": 195}, "mode": "intelligent", "confidence": 0.9609632514304178, "method": "clip"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-01-30 10:00:54.433077
ended_at: 2026-01-30 10:01:01.876518
output_json:
  {"clicked_at": {"x": 807, "y": 159}, "mode": "intelligent", "confidence": 0.5781167572360525, "method": "clip"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-01-30 10:01:07.899586
ended_at: 2026-01-30 10:02:05.963679
output_json:
  {"analysis": "**Texte corrig\u00e9 (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed vision\u2011and\u2011text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native multimodality:** Pre\u2011trained on vision\u2011language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with vision:** K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent swarm:** K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.  \n\n---\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source, natif, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de jetons visuels et textuels combin\u00e9s, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans faille la vision et la compr\u00e9hension du langage avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s cl\u00e9s**  \n- **Multimodalit\u00e9 native :** Pr\u00e9\u2011entra\u00een\u00e9 sur des jetons vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Programmation avec vision :** K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils de traitement de donn\u00e9es visuelles.  \n- **Essaim d\u2019agents :** K2.5 passe d\u2019une mont\u00e9e en charge d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution autonome et coordonn\u00e9 en mode essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.  \n\n---\n\n**\u4e2d\u6587\u7ffb\u8bd1**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u3001\u539f\u751f\u7684\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15 \u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u529f\u80fd**  \n- **\u539f\u751f\u591a\u6a21\u6001\uff1a** \u9884\u8bad\u7ec3\u4e8e\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7a0b\uff1a** K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u96c6\uff1a** K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u540c\u7684\u7fa4\u96c6\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u5c5e\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-01-30 10:02:05.969877
ended_at: 2026-01-30 10:02:14.195318
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "intelligent", "confidence": 0.986578530151824, "method": "clip"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-01-30 10:02:15.009928
ended_at: 2026-01-30 10:02:19.784579
output_json:
  {"clicked_at": {"x": 993, "y": 192}, "mode": "intelligent", "confidence": 0.9629898816092495, "method": "clip"}


execution_id: exec_528de4d24f6d_1769767241
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-01-30 10:02:29.797461
ended_at: 2026-01-30 10:02:30.602101
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Texte corrig\u00e9 (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native mu..."}


execution_id: exec_d32b4ed6b43e_1770748836
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-02-10 18:40:44.322808
ended_at: 2026-02-10 18:41:54.490541
output_json:
  {"analysis": "**Analyse du texte**  \nLe passage d\u00e9crit le mod\u00e8le Kimi\u202fK2.5, un agent multimodal open\u2011source. Le texte est d\u00e9j\u00e0 assez clair, mais quelques formulations peuvent \u00eatre affin\u00e9es pour une meilleure fluidit\u00e9 et une plus grande pr\u00e9cision. Les erreurs mineures de ponctuation et de syntaxe sont corrig\u00e9es, et le style est rendu plus coh\u00e9rent tout en conservant les termes techniques essentiels.\n\n---\n\n**Texte corrig\u00e9 (anglais)**  \n\n*Kimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continuously pretrained on approximately 15\u202ftrillion mixed visual and text tokens, building upon Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, including instant and thinking modes, as well as conversational and agentic paradigms.*\n\n**Key Features**  \n- **Native Multimodality**: Trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm**: K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**  \n\n*Kimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source, pr\u00e9\u2011entra\u00een\u00e9 de fa\u00e7on continue sur environ 15\u202ftrillions de tokens visuels et textuels mixtes, en s\u2019appuyant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans effort la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, incluant des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.*\n\n**Caract\u00e9ristiques cl\u00e9s**  \n- **Multimodalit\u00e9 native** : Form\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement intermodal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec la vision** : K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019UI, workflows vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Swarms d\u2019agents** : K2.5 passe de l\u2019\u00e9chelle \u00e0 un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 en mode \u00ab\u202fswarm\u202f\u00bb. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents sp\u00e9cifiques \u00e0 un domaine, instanci\u00e9s dynamiquement.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**  \n\n*Kimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base\uff0c\u6301\u7eed\u9884\u8bad\u7ec3\u4e86\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u3002\u5b83\u65e0\u7f1d\u6574\u5408\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u5305\u62ec\u5373\u65f6\u6a21\u5f0f\u3001\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002*\n\n**\u4e3b\u8981\u529f\u80fd**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u7684\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u5bfc\u5411\u3001\u534f\u540c\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u7279\u5b9a\u9886\u57df\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_d32b4ed6b43e_1770748836
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-02-10 18:42:05.529397
ended_at: 2026-02-10 18:42:06.333150
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte**  \nLe passage d\u00e9crit le mod\u00e8le Kimi\u202fK2.5, un age..."}


execution_id: exec_414243d397a3_1770748981
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-02-10 18:43:02.116734
ended_at: 2026-02-10 18:43:10.771175
output_json:
  {"clicked_at": {"x": 34, "y": 1045}, "mode": "debug", "confidence": 0.991480643873603, "method": "clip"}


execution_id: exec_414243d397a3_1770748981
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-02-10 18:43:11.589971
ended_at: 2026-02-10 18:43:16.329168
output_json:
  {"clicked_at": {"x": 993, "y": 195}, "mode": "debug", "confidence": 0.9695319524292834, "method": "clip"}


execution_id: exec_414243d397a3_1770748981
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-02-10 18:43:16.334555
ended_at: 2026-02-10 18:43:22.463171
output_json:
  {"clicked_at": {"x": 830, "y": 195}, "mode": "debug", "confidence": 0.9909380417665965, "method": "clip"}


execution_id: exec_414243d397a3_1770748981
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-02-10 18:43:28.486296
ended_at: 2026-02-10 18:44:56.111842
output_json:
  {"analysis": "**Analyse du texte**  \nLe passage d\u00e9crit le mod\u00e8le multimodal \u00ab\u202fKimi\u202fK2.5\u202f\u00bb, un agent open\u2011source qui combine vision, langage et capacit\u00e9s d\u2019agent. Il met l\u2019accent sur son entra\u00eenement massif (\u2248\u202f15\u202ftrillions de tokens visuels et textuels), ses modes de fonctionnement (instantan\u00e9 et r\u00e9fl\u00e9chi), et ses paradigmes conversationnels. Les trois points forts sont la multimodalit\u00e9 native, la g\u00e9n\u00e9ration de code \u00e0 partir de sp\u00e9cifications visuelles, et l\u2019ex\u00e9cution en \u00ab\u202fessaim\u202f\u00bb d\u2019agents autonomes qui d\u00e9composent les t\u00e2ches complexes. Le texte est globalement clair mais comporte quelques maladresses grammaticales et des expressions qui pourraient \u00eatre affin\u00e9es pour une meilleure lisibilit\u00e9.\n\n---\n\n**Texte corrig\u00e9 (en anglais)**  \n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pre\u2011trained on roughly 15\u202ftrillion mixed visual and text tokens, building upon Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering both instant and reflective modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native multimodality**: Pre\u2011trained on vision\u2013language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent swarm**: K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**\n\nKimi\u202fK2.5 est un mod\u00e8le d\u2019agent multimodal natif et open\u2011source, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de tokens mixtes visuels et textuels, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans effort la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, offrant des modes instantan\u00e9s et r\u00e9flexifs, ainsi que des paradigmes conversationnels et agentiques.\n\n**Fonctionnalit\u00e9s cl\u00e9s**\n\n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Essaim d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et auto\u2011dirig\u00e9, semblable \u00e0 un essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 un domaine.\n\n---\n\n**Traduction en chinois**\n\nKimi\u202fK2.5 \u662f\u4e00\u6b3e\u5f00\u6e90\u7684\u539f\u751f\u591a\u6a21\u6001\u667a\u80fd\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u7684\u57fa\u7840\u4e0a\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u89c6\u89c9\u4e0e\u6587\u672c\u6df7\u5408\u6807\u8bb0\u8fdb\u884c\u8bad\u7ec3\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u65e0\u7f1d\u878d\u5408\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u652f\u6301\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**\n\n- **\u539f\u751f\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7a0b**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u53ef\u5e76\u884c\u6267\u884c\u7684\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u7279\u5b9a\u4ee3\u7406\u5b8c\u6210\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_414243d397a3_1770748981
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-02-10 18:45:07.469149
ended_at: 2026-02-10 18:45:12.225200
output_json:
  {"clicked_at": {"x": 994, "y": 191}, "mode": "debug", "confidence": 0.9828103418997759, "method": "clip"}


execution_id: exec_414243d397a3_1770748981
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-02-10 18:45:22.238477
ended_at: 2026-02-10 18:45:23.041987
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte**  \nLe passage d\u00e9crit le mod\u00e8le multimodal \u00ab\u202fKimi..."}


execution_id: exec_7c8ca97ac8a4_1770749201
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-02-10 18:46:49.127650
ended_at: 2026-02-10 18:47:36.254088
output_json:
  {"analysis": "**Analyse et correction du texte original (anglais)**  \n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed visual and text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native Multimodality**: Pre\u2011trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool usage grounded in visual inputs.  \n- **Coding with Vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm**: K2.5 transitions from a single\u2011agent scaling model to a self\u2011directed, coordinated swarm\u2011like execution scheme, decomposing complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.  \n\n---\n\n## Traduction en fran\u00e7ais\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de jetons visuels et textuels combin\u00e9s, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans effort la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques principales**  \n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des jetons vision\u2011langage, K2.5 excelle dans les connaissances visuelles, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques fond\u00e9s sur les entr\u00e9es visuelles.  \n- **Programmation visuelle**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **R\u00e9seau d\u2019agents**\u202f: K2.5 passe d\u2019un mod\u00e8le \u00e0 agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 en mode essaim auto\u2011dirig\u00e9, d\u00e9composant les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.  \n\n---\n\n## \u7ffb\u8bd1\u6210\u4e2d\u6587\n\nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u4e86\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9\u2011\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7a0b**\uff1aK2.5 \u80fd\u4ece\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u6307\u5bfc\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\uff0c\u62c6\u89e3\u590d\u6742\u4efb\u52a1\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u5c5e\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_7c8ca97ac8a4_1770749201
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-02-10 18:47:47.310715
ended_at: 2026-02-10 18:47:48.114407
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse et correction du texte original (anglais)**  \n\nKimi\u202fK2.5 i..."}


execution_id: exec_ebab054e5915_1770802827
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-02-11 09:40:27.362853
ended_at: 2026-02-11 09:40:38.559839
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9929561122274622, "method": "clip"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-02-11 09:40:39.377786
ended_at: 2026-02-11 09:40:44.371785
output_json:
  {"clicked_at": {"x": 993, "y": 194}, "mode": "debug", "confidence": 0.9667403043033305, "method": "clip"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-02-11 09:40:44.377315
ended_at: 2026-02-11 09:40:53.499957
output_json:
  {"clicked_at": {"x": 818, "y": 198}, "mode": "debug", "confidence": 0.6165212635469414, "method": "clip"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-02-11 09:40:59.524496
ended_at: 2026-02-11 09:41:53.808014
output_json:
  {"analysis": "**Texte corrig\u00e9 (anglais)\u00a0:**\n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed visual and text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, including instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native Multimodality:** Pre\u2011trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision:** K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm:** K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction fran\u00e7aise\u00a0:**\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open\u2011source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202fbilliards de tokens visuels et textuels m\u00e9lang\u00e9s, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, incluant des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**\n\n- **Multimodalit\u00e9 native\u202f:** Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens visuel\u2011langage, K2.5 excelle en connaissance visuelle, raisonnement cross\u2011modal et utilisation d\u2019outils agentiques fond\u00e9s sur des entr\u00e9es visuelles.  \n- **Codage avec vision\u202f:** K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019UI, flux vid\u00e9o) et orchestre de mani\u00e8re autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Masse d\u2019agents\u202f:** K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 en mode essaim auto\u2011dirig\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 un domaine.\n\n---\n\n**\u4e2d\u6587\u7ffb\u8bd1\u00a0:**\n\nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u3001\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15 \u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c token \u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u6574\u5408\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u5305\u62ec\u5373\u65f6\u6a21\u5f0f\u3001\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**\n\n- **\u539f\u751f\u591a\u6a21\u6001\u6027\uff1a** \u5728\u89c6\u89c9\u2011\u8bed\u8a00 token \u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801\uff1a** K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53\uff1a** K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u5bfc\u5411\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u7279\u5b9a\u9886\u57df\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-02-11 09:41:53.815477
ended_at: 2026-02-11 09:42:01.980740
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9884065535796968, "method": "clip"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-02-11 09:42:02.795700
ended_at: 2026-02-11 09:42:07.623256
output_json:
  {"clicked_at": {"x": 994, "y": 191}, "mode": "debug", "confidence": 0.9836894355122711, "method": "clip"}


execution_id: exec_ebab054e5915_1770802827
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-02-11 09:42:17.636555
ended_at: 2026-02-11 09:42:18.440931
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Texte corrig\u00e9 (anglais)\u00a0:**\n\nKimi\u202fK2.5 is an open\u2011source, native m..."}


execution_id: exec_a46ac1d6de37_1772663383
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-03-04 22:29:44.227380
ended_at: 2026-03-04 22:29:50.727045
output_json:
  {"clicked_at": {"x": 35, "y": 1046}, "mode": "intelligent", "confidence": 0.8480372851773829, "method": "clip"}


execution_id: exec_a46ac1d6de37_1772663383
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-03-04 22:29:51.548379
ended_at: 2026-03-04 22:29:56.372146
output_json:
  {"clicked_at": {"x": 992, "y": 197}, "mode": "intelligent", "confidence": 0.9621947725382672, "method": "clip"}


execution_id: exec_a46ac1d6de37_1772663383
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-03-04 22:29:56.379454
ended_at: 2026-03-04 22:30:04.796109
output_json:
  {"clicked_at": {"x": 807, "y": 159}, "mode": "intelligent", "confidence": 0.5751044777364474, "method": "clip"}


execution_id: exec_a46ac1d6de37_1772663383
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-03-04 22:30:10.818255
ended_at: 2026-03-04 22:31:24.499527
output_json:
  {"analysis": "**Analyse et am\u00e9lioration du texte original (en anglais)**  \n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source et natif, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de tokens visuels et textuels mixtes, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.  \n\n**Caract\u00e9ristiques cl\u00e9s**  \n\n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans les connaissances visuelles, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage par vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils de traitement de donn\u00e9es visuelles.  \n- **Swarme d\u2019agents**\u202f: K2.5 passe d\u2019une mont\u00e9e en charge \u00e0 un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en mode essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 un domaine.  \n\n---\n\n**Traduction en fran\u00e7ais**  \n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source et natif, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202ftrillions de tokens visuels et textuels mixtes, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de mani\u00e8re transparente la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.  \n\n**Caract\u00e9ristiques cl\u00e9s**  \n\n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans les connaissances visuelles, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage par vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils de traitement de donn\u00e9es visuelles.  \n- **Swarme d\u2019agents**\u202f: K2.5 passe d\u2019une mont\u00e9e en charge \u00e0 un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en mode essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 un domaine.  \n\n---\n\n**Traduction en chinois**  \n\nKimi\u202fK2.5 \u662f\u4e00\u6b3e\u5f00\u6e90\u3001\u539f\u751f\u7684\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 15 \u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u4e0e\u9ad8\u7ea7\u4ee3\u7406\u80fd\u529b\u65e0\u7f1d\u96c6\u6210\uff0c\u5177\u5907\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u4f1a\u8bdd\u548c\u4ee3\u7406\u8303\u5f0f\u3002  \n\n**\u4e3b\u8981\u7279\u6027**  \n\n- **\u539f\u751f\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9-\u8bed\u8a00\u6807\u8bb0\u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u8c03\u5ea6\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u5bfc\u5411\u3001\u534f\u540c\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u7279\u5b9a\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_2e1929267ebc_1773241075
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-03-11 14:57:58.751311
ended_at: 2026-03-11 14:58:00.867241
output_json:
  {"clicked_at": {"x": 994.0, "y": 199.0}, "mode": "debug", "confidence": 1.0, "method": "zoned_template"}


execution_id: exec_2e1929267ebc_1773241075
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-03-11 14:58:00.872395
ended_at: 2026-03-11 14:58:02.985413
output_json:
  {"clicked_at": {"x": 848.0, "y": 277.0}, "mode": "debug", "confidence": 0.9702301025390625, "method": "zoned_template"}


execution_id: exec_2e1929267ebc_1773241075
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-03-11 14:58:09.008851
ended_at: 2026-03-11 14:59:19.067209
output_json:
  {"analysis": "**Corrected English version**\n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pretrained on approximately 15\u202ftrillion mixed visual and text tokens built atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native multimodality** \u2013 Pretrained on vision\u2011language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with vision** \u2013 K2.5 generates code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent swarm** \u2013 K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction fran\u00e7aise**\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source et natif, entra\u00een\u00e9 de fa\u00e7on continue sur environ 15\u202ftrillions de tokens visuels et textuels combin\u00e9s, construit sur la base Kimi\u2011K2\u2011Base. Il int\u00e8gre sans effort la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, offrant des modes instantan\u00e9s et r\u00e9flexifs, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**\n\n- **Multimodalit\u00e9 native** \u2013 Entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec la vision** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (par ex., conceptions d\u2019interface utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils pour le traitement de donn\u00e9es visuelles.  \n- **Groupe d\u2019agents** \u2013 K2.5 passe d\u2019une mont\u00e9e en charge \u00e0 agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents sp\u00e9cifiques au domaine instanci\u00e9s dynamiquement.\n\n---\n\n**\u4e2d\u6587\u7ffb\u8bd1**\n\nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u3001\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u7684\u57fa\u7840\u4e0a\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15 \u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c token\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u4e0e\u9ad8\u7ea7\u4ee3\u7406\u80fd\u529b\u65e0\u7f1d\u6574\u5408\uff0c\u63d0\u4f9b\u5373\u65f6\u548c\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**\n\n- **\u539f\u751f\u591a\u6a21\u6001** \u2013 \u5728\u89c6\u89c9\u2011\u8bed\u8a00 token \u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801** \u2013 K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08\u5982 UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4** \u2013 K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u7684\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u5206\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u7279\u5b9a\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_2e1929267ebc_1773241075
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-03-11 14:59:22.052671
ended_at: 2026-03-11 14:59:24.165585
output_json:
  {"clicked_at": {"x": 992.0, "y": 191.0}, "mode": "debug", "confidence": 0.9999995231628418, "method": "zoned_template"}


execution_id: exec_2e1929267ebc_1773241075
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-03-11 14:59:34.188835
ended_at: 2026-03-11 14:59:34.992679
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Corrected English version**\n\nKimi\u202fK2.5 is an open\u2011source, native m..."}


execution_id: exec_0276b0e4f217_1773301594
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-03-12 07:46:42.095541
ended_at: 2026-03-12 07:47:57.625540
output_json:
  {"analysis": "**Analyse du texte**  \nLe passage pr\u00e9sente *Kimi\u202fK2.5*, un mod\u00e8le multimodal open\u2011source qui combine vision et langage tout en disposant de capacit\u00e9s \u00ab\u202fagentiques\u202f\u00bb (autonomie, orchestration d\u2019outils, ex\u00e9cution de t\u00e2ches complexes). Le texte met en avant trois axes majeurs\u202f: la multimodalit\u00e9 native, la g\u00e9n\u00e9ration de code \u00e0 partir d\u2019entr\u00e9es visuelles et la transition vers un \u00ab\u202fswarm\u202f\u00bb d\u2019agents autonomes. Le style est technique mais assez clair ; toutefois, quelques tournures sont maladroites ou redondantes (ex. \u00ab\u202finstant and thinking modes\u202f\u00bb), et certains termes anglophones ne sont pas traduits ou expliqu\u00e9s. La phrase finale sur le \u00ab\u202fswarm\u2011like execution scheme\u202f\u00bb est un peu longue et pourrait \u00eatre simplifi\u00e9e pour une meilleure lisibilit\u00e9.\n\n---\n\n**Texte corrig\u00e9 (anglais)**  \n\n*Kimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed visual and text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.*\n\n**Key Features**  \n- **Native Multimodality**: Pre\u2011trained on vision\u2011language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm**: K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction fran\u00e7aise**  \n\n*Kimi\u202fK2.5 est un mod\u00e8le agentique multimodal open\u2011source, natif, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202fbilliards de tokens visuels et textuels combin\u00e9s, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre sans faille la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et r\u00e9flexifs, ainsi que des paradigmes conversationnels et agentiques.*\n\n**Caract\u00e9ristiques cl\u00e9s**  \n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans les connaissances visuelles, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques fond\u00e9s sur les entr\u00e9es visuelles.  \n- **Codage avec la vision**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interfaces, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement des donn\u00e9es visuelles.  \n- **Groupe d\u2019agents**\u202f: K2.5 passe d\u2019une mont\u00e9e en charge d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution de type essaim auto\u2011dirig\u00e9 et coordonn\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cialis\u00e9s dans un domaine.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**  \n\n*Kimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 15 \u4e07\u4ebf\u4e2a\u89c6\u89c9\u548c\u6587\u672c\u6df7\u5408 token \u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u4e86\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u4ee5\u53ca\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u4f1a\u8bdd\u548c\u4ee3\u7406\u8303\u5f0f\u3002*\n\n**\u5173\u952e\u7279\u6027**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1a\u5728\u89c6\u89c9-\u8bed\u8a00 token \u4e0a\u9884\u8bad\u7ec3\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7a0b**\uff1aK2.5 \u80fd\u4ece\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u96c6**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u9a71\u52a8\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u96c6\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9886\u57df\u7279\u5b9a\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_0276b0e4f217_1773301594
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-03-12 07:48:08.688917
ended_at: 2026-03-12 07:48:09.492934
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse du texte**  \nLe passage pr\u00e9sente *Kimi\u202fK2.5*, un mod\u00e8le mu..."}


execution_id: exec_0f85bc4a398b_1773302394
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-03-12 07:59:57.545917
ended_at: 2026-03-12 07:59:59.660832
output_json:
  {"clicked_at": {"x": 994.0, "y": 199.0}, "mode": "debug", "confidence": 0.9999998211860657, "method": "zoned_template"}


execution_id: exec_0f85bc4a398b_1773302394
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-03-12 07:59:59.666008
ended_at: 2026-03-12 08:00:01.780206
output_json:
  {"clicked_at": {"x": 830.0, "y": 193.0}, "mode": "debug", "confidence": 0.9999898672103882, "method": "zoned_template"}


execution_id: exec_0f85bc4a398b_1773302394
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-03-12 08:00:07.857333
ended_at: 2026-03-12 08:01:17.598471
output_json:
  {"analysis": "**Texte corrig\u00e9 en anglais (pour clart\u00e9 et lisibilit\u00e9) :**\n\nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model built through continual pre\u2011training on approximately 15\u202ftrillion mixed vision\u2011and\u2011text tokens atop Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**\n\n- **Native Multimodality** \u2013 Pre\u2011trained on vision\u2013language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision** \u2013 K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm** \u2013 K2.5 transitions from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.  \n\n---\n\n**Traduction en fran\u00e7ais :**\n\nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open\u2011source, construit gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202fbilliards de tokens mixtes visuels et textuels, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**\n\n- **Multimodalit\u00e9 native** \u2013 Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement intermodal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage visuel** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Groupe d\u2019agents** \u2013 K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle d\u2019un seul agent \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et auto\u2011dirig\u00e9, semblable \u00e0 un essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.  \n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587\uff08\u7b80\u4f53\uff09\uff1a**\n\nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u4e4b\u4e0a\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u7684 token \u6784\u5efa\u3002\u5b83\u65e0\u7f1d\u96c6\u6210\u4e86\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u3001\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u4e0e\u4ee3\u7406\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u6027**\n\n- **\u672c\u5730\u591a\u6a21\u6001** \u2013 \u9884\u8bad\u7ec3\u4e8e\u89c6\u89c9\u2013\u8bed\u8a00 token\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801** \u2013 K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53** \u2013 K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u5bfc\u5411\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u9886\u57df\u7279\u5b9a\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_0f85bc4a398b_1773302394
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-03-12 08:01:20.556460
ended_at: 2026-03-12 08:01:22.668545
output_json:
  {"clicked_at": {"x": 992.0, "y": 191.0}, "mode": "debug", "confidence": 0.9999997615814209, "method": "zoned_template"}


execution_id: exec_0f85bc4a398b_1773302394
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-03-12 08:01:32.681634
ended_at: 2026-03-12 08:01:33.485570
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Texte corrig\u00e9 en anglais (pour clart\u00e9 et lisibilit\u00e9) :**\n\nKimi\u202fK2...."}


execution_id: exec_1222cd0617bd_1773756197
step_id: step_c995dee8b9be_1773753106
status: success
started_at: 2026-03-17 14:03:18.302035
ended_at: 2026-03-17 14:03:32.799025
output_json:
  {"clicked_at": {"x": 686, "y": 1058}, "mode": "intelligent", "confidence": 0.8630366189571856, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-04-02 12:13:42.243368
ended_at: 2026-04-02 12:13:53.065840
output_json:
  {"clicked_at": {"x": 34, "y": 1047}, "mode": "debug", "confidence": 0.9904663952273333, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-04-02 12:13:53.881399
ended_at: 2026-04-02 12:13:59.123016
output_json:
  {"clicked_at": {"x": 992, "y": 197}, "mode": "debug", "confidence": 0.9542251499239078, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-04-02 12:13:59.128614
ended_at: 2026-04-02 12:14:08.832981
output_json:
  {"clicked_at": {"x": 807, "y": 159}, "mode": "debug", "confidence": 0.5843419006462269, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-04-02 12:14:14.858815
ended_at: 2026-04-02 12:15:45.467049
output_json:
  {"analysis": "**Analyse et correction du texte original (anglais)**  \nLe passage est d\u00e9j\u00e0 bien r\u00e9dig\u00e9, mais quelques ajustements mineurs am\u00e9liorent la fluidit\u00e9 et la clart\u00e9 :  \n- Remplacer \u00ab instant and thinking modes \u00bb par \u00ab instantaneous and deliberative modes \u00bb pour plus de pr\u00e9cision.  \n- Clarifier \u00ab agentic paradigms \u00bb en \u00ab agentic paradigms and conversational modes \u00bb.  \n- Uniformiser l\u2019usage de \u00ab agentic \u00bb en fran\u00e7ais (\u00ab agentique \u00bb).  \n- Mettre un tiret dans \u00ab vision\u2011language tokens \u00bb pour \u00e9viter la confusion.  \n\n---\n\n### Traduction en fran\u00e7ais\n\n**Kimi K2.5** est un mod\u00e8le agentique multimodal natif et open\u2011source, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ **15\u202fmilliards** de tokens visuels et textuels combin\u00e9s, reposant sur **Kimi\u2011K2\u2011Base**. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, des modes instantan\u00e9s et de r\u00e9flexion, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**  \n- **Multimodalit\u00e9 native** : pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement cross\u2011modal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage par vision** : K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions d\u2019interfaces utilisateur, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement des donn\u00e9es visuelles.  \n- **Essaim d\u2019agents** : K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 un agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution coordonn\u00e9 et autonome en mode essaim. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cialis\u00e9s dans chaque domaine.\n\n---\n\n### Traduction en chinois (\u7b80\u4f53\u4e2d\u6587)\n\n**Kimi K2.5** \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u672c\u5730\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e **Kimi\u2011K2\u2011Base** \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 **15 \u4e07\u4ebf** \u4e2a\u6df7\u5408\u89c6\u89c9\u548c\u6587\u672c\u6807\u8bb0\u6784\u5efa\u3002\u5b83\u5c06\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\u4e0e\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\u65e0\u7f1d\u878d\u5408\uff0c\u5177\u5907\u5373\u65f6\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u529f\u80fd**  \n- **\u672c\u5730\u591a\u6a21\u6001**\uff1aK2.5 \u5728\u89c6\u89c9-\u8bed\u8a00\u6807\u8bb0\u4e0a\u8fdb\u884c\u9884\u8bad\u7ec3\uff0c\u64c5\u957f\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\uff0c\u5e76\u4ee5\u89c6\u89c9\u8f93\u5165\u4e3a\u57fa\u7840\u8fdb\u884c\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u3002  \n- **\u89c6\u89c9\u7f16\u7a0b**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u8702\u7fa4**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u5bfc\u5411\u3001\u534f\u8c03\u4e00\u81f4\u7684\u8702\u7fa4\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u7528\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-04-02 12:15:45.480059
ended_at: 2026-04-02 12:15:51.468421
output_json:
  {"clicked_at": {"x": 34, "y": 1046}, "mode": "debug", "confidence": 0.9923234369074972, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-04-02 12:15:52.283910
ended_at: 2026-04-02 12:15:57.060476
output_json:
  {"clicked_at": {"x": 994, "y": 195}, "mode": "debug", "confidence": 0.9687837695409456, "method": "clip"}


execution_id: exec_1a045cceec5a_1775132021
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-04-02 12:16:07.074138
ended_at: 2026-04-02 12:16:07.878142
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Analyse et correction du texte original (anglais)**  \nLe passage e..."}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-04-02 12:43:15.845398
ended_at: 2026-04-02 12:43:25.726956
output_json:
  {"clicked_at": {"x": 33, "y": 1045}, "mode": "debug", "confidence": 0.9948143704553883, "method": "clip"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_274b22100233_1769197670
status: success
started_at: 2026-04-02 12:43:26.541711
ended_at: 2026-04-02 12:43:31.577017
output_json:
  {"clicked_at": {"x": 992, "y": 198}, "mode": "debug", "confidence": 0.9582884084896476, "method": "clip"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-04-02 12:43:31.582339
ended_at: 2026-04-02 12:43:37.287239
output_json:
  {"clicked_at": {"x": 831, "y": 195}, "mode": "debug", "confidence": 0.9900137462536444, "method": "clip"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-04-02 12:43:43.314361
ended_at: 2026-04-02 12:44:28.541504
output_json:
  {"analysis": "**Texte corrig\u00e9 et clarifi\u00e9 (anglais)**  \nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pretrained on roughly 15\u202ftrillion mixed vision\u2011and\u2011text tokens, building on Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering instant and thinking modes, as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native multimodality**: Pretrained on vision\u2011language tokens, K2.5 excels at visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with vision**: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent swarm**: K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme. It decomposes complex tasks into parallel sub\u2011tasks executed by dynamically instantiated, domain\u2011specific agents.  \n\n---\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open\u2011source, form\u00e9 par pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202fmilliards de tokens mixtes visuels et textuels, reposant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, proposant des modes instantan\u00e9s et r\u00e9fl\u00e9chis, ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques cl\u00e9s**  \n- **Multimodalit\u00e9 native**\u202f: Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens vision\u2011langage, K2.5 excelle dans la connaissance visuelle, le raisonnement intermodal et l\u2019utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage visuel**\u202f: K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome des outils pour le traitement de donn\u00e9es visuelles.  \n- **Royaume d\u2019agents**\u202f: K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim coordonn\u00e9 et auto\u2011dirig\u00e9. Il d\u00e9compose les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 chaque domaine.  \n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u3001\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u5728 Kimi\u2011K2\u2011Base \u7684\u57fa\u7840\u4e0a\uff0c\u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c\u6807\u8bb0\uff0c\u6784\u5efa\u800c\u6210\u3002\u5b83\u65e0\u7f1d\u6574\u5408\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u63d0\u4f9b\u5373\u65f6\u6a21\u5f0f\u4e0e\u601d\u8003\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u548c\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**  \n- **\u539f\u751f\u591a\u6a21\u6001**\uff1a\u9884\u8bad\u7ec3\u4e8e\u89c6\u89c9-\u8bed\u8a00\u6807\u8bb0\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u8f93\u5165\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801**\uff1aK2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u534f\u8c03\u5de5\u5177\u8fdb\u884c\u89c6\u89c9\u6570\u636e\u5904\u7406\u3002  \n- **\u4ee3\u7406\u7fa4\u4f53**\uff1aK2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u5230\u81ea\u6211\u5bfc\u5411\u3001\u534f\u8c03\u4e00\u81f4\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\u3002\u5b83\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u5206\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u3001\u7279\u5b9a\u9886\u57df\u7684\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-04-02 12:44:28.552260
ended_at: 2026-04-02 12:44:36.452628
output_json:
  {"clicked_at": {"x": 33, "y": 1046}, "mode": "debug", "confidence": 0.9924418966225333, "method": "clip"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-04-02 12:44:37.268120
ended_at: 2026-04-02 12:44:41.969586
output_json:
  {"clicked_at": {"x": 994, "y": 195}, "mode": "debug", "confidence": 0.9760314605878165, "method": "clip"}


execution_id: exec_f504f4c42c75_1775133795
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-04-02 12:44:51.982798
ended_at: 2026-04-02 12:44:52.786812
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Texte corrig\u00e9 et clarifi\u00e9 (anglais)**  \nKimi\u202fK2.5 is an open\u2011sourc..."}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_6184d7fd0f5b_1769196774
status: success
started_at: 2026-04-02 12:49:29.069332
ended_at: 2026-04-02 12:49:38.660635
output_json:
  {"clicked_at": {"x": 32, "y": 1045}, "mode": "debug", "confidence": 0.9927617931412769, "method": "clip"}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_957fe56946d0_1769200014
status: success
started_at: 2026-04-02 12:49:44.688864
ended_at: 2026-04-02 12:49:50.810562
output_json:
  {"clicked_at": {"x": 831, "y": 195}, "mode": "debug", "confidence": 0.9891300851348296, "method": "clip"}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_a393cbf114cb_1769720990
status: success
started_at: 2026-04-02 12:49:56.835135
ended_at: 2026-04-02 12:50:51.783420
output_json:
  {"analysis": "**Version corrig\u00e9e en anglais**  \nKimi\u202fK2.5 is an open\u2011source, native multimodal agentic model that has been continually pretrained on roughly 15\u202ftrillion mixed visual\u2011and\u2011text tokens, building upon Kimi\u2011K2\u2011Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, offering both instant and deliberative modes as well as conversational and agentic paradigms.\n\n**Key Features**  \n- **Native Multimodality** \u2013 Pre\u2011trained on vision\u2011language tokens, K2.5 excels in visual knowledge, cross\u2011modal reasoning, and agentic tool use grounded in visual inputs.  \n- **Coding with Vision** \u2013 K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.  \n- **Agent Swarm** \u2013 K2.5 moves from single\u2011agent scaling to a self\u2011directed, coordinated swarm\u2011like execution scheme, decomposing complex tasks into parallel sub\u2011tasks carried out by dynamically instantiated, domain\u2011specific agents.\n\n---\n\n**Traduction en fran\u00e7ais**  \nKimi\u202fK2.5 est un mod\u00e8le agentique multimodal natif et open source, d\u00e9velopp\u00e9 gr\u00e2ce \u00e0 un pr\u00e9\u2011entra\u00eenement continu sur environ 15\u202fbilliards de tokens visuels et textuels combin\u00e9s, s\u2019appuyant sur Kimi\u2011K2\u2011Base. Il int\u00e8gre de fa\u00e7on fluide la compr\u00e9hension visuelle et linguistique avec des capacit\u00e9s agentiques avanc\u00e9es, offrant des modes instantan\u00e9s et r\u00e9fl\u00e9chis ainsi que des paradigmes conversationnels et agentiques.\n\n**Caract\u00e9ristiques principales**  \n- **Multimodalit\u00e9 native** \u2013 Pr\u00e9\u2011entra\u00een\u00e9 sur des tokens visuel\u2011langage, K2.5 excelle en connaissances visuelles, raisonnement cross\u2011modal et utilisation d\u2019outils agentiques ancr\u00e9s dans les entr\u00e9es visuelles.  \n- **Codage avec vision** \u2013 K2.5 g\u00e9n\u00e8re du code \u00e0 partir de sp\u00e9cifications visuelles (conceptions UI, flux vid\u00e9o) et orchestre de fa\u00e7on autonome les outils de traitement de donn\u00e9es visuelles.  \n- **Groupe d\u2019agents** \u2013 K2.5 passe d\u2019une mise \u00e0 l\u2019\u00e9chelle \u00e0 agent unique \u00e0 un sch\u00e9ma d\u2019ex\u00e9cution en essaim auto\u2011dirig\u00e9 et coordonn\u00e9, d\u00e9composant les t\u00e2ches complexes en sous\u2011t\u00e2ches parall\u00e8les ex\u00e9cut\u00e9es par des agents dynamiquement instanci\u00e9s et sp\u00e9cifiques \u00e0 un domaine.\n\n---\n\n**\u7ffb\u8bd1\u6210\u4e2d\u6587\uff08\u7b80\u4f53\uff09**  \nKimi\u202fK2.5 \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u539f\u751f\u591a\u6a21\u6001\u4ee3\u7406\u6a21\u578b\uff0c\u57fa\u4e8e Kimi\u2011K2\u2011Base \u901a\u8fc7\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u7ea6 15\u202f\u4e07\u4ebf\u4e2a\u6df7\u5408\u89c6\u89c9\u4e0e\u6587\u672c token\u3002\u5b83\u65e0\u7f1d\u6574\u5408\u89c6\u89c9\u4e0e\u8bed\u8a00\u7406\u89e3\uff0c\u5e76\u5177\u5907\u5148\u8fdb\u7684\u4ee3\u7406\u80fd\u529b\uff0c\u63d0\u4f9b\u5373\u65f6\u4e0e\u601d\u8003\u4e24\u79cd\u6a21\u5f0f\uff0c\u4ee5\u53ca\u5bf9\u8bdd\u5f0f\u4e0e\u4ee3\u7406\u5f0f\u8303\u5f0f\u3002\n\n**\u4e3b\u8981\u7279\u70b9**  \n- **\u539f\u751f\u591a\u6a21\u6001** \u2013 \u9884\u8bad\u7ec3\u4e8e\u89c6\u89c9\u2011\u8bed\u8a00 token\uff0cK2.5 \u5728\u89c6\u89c9\u77e5\u8bc6\u3001\u8de8\u6a21\u6001\u63a8\u7406\u4ee5\u53ca\u4ee5\u89c6\u89c9\u8f93\u5165\u4e3a\u57fa\u7840\u7684\u4ee3\u7406\u5de5\u5177\u4f7f\u7528\u65b9\u9762\u8868\u73b0\u5353\u8d8a\u3002  \n- **\u89c6\u89c9\u7f16\u7801** \u2013 K2.5 \u80fd\u6839\u636e\u89c6\u89c9\u89c4\u8303\uff08UI \u8bbe\u8ba1\u3001\u89c6\u9891\u5de5\u4f5c\u6d41\uff09\u751f\u6210\u4ee3\u7801\uff0c\u5e76\u81ea\u4e3b\u7f16\u6392\u89c6\u89c9\u6570\u636e\u5904\u7406\u5de5\u5177\u3002  \n- **\u4ee3\u7406\u7fa4** \u2013 K2.5 \u4ece\u5355\u4e00\u4ee3\u7406\u6269\u5c55\u8f6c\u5411\u81ea\u6211\u9a71\u52a8\u3001\u534f\u540c\u7684\u7fa4\u4f53\u5f0f\u6267\u884c\u65b9\u6848\uff0c\u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5e76\u884c\u5b50\u4efb\u52a1\uff0c\u7531\u52a8\u6001\u5b9e\u4f8b\u5316\u7684\u9886\u57df\u4e13\u5c5e\u4ee3\u7406\u6267\u884c\u3002", "variable": "resultat_analyse", "model": "gpt-oss:latest", "mode": "text"}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_117f3ccc46d1_1769202475
status: success
started_at: 2026-04-02 12:50:51.796513
ended_at: 2026-04-02 12:50:59.445259
output_json:
  {"clicked_at": {"x": 32, "y": 1044}, "mode": "debug", "confidence": 0.9886456459911749, "method": "clip"}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_56bb4454972a_1769202487
status: success
started_at: 2026-04-02 12:51:00.260041
ended_at: 2026-04-02 12:51:04.819359
output_json:
  {"clicked_at": {"x": 993, "y": 190}, "mode": "debug", "confidence": 0.9879724107225903, "method": "clip"}


execution_id: exec_8a7b3b657e93_1775134168
step_id: step_76473bd27236_1769202498
status: success
started_at: 2026-04-02 12:51:14.832679
ended_at: 2026-04-02 12:51:15.637151
output_json:
  {"typed": "Voici le retour d'analyse IA :\n\n**Version corrig\u00e9e en anglais**  \nKimi\u202fK2.5 is an open\u2011source, nativ..."}


execution_id: exec_d235276a22ed_1776546269
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-18 21:04:30.996054
ended_at: 2026-04-18 21:04:36.318560
output_json:
  {"clicked_at": {"x": 1232, "y": 1050}, "mode": "debug", "confidence": 0.9971391466157797, "method": "clip"}


execution_id: exec_6b7e5bedab47_1776546710
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-18 21:11:52.714669
ended_at: 2026-04-18 21:12:02.218895
output_json:
  {"clicked_at": {"x": 1262, "y": 1049}, "mode": "debug", "confidence": 0.9300067168625259, "method": "clip"}


execution_id: exec_7bc4781331f1_1776547103
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-18 21:18:25.754304
ended_at: 2026-04-18 21:18:31.499462
output_json:
  {"clicked_at": {"x": 1262, "y": 1049}, "mode": "debug", "confidence": 0.9302564928987315, "method": "clip"}


execution_id: exec_5b496f997c8b_1776547175
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-18 21:19:36.954962
ended_at: 2026-04-18 21:19:41.809124
output_json:
  {"clicked_at": {"x": 1262, "y": 1050}, "mode": "debug", "confidence": 0.9312444847042943, "method": "clip"}


execution_id: exec_c9775f0cacaf_1776586273
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-19 08:11:15.590760
ended_at: 2026-04-19 08:11:21.369897
output_json:
  {"clicked_at": {"x": 1262, "y": 1050}, "mode": "debug", "confidence": 0.9329211612516598, "method": "clip"}


execution_id: exec_32b738fe0ff2_1776586770
step_id: step_43385710215a_1776523435
status: success
started_at: 2026-04-19 08:19:32.726452
ended_at: 2026-04-19 08:19:37.655764
output_json:
  {"clicked_at": {"x": 1292, "y": 1050}, "mode": "debug", "confidence": 0.865730008169337, "method": "clip"}


execution_id: exec_aab33bcbd0b6_1776592457
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-19 09:54:19.140287
ended_at: 2026-04-19 09:54:24.031014
output_json:
  {"clicked_at": {"x": 817, "y": 1050}, "mode": "debug", "confidence": 0.7137158343175537, "method": "clip"}


execution_id: exec_aab33bcbd0b6_1776592457
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-19 09:54:31.354947
ended_at: 2026-04-19 09:54:38.497282
output_json:
  {"clicked_at": {"x": 1255, "y": 403}, "mode": "debug", "confidence": 0.8921344905363964, "method": "clip"}


execution_id: exec_27e8cb15330f_1776611941
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-19 15:19:03.623638
ended_at: 2026-04-19 15:19:08.564074
output_json:
  {"clicked_at": {"x": 812, "y": 1048}, "mode": "debug", "confidence": 0.7307093913739847, "method": "clip"}


execution_id: exec_27e8cb15330f_1776611941
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-19 15:19:14.882958
ended_at: 2026-04-19 15:19:21.891445
output_json:
  {"clicked_at": {"x": 1255, "y": 403}, "mode": "debug", "confidence": 0.892299856461693, "method": "clip"}


execution_id: exec_4093cddbaed9_1776615931
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-19 16:25:33.264946
ended_at: 2026-04-19 16:25:38.918108
output_json:
  {"clicked_at": {"x": 815, "y": 1050}, "mode": "debug", "confidence": 0.7217548706593377, "method": "clip"}


execution_id: exec_6dafde425130_1776668920
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 07:08:42.067868
ended_at: 2026-04-20 07:08:47.574781
output_json:
  {"clicked_at": {"x": 812, "y": 1049}, "mode": "debug", "confidence": 0.7230043680598831, "method": "clip"}


execution_id: exec_3b029e7f3f8c_1776669055
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 07:10:57.493877
ended_at: 2026-04-20 07:11:02.290621
output_json:
  {"clicked_at": {"x": 811, "y": 1048}, "mode": "debug", "confidence": 0.7252905184837996, "method": "clip"}


execution_id: exec_ba377dc7f295_1776670869
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 07:41:11.670453
ended_at: 2026-04-20 07:41:17.176317
output_json:
  {"clicked_at": {"x": 813, "y": 1048}, "mode": "debug", "confidence": 0.7237220739635781, "method": "clip"}


execution_id: exec_89146441d69e_1776671194
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 07:46:35.983623
ended_at: 2026-04-20 07:46:41.457902
output_json:
  {"clicked_at": {"x": 811, "y": 1048}, "mode": "debug", "confidence": 0.7202358227753345, "method": "clip"}


execution_id: exec_51f17d938dd8_1776671932
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 07:58:53.858934
ended_at: 2026-04-20 07:58:59.415546
output_json:
  {"clicked_at": {"x": 812, "y": 1048}, "mode": "debug", "confidence": 0.7279082210924224, "method": "clip"}


execution_id: exec_79b535180e81_1776672129
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:02:11.814917
ended_at: 2026-04-20 08:02:17.198767
output_json:
  {"clicked_at": {"x": 813, "y": 1048}, "mode": "debug", "confidence": 0.7196641037564963, "method": "clip"}


execution_id: exec_eb92f1d67d90_1776672384
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:06:26.486138
ended_at: 2026-04-20 08:06:31.898826
output_json:
  {"clicked_at": {"x": 813, "y": 1050}, "mode": "debug", "confidence": 0.722844360763073, "method": "clip"}


execution_id: exec_eb92f1d67d90_1776672384
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:06:42.138443
ended_at: 2026-04-20 08:06:49.492102
output_json:
  {"clicked_at": {"x": 1256, "y": 403}, "mode": "debug", "confidence": 0.8824538611867991, "method": "clip"}


execution_id: exec_b0700995f623_1776673030
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:17:11.847581
ended_at: 2026-04-20 08:17:17.519192
output_json:
  {"clicked_at": {"x": 816, "y": 1050}, "mode": "debug", "confidence": 0.7166194398930846, "method": "clip"}


execution_id: exec_302d16ecdc12_1776673596
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:26:38.210364
ended_at: 2026-04-20 08:26:44.005773
output_json:
  {"clicked_at": {"x": 821, "y": 1051}, "mode": "debug", "confidence": 0.7052004617774069, "method": "clip"}


execution_id: exec_302d16ecdc12_1776673596
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:26:54.125632
ended_at: 2026-04-20 08:27:01.576347
output_json:
  {"clicked_at": {"x": 1255, "y": 402}, "mode": "debug", "confidence": 0.885893683646663, "method": "clip"}


execution_id: exec_4634f7e1cab3_1776673693
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:28:15.798062
ended_at: 2026-04-20 08:28:20.646871
output_json:
  {"clicked_at": {"x": 817, "y": 1050}, "mode": "debug", "confidence": 0.7157181663122817, "method": "clip"}


execution_id: exec_4634f7e1cab3_1776673693
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:28:29.799038
ended_at: 2026-04-20 08:28:36.521063
output_json:
  {"clicked_at": {"x": 1255, "y": 402}, "mode": "debug", "confidence": 0.8861066436459623, "method": "clip"}


execution_id: exec_c5fc9dd7e544_1776673874
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:31:16.193629
ended_at: 2026-04-20 08:31:22.239197
output_json:
  {"clicked_at": {"x": 818, "y": 1050}, "mode": "debug", "confidence": 0.7149588629539693, "method": "clip"}


execution_id: exec_c5fc9dd7e544_1776673874
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:31:32.777319
ended_at: 2026-04-20 08:31:39.983603
output_json:
  {"clicked_at": {"x": 1256, "y": 403}, "mode": "debug", "confidence": 0.8823061389154616, "method": "clip"}


execution_id: exec_9289f6f4152e_1776674075
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:34:37.023837
ended_at: 2026-04-20 08:34:43.339895
output_json:
  {"clicked_at": {"x": 815, "y": 1050}, "mode": "debug", "confidence": 0.7190576821046983, "method": "clip"}


execution_id: exec_9289f6f4152e_1776674075
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:34:53.738538
ended_at: 2026-04-20 08:35:00.761963
output_json:
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execution_id: exec_a8f96b8fc463_1776674317
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:38:39.230694
ended_at: 2026-04-20 08:38:45.249740
output_json:
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execution_id: exec_a8f96b8fc463_1776674317
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:38:55.652783
ended_at: 2026-04-20 08:39:02.812608
output_json:
  {"clicked_at": {"x": 1256, "y": 403}, "mode": "debug", "confidence": 0.8821484852582293, "method": "clip"}


execution_id: exec_ff0ff3e614b6_1776675184
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:53:05.834825
ended_at: 2026-04-20 08:53:11.709037
output_json:
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execution_id: exec_ff0ff3e614b6_1776675184
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 08:53:22.238788
ended_at: 2026-04-20 08:53:29.556403
output_json:
  {"clicked_at": {"x": 1255, "y": 403}, "mode": "debug", "confidence": 0.8983395525010891, "method": "clip"}


execution_id: exec_f375d31d2477_1776675467
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 08:57:49.240583
ended_at: 2026-04-20 08:57:55.116534
output_json:
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execution_id: exec_d00dbbc55e11_1776675886
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 09:04:48.224490
ended_at: 2026-04-20 09:04:54.040406
output_json:
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execution_id: exec_d00dbbc55e11_1776675886
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 09:05:04.738874
ended_at: 2026-04-20 09:05:11.784401
output_json:
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execution_id: exec_b6c6b18f42e3_1776678317
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 09:45:19.673659
ended_at: 2026-04-20 09:45:24.419742
output_json:
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execution_id: exec_b6c6b18f42e3_1776678317
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 09:45:33.273869
ended_at: 2026-04-20 09:45:40.275253
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execution_id: exec_54a8d01b8eda_1776689605
step_id: step_d1031d09c146_1776591746
status: success
started_at: 2026-04-20 12:53:27.045270
ended_at: 2026-04-20 12:53:33.083841
output_json:
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execution_id: exec_54a8d01b8eda_1776689605
step_id: step_3284c3c5563f_1776591977
status: success
started_at: 2026-04-20 12:53:43.312874
ended_at: 2026-04-20 12:53:50.644835
output_json:
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execution_id: exec_e99a2bee7071_1776757563
step_id: step_e2d75795e4a0_1776752830
status: success
started_at: 2026-04-21 07:46:05.188193
ended_at: 2026-04-21 07:46:12.970770
output_json:
  {"clicked_at": {"x": 472, "y": 175}, "mode": "debug", "confidence": 0.6016059915288193, "method": "clip"}


execution_id: exec_e99a2bee7071_1776757563
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 07:46:12.977239
ended_at: 2026-04-21 07:46:19.308703
output_json:
  {"clicked_at": {"x": 160, "y": 745}, "mode": "debug", "confidence": 0.9434423441986081, "method": "clip"}


execution_id: exec_33a42ee2e527_1776759503
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 08:20:01.320057
ended_at: 2026-04-21 08:20:49.585445
output_json:
  {"clicked_at": {"x": 117, "y": 763}, "mode": "debug", "confidence": 0.6257186329970869, "method": "clip"}


execution_id: exec_924329ef0cf2_1776760356
step_id: step_e2d75795e4a0_1776752830
status: success
started_at: 2026-04-21 08:32:38.073000
ended_at: 2026-04-21 08:32:45.617457
output_json:
  {"clicked_at": {"x": 419, "y": 269}, "mode": "debug", "confidence": 0.9487815645678005, "method": "clip"}


execution_id: exec_924329ef0cf2_1776760356
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 08:32:45.624758
ended_at: 2026-04-21 08:32:51.394189
output_json:
  {"clicked_at": {"x": 163, "y": 677}, "mode": "debug", "confidence": 0.6805845581659142, "method": "clip"}


execution_id: exec_6eb93da83e55_1776760443
step_id: step_e2d75795e4a0_1776752830
status: success
started_at: 2026-04-21 08:34:05.661886
ended_at: 2026-04-21 08:34:09.727315
output_json:
  {"clicked_at": {"x": 166, "y": 332}, "mode": "debug", "confidence": 0.25397021741655895, "method": "clip"}


execution_id: exec_6eb93da83e55_1776760443
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 08:34:09.732969
ended_at: 2026-04-21 08:34:58.007006
output_json:
  {"clicked_at": {"x": 238, "y": 616}, "mode": "debug", "confidence": 0.4622884590990779, "method": "clip"}


execution_id: exec_9e55929f7761_1776760847
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 08:41:22.610476
ended_at: 2026-04-21 08:42:12.292785
output_json:
  {"clicked_at": {"x": 180, "y": 718}, "mode": "debug", "confidence": 0.6374394285298007, "method": "clip"}


execution_id: exec_5f1e1ea831f0_1776761731
step_id: step_45c11ef24a74_1776753962
status: success
started_at: 2026-04-21 08:56:08.348730
ended_at: 2026-04-21 08:57:05.137160
output_json:
  {"clicked_at": {"x": 179, "y": 720}, "mode": "debug", "confidence": 0.6627258991070754, "method": "clip"}


execution_id: exec_e17ac957a37e_1776773683
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 12:14:45.680720
ended_at: 2026-04-21 12:14:50.764683
output_json:
  {"clicked_at": {"x": 169, "y": 749.0}, "mode": "debug", "confidence": 0.9999994039535522, "method": "zoned_template"}


execution_id: exec_f1863f2b7cdf_1776774138
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 12:22:20.797499
ended_at: 2026-04-21 12:22:25.160698
output_json:
  {"clicked_at": {"x": 169, "y": 749.0}, "mode": "debug", "confidence": 0.8951815366744995, "method": "zoned_template"}


execution_id: exec_f1863f2b7cdf_1776774138
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-21 12:22:25.166263
ended_at: 2026-04-21 12:23:15.539549
output_json:
  {"clicked_at": {"x": 422.0, "y": 270.0}, "mode": "debug", "confidence": 0.999996542930603, "method": "zoned_template"}


execution_id: exec_6f846dbde75f_1776774222
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 12:23:44.243907
ended_at: 2026-04-21 12:24:00.279959
output_json:
  {"clicked_at": {"x": 111, "y": 819}, "mode": "debug", "confidence": 0.5980860206889803, "method": "clip"}


execution_id: exec_b01080fe5a4c_1776781208
step_id: step_1f657c041ad7_1776765219
status: error
started_at: 2026-04-21 14:20:10.772120
ended_at: 2026-04-21 14:20:14.659033
output_json: {}
error_message:
  Erreur vision: cannot access local variable 'result' where it is not associated with a value. Ancre introuvable à l'écran.


execution_id: exec_539176d6fb67_1776788649
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 16:24:11.147538
ended_at: 2026-04-21 16:24:13.609311
output_json:
  {"clicked_at": {"x": 166, "y": 785}, "mode": "debug", "confidence": 0.95, "method": "grounding_ocr"}


execution_id: exec_13b5af2d4b88_1776788815
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 16:26:57.556085
ended_at: 2026-04-21 16:27:00.012268
output_json:
  {"clicked_at": {"x": 165, "y": 785}, "mode": "debug", "confidence": 0.95, "method": "grounding_ocr"}


execution_id: exec_7d03492a1e6d_1776789662
step_id: step_1f657c041ad7_1776765219
status: error
started_at: 2026-04-21 16:41:04.136957
ended_at: 2026-04-21 16:41:08.181656
output_json: {}
error_message:
  Erreur vision: PyAutoGUI fail-safe triggered from mouse moving to a corner of the screen. To disable this fail-safe, set pyautogui.FAILSAFE to False. DISABLING FAIL-SAFE IS NOT RECOMMENDED.. Ancre introuvable à l'écran.


execution_id: exec_96d2a2a3c065_1776789711
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 16:41:53.462572
ended_at: 2026-04-21 16:41:57.592506
output_json:
  {"clicked_at": {"x": 168, "y": 751}, "mode": "debug", "confidence": 0.9455311552272624, "method": "clip"}


execution_id: exec_6dad942001bc_1776789745
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 16:42:26.909106
ended_at: 2026-04-21 16:42:31.047070
output_json:
  {"clicked_at": {"x": 160, "y": 732}, "mode": "debug", "confidence": 0.8023550198974435, "method": "clip"}


execution_id: exec_6dad942001bc_1776789745
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-21 16:42:31.052590
ended_at: 2026-04-21 16:43:18.496607
output_json:
  {"clicked_at": {"x": 418, "y": 269}, "mode": "debug", "confidence": 0.9606024161609176, "method": "clip"}


execution_id: exec_6dad942001bc_1776789745
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 16:43:38.777938
ended_at: 2026-04-21 16:44:07.460607
output_json:
  {"clicked_at": {"x": 794, "y": 1050}, "mode": "debug", "confidence": 0.9652952218474116, "method": "clip"}


execution_id: exec_6dad942001bc_1776789745
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 16:44:10.012770
ended_at: 2026-04-21 16:44:38.200488
output_json:
  {"clicked_at": {"x": 1292, "y": 490}, "mode": "debug", "confidence": 0.9924361908111119, "method": "clip"}


execution_id: exec_3fa282122261_1776790585
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 16:56:27.023254
ended_at: 2026-04-21 16:56:32.635191
output_json:
  {"clicked_at": {"x": 165, "y": 679}, "mode": "debug", "confidence": 0.6422560969067166, "method": "clip"}


execution_id: exec_3fa282122261_1776790585
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 16:56:58.317283
ended_at: 2026-04-21 16:57:08.338909
output_json:
  {"clicked_at": {"x": 810, "y": 1051}, "mode": "debug", "confidence": 0.8949643565140621, "method": "clip"}


execution_id: exec_3fa282122261_1776790585
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 16:57:09.276083
ended_at: 2026-04-21 16:57:16.505464
output_json:
  {"clicked_at": {"x": 1303, "y": 490}, "mode": "debug", "confidence": 0.8535022480060229, "method": "clip"}


execution_id: exec_d6b5a0b2c971_1776791890
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:18:12.702202
ended_at: 2026-04-21 17:18:18.324370
output_json:
  {"clicked_at": {"x": 169, "y": 749.0}, "mode": "debug", "confidence": 0.8880746960639954, "method": "clip"}


execution_id: exec_d6b5a0b2c971_1776791890
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:18:46.846481
ended_at: 2026-04-21 17:18:54.726074
output_json:
  {"clicked_at": {"x": 794, "y": 1050}, "mode": "debug", "confidence": 0.9682492931716712, "method": "clip"}


execution_id: exec_d6b5a0b2c971_1776791890
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 17:19:05.558092
ended_at: 2026-04-21 17:19:24.820934
output_json:
  {"clicked_at": {"x": 1292, "y": 490}, "mode": "debug", "confidence": 0.9923956921780098, "method": "clip"}


execution_id: exec_ee53cc12d489_1776792168
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-21 17:22:57.186336
ended_at: 2026-04-21 17:23:08.998088
output_json:
  {"clicked_at": {"x": 422, "y": 270}, "mode": "debug", "confidence": 0.9999986886978149, "method": "template"}


execution_id: exec_ee53cc12d489_1776792168
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:23:20.362136
ended_at: 2026-04-21 17:23:28.626898
output_json:
  {"clicked_at": {"x": 794, "y": 1051}, "mode": "debug", "confidence": 0.9473874938491446, "method": "clip"}


execution_id: exec_ee53cc12d489_1776792168
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 17:23:29.712400
ended_at: 2026-04-21 17:23:32.802928
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999962449073792, "method": "template"}


execution_id: exec_de0cc9c1e53e_1776793787
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:49:48.900864
ended_at: 2026-04-21 17:49:49.431525
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8625848293304443, "method": "template"}


execution_id: exec_de0cc9c1e53e_1776793787
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:50:01.781683
ended_at: 2026-04-21 17:50:06.328264
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9504931246278763, "method": "clip"}


execution_id: exec_de0cc9c1e53e_1776793787
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 17:50:07.386375
ended_at: 2026-04-21 17:50:08.706683
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999912977218628, "method": "template"}


execution_id: exec_e36826fd3d41_1776794023
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:53:45.271256
ended_at: 2026-04-21 17:53:45.782975
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8625852465629578, "method": "template"}


execution_id: exec_e36826fd3d41_1776794023
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:53:57.856591
ended_at: 2026-04-21 17:54:00.733187
output_json:
  {"clicked_at": {"x": 794, "y": 1051}, "mode": "debug", "confidence": 0.9474534195295293, "method": "clip"}


execution_id: exec_b15dd3c9f1c1_1776794085
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:54:47.728156
ended_at: 2026-04-21 17:54:48.214199
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8625844120979309, "method": "template"}


execution_id: exec_b15dd3c9f1c1_1776794085
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:54:59.755053
ended_at: 2026-04-21 17:55:02.496411
output_json:
  {"clicked_at": {"x": 794, "y": 1051}, "mode": "debug", "confidence": 0.9474174814910711, "method": "clip"}


execution_id: exec_b15dd3c9f1c1_1776794085
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 17:55:03.407675
ended_at: 2026-04-21 17:55:04.678096
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999945759773254, "method": "template"}


execution_id: exec_47e1f271cdb9_1776794140
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:55:54.695036
ended_at: 2026-04-21 17:55:57.590398
output_json:
  {"clicked_at": {"x": 794, "y": 1051}, "mode": "debug", "confidence": 0.9474224303357113, "method": "clip"}


execution_id: exec_07d2fd2cabf9_1776794204
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:56:46.157207
ended_at: 2026-04-21 17:56:46.667345
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.9534551501274109, "method": "template"}


execution_id: exec_07d2fd2cabf9_1776794204
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:56:58.659320
ended_at: 2026-04-21 17:57:01.432436
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9461726241352462, "method": "clip"}


execution_id: exec_a65d362cfa54_1776794257
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 17:57:39.344142
ended_at: 2026-04-21 17:57:39.862062
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.835942804813385, "method": "template"}


execution_id: exec_850cddeaf2fd_1776794296
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 17:58:31.034403
ended_at: 2026-04-21 17:58:34.015085
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9503063033697577, "method": "clip"}


execution_id: exec_850cddeaf2fd_1776794296
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 17:58:34.986784
ended_at: 2026-04-21 17:58:36.273128
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999979138374329, "method": "template"}


execution_id: exec_9a825caaf243_1776794397
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:00:11.865952
ended_at: 2026-04-21 18:00:14.748244
output_json:
  {"clicked_at": {"x": 791, "y": 1051}, "mode": "debug", "confidence": 0.954466623075035, "method": "clip"}


execution_id: exec_a3d7d1c7db31_1776794455
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:01:09.452981
ended_at: 2026-04-21 18:01:12.257549
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9457865544843228, "method": "clip"}


execution_id: exec_d0a94fef2916_1776794490
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 18:01:32.385554
ended_at: 2026-04-21 18:01:32.887713
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8625839352607727, "method": "template"}


execution_id: exec_9d45bbdc0a8e_1776794521
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:02:13.714968
ended_at: 2026-04-21 18:02:16.117951
output_json:
  {"clicked_at": {"x": 817, "y": 1051}, "mode": "debug", "confidence": 0.8952072800382355, "method": "clip"}


execution_id: exec_9d45bbdc0a8e_1776794521
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 18:02:16.819739
ended_at: 2026-04-21 18:02:17.852574
output_json:
  {"clicked_at": {"x": 1323, "y": 490}, "mode": "debug", "confidence": 0.9750422239303589, "method": "template"}


execution_id: exec_a0e017f5067f_1776794663
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:04:37.671559
ended_at: 2026-04-21 18:04:40.355852
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9504880945971699, "method": "clip"}


execution_id: exec_283f0ab59d97_1776794695
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:05:09.840292
ended_at: 2026-04-21 18:05:12.663968
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9504314031922673, "method": "clip"}


execution_id: exec_7e36ebadab86_1776794749
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 18:05:50.920227
ended_at: 2026-04-21 18:05:51.430779
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8625848889350891, "method": "template"}


execution_id: exec_2bd891cfffbf_1776794783
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-21 18:06:37.151909
ended_at: 2026-04-21 18:06:39.965290
output_json:
  {"clicked_at": {"x": 793, "y": 1051}, "mode": "debug", "confidence": 0.9456610253737876, "method": "clip"}


execution_id: exec_2bd891cfffbf_1776794783
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 18:06:40.910783
ended_at: 2026-04-21 18:06:42.141540
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999986886978149, "method": "template"}


execution_id: exec_446d7616fc78_1776794826
step_id: step_472e4a131027_1776784823
status: success
started_at: 2026-04-21 18:07:24.264607
ended_at: 2026-04-21 18:07:25.564327
output_json:
  {"clicked_at": {"x": 1293, "y": 490}, "mode": "debug", "confidence": 0.9999929666519165, "method": "template"}


execution_id: exec_4950caacded9_1776794899
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 18:08:20.964304
ended_at: 2026-04-21 18:08:21.469805
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.9534547924995422, "method": "template"}


execution_id: exec_e7f6c9ad575f_1776795013
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-21 18:10:15.457751
ended_at: 2026-04-21 18:10:15.970978
output_json:
  {"clicked_at": {"x": 169, "y": 749}, "mode": "debug", "confidence": 0.8695094585418701, "method": "template"}


execution_id: exec_b4d0418827a2_1776860106
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:15:08.396545
ended_at: 2026-04-22 12:15:12.116336
output_json:
  {"clicked_at": {"x": 162, "y": 748}, "mode": "debug", "confidence": 0.8881926833808416, "method": "clip"}


execution_id: exec_b4d0418827a2_1776860106
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-22 12:15:16.198028
ended_at: 2026-04-22 12:15:18.952358
output_json:
  {"clicked_at": {"x": 792, "y": 1051}, "mode": "debug", "confidence": 0.9504448955099267, "method": "clip"}


execution_id: exec_e08183381171_1776860440
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:20:42.473354
ended_at: 2026-04-22 12:20:46.183026
output_json:
  {"clicked_at": {"x": 226, "y": 775}, "mode": "debug", "confidence": 0.5963259411284092, "method": "clip"}


execution_id: exec_5794674774f4_1776860844
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:27:26.629237
ended_at: 2026-04-22 12:27:29.048329
output_json:
  {"clicked_at": {"x": 163, "y": 613}, "mode": "debug", "confidence": 0.4821838879325259, "method": "clip"}


execution_id: exec_5794674774f4_1776860844
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-22 12:27:48.505956
ended_at: 2026-04-22 12:27:50.588902
output_json:
  {"clicked_at": {"x": 818, "y": 1050}, "mode": "debug", "confidence": 0.8992543291734268, "method": "clip"}


execution_id: exec_503c45a08b69_1776860891
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:28:12.907616
ended_at: 2026-04-22 12:28:15.186645
output_json:
  {"clicked_at": {"x": 163, "y": 613}, "mode": "debug", "confidence": 0.48013718341664335, "method": "clip"}


execution_id: exec_4f9e547c16d4_1776862161
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:49:41.864963
ended_at: 2026-04-22 12:49:41.864975
output_json:
  {"change_level": "major", "matches_expected": true, "detail": "Changement majeur d\u00e9tect\u00e9 (distance=28)", "mode": "verified"}


execution_id: exec_4f9e547c16d4_1776862161
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-22 12:50:02.046339
ended_at: 2026-04-22 12:50:02.046357
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=12) | VLM: matches=True, \u00e9tat='L'\u00e9cran devrait changer apr\u00e8s le clic sur 'CR_patient demo'.'", "mode": "verified"}


execution_id: exec_4f9e547c16d4_1776862161
step_id: step_b08e9c1f2d86_1776773949
status: success
started_at: 2026-04-22 12:50:03.421138
ended_at: 2026-04-22 12:50:03.421144
output_json:
  {"change_level": "n/a", "matches_expected": true, "detail": "Action 'wait' \u2014 pas de changement attendu", "mode": "verified"}


execution_id: exec_081c2988d7c8_1776862471
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 12:54:34.455728
ended_at: 2026-04-22 12:54:34.455740
output_json:
  {"change_level": "major", "matches_expected": true, "detail": "Changement majeur d\u00e9tect\u00e9 (distance=18)", "mode": "verified"}


execution_id: exec_081c2988d7c8_1776862471
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-22 12:54:44.118064
ended_at: 2026-04-22 12:54:44.118079
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=14) | VLM: matches=True, \u00e9tat='L'\u00e9cran devrait changer apr\u00e8s le clic sur 'CR_patient demo'.'", "mode": "verified"}


execution_id: exec_081c2988d7c8_1776862471
step_id: step_d240b89333ef_1776774050
status: success
started_at: 2026-04-22 12:54:58.938002
ended_at: 2026-04-22 12:54:58.938015
output_json:
  {"change_level": "same", "matches_expected": true, "detail": "Aucun changement d\u00e9tect\u00e9 (distance=0) | VLM: matches=True, \u00e9tat='Le texte est s\u00e9lectionn\u00e9, ce qui sugg\u00e8re que la commande Ctrl+A a \u00e9t\u00e9 ex\u00e9cut\u00e9e. '", "mode": "verified"}


execution_id: exec_916b010151aa_1776863133
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 13:05:35.956695
ended_at: 2026-04-22 13:05:35.956704
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=10)", "mode": "verified"}


execution_id: exec_916b010151aa_1776863133
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-22 13:05:37.012967
ended_at: 2026-04-22 13:05:37.012973
output_json:
  {"change_level": "major", "matches_expected": true, "detail": "Changement majeur d\u00e9tect\u00e9 (distance=24)", "mode": "verified"}


execution_id: exec_916b010151aa_1776863133
step_id: step_d240b89333ef_1776774050
status: success
started_at: 2026-04-22 13:05:38.774955
ended_at: 2026-04-22 13:05:38.774965
output_json:
  {"change_level": "same", "matches_expected": true, "detail": "Changement minimal accept\u00e9 (confiance=0.90)", "mode": "verified"}


execution_id: exec_916b010151aa_1776863133
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-22 13:05:54.277109
ended_at: 2026-04-22 13:05:54.277116
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=12)", "mode": "verified"}


execution_id: exec_71e9723b409d_1776863308
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-22 13:08:32.511442
ended_at: 2026-04-22 13:08:32.511448
output_json:
  {"change_level": "major", "matches_expected": true, "detail": "Changement majeur d\u00e9tect\u00e9 (distance=30)", "mode": "verified"}


execution_id: exec_71e9723b409d_1776863308
step_id: step_4c1ba6711cb4_1776784685
status: success
started_at: 2026-04-22 13:08:53.194021
ended_at: 2026-04-22 13:08:53.194028
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=14)", "mode": "verified"}


execution_id: exec_d9ec004ff805_1776865197
step_id: step_1f657c041ad7_1776765219
status: success
started_at: 2026-04-22 13:40:00.343196
ended_at: 2026-04-22 13:40:00.343206
output_json:
  {"change_level": "minor", "matches_expected": true, "detail": "Changement mineur (distance=6)", "mode": "verified"}


execution_id: exec_d9ec004ff805_1776865197
step_id: step_c8c9d97853e0_1776773741
status: success
started_at: 2026-04-22 13:40:01.525771
ended_at: 2026-04-22 13:40:01.525778
output_json:
  {"change_level": "major", "matches_expected": true, "detail": "Changement majeur d\u00e9tect\u00e9 (distance=34)", "mode": "verified"}


