diff --git a/MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb b/MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb
index a58e219e7a..d8c2077c7b 100644
--- a/MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb
+++ b/MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb
@@ -5,17 +5,18 @@
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-     "end_time": "2026-09-23T14:36:34.272624+00:00",
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      "exception": false,
-     "start_time": "2026-09-23T14:36:34.266511+00:00",
+     "start_time": "2026-09-25T04:29:14.533884",
      "status": "completed"
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     "tags": []
    },
    "source": [
-    "**Navigation** : [Index](../../../../README.md) | [<< Lab5](../Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | [Lab7 >>](../Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb)\n",
-    "# Lab 6 - Anatomie de votre premier Agent d'IA"
+    "# Lab 6 - Anatomie de votre premier Agent d'IA\n",
+    "\n",
+    "**Navigation** : [Lab 5 <<](../Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | [Index](../../README.md) | [Lab 7 >>](../Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb)\n"
    ]
   },
   {
@@ -23,19 +24,15 @@
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-     "end_time": "2026-09-23T14:36:34.281592+00:00",
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+     "start_time": "2026-09-25T04:29:14.546155",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## Lab 6 - Anatomie de votre premier Agent d'IA\n",
-    "\n",
-    "**Navigation** : [Lab 5 <<](../Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | [Index](../../README.md) | [>> Lab 7](../Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb)\n",
-    "\n",
     "## Objectifs d'apprentissage\n",
     "\n",
     "A la fin de ce laboratoire, vous saurez :\n",
@@ -59,10 +56,10 @@
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@@ -76,10 +73,10 @@
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@@ -93,10 +90,10 @@
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@@ -140,10 +137,10 @@
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@@ -177,16 +174,16 @@
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@@ -207,10 +204,10 @@
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@@ -224,10 +221,10 @@
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@@ -242,16 +239,16 @@
    "id": "cdd296c8",
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-     "end_time": "2026-09-23T14:36:39.012427+00:00",
+     "duration": 0.123831,
+     "end_time": "2026-09-25T04:29:16.986933",
      "exception": false,
-     "start_time": "2026-09-23T14:36:38.876333+00:00",
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@@ -280,21 +277,30 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "id": "37a3f099-783f-4cea-ba61-137b35bd32a1",
+   "metadata": {
+    "papermill": {
+     "duration": 0.002585,
+     "end_time": "2026-09-25T04:29:16.995824",
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+     "start_time": "2026-09-25T04:29:16.993239",
+     "status": "completed"
+    },
+    "tags": []
+   },
    "source": [
     "**Lecture ancrée** : Le template, verbatim du code : `(\"system\", \"You are a helpful assistant. Use the tools available to help the user.\")` puis `MessagesPlaceholder(\"messages\")` — la sortie confirme « Prompt REACT configure avec ChatPromptTemplate ». Structure fixe (le rôle système, qui ordonne d'utiliser les outils) + slot variable (l'historique des messages) : LangGraph injectera la conversation dans le slot à chaque tour de la boucle REACT."
-   ],
-   "id": "37a3f099-783f-4cea-ba61-137b35bd32a1"
+   ]
   },
   {
    "cell_type": "markdown",
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+     "start_time": "2026-09-25T04:29:16.999598",
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     },
     "tags": []
@@ -308,10 +314,10 @@
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@@ -328,16 +334,16 @@
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@@ -363,7 +369,16 @@
   {
    "cell_type": "markdown",
    "id": "3604fb2c-b426-40e2-89a6-6f59ca2a83c0",
-   "metadata": {},
+   "metadata": {
+    "papermill": {
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+     "status": "completed"
+    },
+    "tags": []
+   },
    "source": [
     "**Lecture ancree** : la cellule imprime « Agent REACT cree avec LangGraph » — et rien d'autre. Plus de `LangGraphDeprecatedSinceV10` : le filtre `warnings.filterwarnings('ignore', category=DeprecationWarning)` pose plus haut dans le notebook etouffe l'avertissement avant l'impression. L'appel `create_react_agent(model=llm, tools=tools, prompt=prompt)` porte trois arguments nommes, trois roles — le modele decide, la liste d'outils agit, le prompt cadre. La boucle REACT n'est pas ecrite a la main : elle est COMPILEE par cet appel, c'est ce que « prebuilt » annonce dans `from langgraph.prebuilt import create_react_agent`. L'avertissement reste reel meme silencieux : cet import migre en v1.0 (`from langchain.agents import create_agent`) et disparaitra en v2.0 — le filtre ne change pas l'horizon de migration, il l'ote seulement de la sortie.\n"
    ]
@@ -373,10 +388,10 @@
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-     "end_time": "2026-09-23T14:36:39.522045+00:00",
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      "exception": false,
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+     "start_time": "2026-09-25T04:29:17.636168",
      "status": "completed"
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     "tags": []
@@ -391,40 +406,49 @@
    "id": "926d2c0e",
    "metadata": {
     "execution": {
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+     "iopub.execute_input": "2026-09-25T04:29:17.651734Z",
+     "iopub.status.busy": "2026-09-25T04:29:17.651734Z",
+     "iopub.status.idle": "2026-09-25T04:29:20.868929Z",
+     "shell.execute_reply": "2026-09-25T04:29:20.867922Z"
     },
     "papermill": {
-     "duration": 5.287714,
-     "end_time": "2026-09-23T14:36:44.814310+00:00",
+     "duration": 3.221938,
+     "end_time": "2026-09-25T04:29:20.868929",
      "exception": false,
-     "start_time": "2026-09-23T14:36:39.526596+00:00",
+     "start_time": "2026-09-25T04:29:17.646991",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "La racine carrée de 256 est 16, car 16 × 16 = 256.\n"
+     ]
+    }
+   ],
    "source": [
-    "result = graph.invoke({\"messages\": [(\"user\", \"Quelle est la racine carree de 256 ?\")]})"
+    "result = graph.invoke({\"messages\": [(\"user\", \"Quelle est la racine carree de 256 ?\")]})\n",
+    "print(result[\"messages\"][-1].content)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "479cf1ff",
+   "id": "42149a20",
    "metadata": {
     "papermill": {
-     "duration": 0.003995,
-     "end_time": "2026-09-23T14:36:44.823195+00:00",
+     "duration": 0.003455,
+     "end_time": "2026-09-25T04:29:20.876255",
      "exception": false,
-     "start_time": "2026-09-23T14:36:44.819200+00:00",
+     "start_time": "2026-09-25T04:29:20.872800",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## Conclusion"
+    "**Lecture** : verbatim de la sortie — « La racine carrée de 256 est 16. » Le climax du lab : un seul `graph.invoke` et le graphe orchestre la boucle jusqu'à la réponse finale en langage naturel. La trajectoire complète (messages successifs de l'agent, appel de l'outil `calculer_racine_carree`) est conservée dans `result[\"messages\"]` — on affiche ici le dernier message, celui de la réponse.\n"
    ]
   },
   {
@@ -432,10 +456,10 @@
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+     "start_time": "2026-09-25T04:29:20.879510",
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@@ -460,16 +484,16 @@
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+     "iopub.execute_input": "2026-09-25T04:29:20.899109Z",
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@@ -511,10 +535,10 @@
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      "exception": false,
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@@ -539,16 +563,16 @@
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+     "start_time": "2026-09-25T04:29:20.925255",
      "status": "completed"
     },
     "tags": []
@@ -595,10 +619,10 @@
    "id": "f595bfe3",
    "metadata": {
     "papermill": {
-     "duration": 0.007921,
-     "end_time": "2026-09-23T14:36:44.967598+00:00",
+     "duration": 0.005084,
+     "end_time": "2026-09-25T04:29:20.953810",
      "exception": false,
-     "start_time": "2026-09-23T14:36:44.959677+00:00",
+     "start_time": "2026-09-25T04:29:20.948726",
      "status": "completed"
     },
     "tags": []
@@ -622,16 +646,16 @@
    "id": "598cb3f2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-23T14:36:44.992956Z",
-     "iopub.status.busy": "2026-09-23T14:36:44.992578Z",
-     "iopub.status.idle": "2026-09-23T14:36:45.015283Z",
-     "shell.execute_reply": "2026-09-23T14:36:45.007676Z"
+     "iopub.execute_input": "2026-09-25T04:29:20.966287Z",
+     "iopub.status.busy": "2026-09-25T04:29:20.966287Z",
+     "iopub.status.idle": "2026-09-25T04:29:20.970809Z",
+     "shell.execute_reply": "2026-09-25T04:29:20.970284Z"
     },
     "papermill": {
-     "duration": 0.0446,
-     "end_time": "2026-09-23T14:36:45.019111+00:00",
+     "duration": 0.012431,
+     "end_time": "2026-09-25T04:29:20.971836",
      "exception": false,
-     "start_time": "2026-09-23T14:36:44.974511+00:00",
+     "start_time": "2026-09-25T04:29:20.959405",
      "status": "completed"
     },
     "tags": []
@@ -668,45 +692,25 @@
     "print(\"Exercice 3 a completer : personnalisation du prompt systeme\")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "cc215b72",
-   "metadata": {
-    "papermill": {
-     "duration": 0.003759,
-     "end_time": "2026-09-23T14:36:45.027779+00:00",
-     "exception": false,
-     "start_time": "2026-09-23T14:36:45.024020+00:00",
-     "status": "completed"
-    },
-    "tags": []
-   },
-   "source": [
-    "Felicitations ! Vous avez assemble les 4 composants fondamentaux d'un agent : un LLM pour raisonner, un Outil pour agir, un Prompt pour guider, et un Graphe LangGraph pour orchestrer.\n",
-    "\n",
-    "Maintenant que nous savons construire un agent et lui donner un outil simple, nous sommes prets pour la prochaine étape : lui donner des outils puissants pour interagir avec des DataFrames Pandas et devenir un veritable assistant d'analyse de données. C'est l'objet du Lab 7 !"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "5dbb2a89",
    "metadata": {
     "papermill": {
-     "duration": 0.004677,
-     "end_time": "2026-09-23T14:36:45.041274+00:00",
+     "duration": 0.005405,
+     "end_time": "2026-09-25T04:29:20.982504",
      "exception": false,
-     "start_time": "2026-09-23T14:36:45.036597+00:00",
+     "start_time": "2026-09-25T04:29:20.977099",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## Exemple guidé\n",
+    "### Exercice 4 : Étendre l'agent avec un outil de puissance\n",
     "\n",
-    "À vous d'étendre l'agent en lui ajoutant un nouvel outil mathématique !\n",
+    "L'agent ne vaut que par ses outils. À vous d'étendre l'agent en lui ajoutant un nouvel outil mathématique : `calculer_puissance`, puis de reconstruire l'agent avec les DEUX outils et de le tester sur une question qui exige la puissance.\n",
     "\n",
-    "***\n",
-    "**Retour au sommaire** : [Index ML](../../../../README.md)\n"
+    "**Objectif** : un agent multi-outils qui choisit seul entre racine carrée et puissance.\n"
    ]
   },
   {
@@ -715,23 +719,23 @@
    "id": "20603f66",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-23T14:36:45.056949Z",
-     "iopub.status.busy": "2026-09-23T14:36:45.056596Z",
-     "iopub.status.idle": "2026-09-23T14:36:45.072042Z",
-     "shell.execute_reply": "2026-09-23T14:36:45.067297Z"
+     "iopub.execute_input": "2026-09-25T04:29:20.992554Z",
+     "iopub.status.busy": "2026-09-25T04:29:20.991995Z",
+     "iopub.status.idle": "2026-09-25T04:29:20.999199Z",
+     "shell.execute_reply": "2026-09-25T04:29:20.999199Z"
     },
     "papermill": {
-     "duration": 0.027893,
-     "end_time": "2026-09-23T14:36:45.073910+00:00",
+     "duration": 0.014544,
+     "end_time": "2026-09-25T04:29:21.000452",
      "exception": false,
-     "start_time": "2026-09-23T14:36:45.046017+00:00",
+     "start_time": "2026-09-25T04:29:20.985908",
      "status": "completed"
     },
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# Exercice : Ajoutez un nouvel outil a l'agent\n",
+    "# Exercice 4 : Ajoutez un nouvel outil a l'agent\n",
     "# Creez un outil qui calcule la puissance d'un nombre\n",
     "\n",
     "# Exercice: Creez un outil 'calculer_puissance' avec le decorateur @tool\n",
@@ -754,15 +758,36 @@
     "# result_exo = graph_exo.invoke({\"messages\": [(\"user\", \"Quelle est la puissance de 5 eleve au carre ?\")]})"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "cc215b72",
+   "metadata": {
+    "papermill": {
+     "duration": 0.005287,
+     "end_time": "2026-09-25T04:29:21.009852",
+     "exception": false,
+     "start_time": "2026-09-25T04:29:21.004565",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "Felicitations ! Vous avez assemble les 4 composants fondamentaux d'un agent : un LLM pour raisonner, un Outil pour agir, un Prompt pour guider, et un Graphe LangGraph pour orchestrer.\n",
+    "\n",
+    "Maintenant que nous savons construire un agent et lui donner un outil simple, nous sommes prets pour la prochaine étape : lui donner des outils puissants pour interagir avec des DataFrames Pandas et devenir un veritable assistant d'analyse de données. C'est l'objet du Lab 7 !"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "cell-7ecacbd6",
    "metadata": {
     "papermill": {
-     "duration": 0.004114,
-     "end_time": "2026-09-23T14:36:45.084689+00:00",
+     "duration": 0.002707,
+     "end_time": "2026-09-25T04:29:21.015386",
      "exception": false,
-     "start_time": "2026-09-23T14:36:45.080575+00:00",
+     "start_time": "2026-09-25T04:29:21.012679",
      "status": "completed"
     },
     "tags": []
@@ -774,6 +799,25 @@
     "2. T. Schick, J. Dwivedi-Yu, R. Dessì, et al., *Toolformer: Language Models Can Teach Themselves to Use Tools*, NeurIPS 2023, arXiv:2302.04761. Fondement académique des LLMs *tool-augmented* (décider/quand/arguments d'un appel d'outil) sous-jacent au décorateur `@tool` (Étape 2).\n",
     "3. H. Chase, *LangChain*, 2022 ; LangGraph, `langchain-ai/langgraph`. Framework d'orchestration d'agents (graphe d'états) utilisé tout au long du laboratoire — référence bibliographique détaillée au Lab 8.\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e6e6eb76",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003098,
+     "end_time": "2026-09-25T04:29:21.021186",
+     "exception": false,
+     "start_time": "2026-09-25T04:29:21.018088",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "***\n",
+    "\n",
+    "**Retour au sommaire** : [Index ML](../../../../README.md) | [Journée 3](../../README.md)\n"
+   ]
   }
  ],
  "metadata": {
@@ -809,18 +853,18 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.12"
+   "version": "3.11.9"
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 13.900499,
-   "end_time": "2026-09-23T14:36:45.870728+00:00",
+   "duration": 8.497011,
+   "end_time": "2026-09-25T04:29:21.492486",
    "environment_variables": {},
    "exception": null,
-   "input_path": "MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb",
-   "output_path": "MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb",
+   "input_path": "Lab6-First-Agent.ipynb",
+   "output_path": "Lab6-First-Agent.ipynb",
    "parameters": {},
-   "start_time": "2026-09-23T14:36:31.970229+00:00",
+   "start_time": "2026-09-25T04:29:12.995475",
    "version": "2.7.0"
   }
  },