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IA Générative en Production: Construire des systèmes autonomes avec LangChain et LangGraph
Paperback
Publisher: Independently Published
Published: Dec 18 2025
Pages: 186
Weight: 0.73
Height: 0.40 Width: 7.50 Depth: 9.25
Language: French
Vous avez probablement déjà exécuté un script Python qui appelle OpenAI et affiche une réponse. Cela ressemble à de la magie. Mais transformer ce script en une application fiable et évolutive - capable de gérer les échecs, de se souvenir du contexte et d'interagir avec vos données internes - est un défi d'ingénierie totalement différent.
IA Générative en Production comble le fossé entre le prototype du week-end et le logiciel robuste. Ce livre ne perd pas de temps avec la hype; il se concentre sur les modèles architecturaux nécessaires pour maîtriser la nature probabiliste des grands modèles de langage (LLM). Vous cesserez de voir le LLM comme une boîte noire pour le traiter comme un moteur de raisonnement devant être intégré dans une stack déterministe.
En utilisant les frameworks standards de l'industrie, LangChain et LangGraph, vous apprendrez à construire des agents qui sont étatiques, contrôlables et autonomes. De l'obligation pour les modèles de produire du JSON valide avec Pydantic, à l'orchestration d'équipes multi-agents complexes qui recherchent, codent et révisent leur propre travail, ce guide couvre le cycle de vie complet du développement IA.
Dans ce livre, vous apprendrez Ã
Maîtriser la Stack: Passez de scripts fragiles à des chaînes modulaires utilisant le LangChain Expression Language (LCEL).
Contrôler la Sortie: Éliminez les erreurs d'analyse en liant des outils et en imposant des schémas de données structurés via Pydantic.
Construire un RAG Avancé Allez au-delà de la récupération naïve avec la recherche hybride, la reformulation de requêtes et le re-ranking pour éliminer les hallucinations.
Orchestrer des Agents: Passez de chaînes linéaires à des graphes cycliques avec LangGraph, permettant la persistance de la mémoire, l'approbation humaine et des boucles de raisonnement complexes.
Mettre à l'Échelle et Déployer: Conteneurisez votre application avec Docker, exposez-la via l'API LangServe et surveillez les performances avec les traces LangSmith.
Que vous soyez ingénieur logiciel, data scientist ou fondateur technique, ce livre fournit les modèles mentaux et le code nécessaires pour construire la prochaine génération de logiciels.
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