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Generative AI Apps with LangChain and Python

64,19 €*

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Produktnummer: 18fbe5916bc2f746dfa7ea99017ec79556
Autor: Jay, Rabi
Themengebiete: AI Text Generation Artificial Intelligence Artificial Intelligence Applications Generative AI Generative AI App Development LLM Chatbot Development LLM Document Search LLMs Large language models Python
Veröffentlichungsdatum: 27.12.2024
EAN: 9798868808814
Sprache: Englisch
Seitenzahl: 513
Produktart: Kartoniert / Broschiert
Verlag: APRESS
Untertitel: A Project-Based Approach to Building Real-World LLM Apps
Produktinformationen "Generative AI Apps with LangChain and Python"
Future-proof your programming career through practical projects designed to grasp the intricacies of LangChain’s components, from core chains to advanced conversational agents.  This hands-on book provides Python developers with the necessary skills to develop real-world Large Language Model (LLM)-based Generative AI applications quickly, regardless of their experience level.Projects throughout the book offer practical LLM solutions for common business issues, such as information overload, internal knowledge access, and enhanced customer communication. Meanwhile, you’ll learn how to optimize workflows, enhance embedding efficiency, select between vector stores, and other optimizations relevant to experienced AI users. The emphasis on real-world applications and practical examples will enable you to customize your own projects to address pain points across various industries.Developing LangChain-based Generative AI LLM Apps with Python employs a focused toolkit (LangChain, Pinecone, and Streamlit LLM integration) to practically showcase how Python developers can leverage existing skills to build Generative AI solutions. By addressing tangible challenges, you’ll learn-by-be doing, enhancing your career possibilities in today’s rapidly evolving landscape.What You Will Learn Understand different types of LLMs and how to select the right ones for responsible AI.Structure effective prompts.Master LangChain concepts, such as chains, models, memory, and agents.Apply embeddings effectively for search, content comparison, and understanding similarity.Setup and integrate Pinecone vector database for indexing, structuring data, and search.Build Q & A applications for multiple doc formats.Develop multi-step AI workflow apps using LangChain agents.Who This Book Is ForPython programmers who aim to develop a basic understanding of AI concepts and move from LLM theory to practical Generative AI application development using LangChain; those seeking a structured guide to enhance their careers by learning to create robust, real-world LLM-powered Generative AI applications; data scientists, analysts, and experienced developers new to LLMs.
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