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Herrenberg Riesling Spätlese 2023Der erste Eindruck in der Nase zeigt eine rauchige dunkle Schieferaromatik. Geschwenkt kommen fruchtige Aromen dazu. Grner Apfel, gelber Pfirsich und Ananas. Etherische und kruterwrzige Nuancen geben ihm das typische Herrenberg Aroma. Am Gaumen zeigt er eine saftige gelbe Zitrusfrucht wie Mango, Maracuja und Nektarine. Diese Fruchtigkeit ist balanciert durch einen eher zitrischen Abgang, der an reife Saftzitrone erinnert. Trotz seiner expressiven
Der erste Eindruck in der Nase zeigt eine rauchige dunkle Schieferaromatik. Geschwenkt kommen fruchtige Aromen dazu. Grüner Apfel, gelber Pfirsich und Ananas. Etherische und kräuterwürzige Nuancen geben ihm das typische Herrenberg Aroma. Am Gaumen zeigt er eine saftige gelbe Zitrusfrucht wie Mango, Maracuja und Nektarine. Diese Fruchtigkeit ist balanciert durch einen eher zitrischen Abgang, der an reife Saftzitrone erinnert. Trotz seiner expressiven Fruchtaromatik ist der Wein glasklar und brillant mit einer kräuterigen floralen Leichtigkeit und animierender Salzigkeit.Food Pairing (Speiseempfehlung): Ceviche mit Milch, Mango und Avocado oder fruchtige Desserts wie Sorbet von Johannisbeeren.
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4.8 ★★★★★
Based on 22 reviews
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Product Reviews
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 5, 2025
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents.
What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025
★★★★★ 5
Excellent Handbook
Format: Paperback
What got my interest in this book is the author. He's well-known as a leader in the LangChain world. And his book did not disappoint. It goes through the whole life cycle of development and there is a lot useful insights. If you are looking to build real-world genAI/agentic apps, then this book is certainly a great choice.
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Reviewed in the United States on April 11, 2025
★★★★★ 5
Useful resource!
Format: Paperback
I found this book well written and extremely useful for getting comfortable with LLMs for building AI apps in production and other agent driven applications.
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Reviewed in the United States on April 10, 2025
★★★★★ 5
Fantastic!
Format: Paperback
A great primer on getting started with LangChain concepts!
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Reviewed in the United States on April 10, 2025
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