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14k White Gold 4mm Heart Amethyst VS Diamond ringPrecious Metal Type: 14k White Gold Weight: 1. 79 GM Material: Primary Purity: 14K Finish: Polished Stone Type_1: Amethyst Stone Type_2: Diamond Stone Color_1: Purple Stone Color_2: White Stone Quantity_1: 1 Stone Quantity_2: 1 Plating: Rhodium Band Width: 1. 5 mm Stone Weight_1: 0. 250 ct Stone Weight_2: 0. 012 ct Stone Clarity_2: VS2 SI1 (VS) Material: Primary: Gold Completeness: Complete (all stones included) Stone Shape_1: Heart Stone Shape_2:
Precious Metal Type: 14k White GoldWeight: 1.79 GM
Material: Primary - Purity:14K
Finish:Polished
Stone Type_1:Amethyst
Stone Type_2:Diamond
Stone Color_1:Purple
Stone Color_2:White
Stone Quantity_1:1
Stone Quantity_2:1
Plating:Rhodium
Band Width:1.5 mm
Stone Weight_1:0.250 ct
Stone Weight_2:0.012 ct
Stone Clarity_2:VS2/SI1 (VS)
Material: Primary:Gold
Completeness:Complete (all stones included)
Stone Shape_1:Heart
Stone Shape_2:Round
Stone Size_1:4 mm
Stone Size_2:1.4 mm
Stone Treatment_1:Heating
Product Type:Jewelry
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Material: Primary - Color:White
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Stone Cut_2:Faceted
Stone Creation Method_1:Natural
Stone Creation Method_2:Natural
Birthstone Month_1:(02) February
Birthstone Month_2:(04) April
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Product ID: Y4587AM-VS
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4.3 ★★★★★
Based on 14 reviews
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Product Reviews
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
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Reviewed in the United States on November 16, 2019
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript.
Great book.
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Reviewed in the United States on June 10, 2025
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
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Reviewed in the United States on April 19, 2025
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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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