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Description
silk women dress SilkSilky 100% Mulberry Silk Spaghetti Strap Deep V Neck Midi Dress with V-Back Design, Brown / XLModel Wear: S (Height: 176cm Bust: 86cm Waist: 61cm Hips: 90cm). Dress length measured from top of strap (at maximum extension) to hem. Size Bust Length XS 84cm 33. 1" 118cm 46. 5" S 88cm 34. 6" 120cm 47. 2" M 92cm 36. 2" 122cm 48" L 98cm 38. 6" 124cm 48. 8" XL 102cm 40. 2" 126cm 49. 6" Material: 100% 6A Grade Mulberry Silk,No harmful substances. Elegant midi length, offering a sophisticated and versatile look. Smooth, flowing silhouette, gracefully
- Model Wear: S (Height:176cm / Bust: 86cm / Waist: 61cm / Hips: 90cm).
- Dress length measured from top of strap (at maximum extension) to hem.
| Size | Bust | Length |
| XS | 84cm/33.1" | 118cm / 46.5" |
| S | 88cm/34.6" | 120cm / 47.2" |
| M | 92cm/36.2" | 122cm / 48" |
| L | 98cm/38.6" | 124cm / 48.8" |
| XL | 102cm/40.2" | 126cm / 49.6" |
- Material: 100% 6A Grade Mulberry Silk,No harmful substances.
- Elegant midi length, offering a sophisticated and versatile look.
- Smooth, flowing silhouette, gracefully draping to flatter the figure and enhance natural curves.
- Delicate spaghetti straps, providing subtle support and a refined aesthetic.
- Deep V-neckline, dramatically highlighting the décolletage.
- Subtle V-back, adding a touch of understated elegance.
- Details: Crafted from luxurious silk, this stunning midi slip dress features a smooth, flowing silhouette that beautifully drapes the body. It is designed with delicate spaghetti straps, a deep V-neckline, and a subtle V-back, creating a timeless and effortlessly chic garment perfect for various occasions.
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4.6 ★★★★★
Based on 22 reviews
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Product Reviews
★★★★★ 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Already outdated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
★★★★★ 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