Rice Lake 50412 RoughDeck® QC Quick Clean Floor Scale - 4x6HPQC-10K, 4' x 6' x 5.5

Rice Lake 50412 RoughDeck® QC Quick Clean Floor Scale - 4x6HPQC-10K, 4' x 6' x 5.5", 10,000 lb, 20', NTEP III, SST, HE

Marsoni

M251S

$6273.00

Get it in 3 business days with 1 day shipping. Friday, May 29

Rice Lake 50412 RoughDeck® QC Quick Clean Floor Scale - 4x6HPQC-10K, 4' x 6' x 5.5", 10,000 lb, 20', NTEP III, SST, HEThe RoughDeck QC is a hostile environment, stainless steel floor scale customized for food, chemical and other demanding washdown applications. The RoughDeck QCs exclusive gas shock design provides easy lifting and soft closing of the 3 16 inch top plate. Also included is a manual drop in place support bar for use during extended underdeck cleaning. All of our floor scales, unless specified otherwise, are built with lifting holes to assist our dealers

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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