SKU/Artículo: AMZ-B0GF2QP2QM
LLM Engineering in Rust: Designing High Performance LLM Pipelines, APIs and Integrations with Rust
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
1.26 kg
1.26 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Master LLM Engineering with the Speed, Safety, and Power of Rust Modern AI systems demand more than clever prompts, require reliable pipelines, high-performance APIs, fast embeddings, efficient vector search, safe deployment, and rock-solid engineering. Rust is uniquely positioned to meet these challenges, giving developers the memory safety, concurrency tools, and performance needed to run LLM applications at scale. LLM Engineering in Rust is your complete, practical guide to building production-grade AI systems using Rust. Whether you’re integrating cloud models like OpenAI or Anthropic, running local models with GGML or llama.cpp, or designing advanced RAG and agent workflows, this book gives you the tools and patterns to build fast, dependable, and maintainable AI solutions. You’ll learn how to structure LLM pipelines, design reusable clients, build streaming APIs, integrate vector databases, run local inference, optimize performance, secure your systems, and deploy Rust microservices in real environments. Every chapter includes clear explanations and authentic Rust code examples to help you understand each concept in depth—not just in theory, but in practice. Inside, you’ll learn how to:Work confidently with tokens, embeddings, prompts, and LLM pipelinesBuild reusable Rust abstractions for cloud and local modelsHandle streaming responses, rate limits, authentication, and retriesGenerate embeddings and implement fast semantic search with Qdrant, Pinecone, or MilvusDesign low-latency pipelines with caching, batching, and parallel processingBuild REST and gRPC LLM services with real-time streamingRun models locally using GGML, llama.cpp, and Rust runtimesOptimize quantization, memory usage, and hardware accelerationPair LLMs with databases, queues, and distributed systemsImplement RAG, hybrid search, rules-based logic, and autonomous agentsApply best practices for safety, security, monitoring, and incident responseEvaluate LLM outputs with snapshot tests, benchmarks, and golden datasetsDeploy production-ready Rust services using Docker, Kubernetes, and CI/CDWhether you're an AI engineer, Rust developer, backend engineer, or someone building the next generation of intelligent applications, this book gives you the complete toolkit to design, optimize, and deploy LLM-powered systems with confidence. If you find this book helpful, please consider leaving a review, your feedback helps other developers discover reliable, practical resources for mastering Rust and AI.
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AR$102.910
49% OFF
AR$52.778
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