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Generative AI with JavaScript & TypeScript: A Practical Developer's Guide to LLMs, Prompt Engineering, RAG, AI Agents, Tool Calling, LangChain, LangGraph, MCP, and Production AI Applications - Couverture souple
Synopsis
Unlock the Power of Generative AI Using Your Existing JavaScript & TypeScript Skills!
If you are a JavaScript or TypeScript developer, you don't need to learn Python or machine learning mathematics to build modern AI applications. Generative AI with JavaScript & TypeScript delivers a clear, pragmatic engineering roadmap for software developers who want to move past simple API demos and build production-ready AI features.
Authored by experienced software developer Garima Pandey, this book guides you step-by-step through building 10 real-world projects—from streaming API clients and Zod-validated structured outputs to vector database RAG pipelines, stateful LangGraph agent workflows, and Model Context Protocol (MCP) tool integrations.
What You Will Learn:- LLM Fundamentals: Tokenization, context windows, sampling parameters (temperature, top_p), and message roles.
- Type-Safe AI Applications: Building resilient Node.js & TypeScript integrations with Zod schemas and retry handlers.
- Prompt & Context Engineering: Grounding AI responses, decomposing prompts, and defending against prompt injection.
- Real-Time Streaming & Memory: Server-Sent Events (SSE) chatbots, sliding window sessions, and database-backed persistent user memory.
- Tool Calling: Giving AI models the ability to execute application functions and external APIs safely.
- Retrieval-Augmented Generation (RAG): Building vector search pipelines with Pinecone, parent-child chunking, hybrid search, and re-ranking.
- AI Agents & Workflows: ReAct agent loops, LangChain.js, and stateful cyclic graphs with LangGraph.js and human-in-the-loop approvals.
- Model Context Protocol (MCP): Interoperating with standardized MCP tool servers using @modelcontextprotocol/sdk.
- Production Engineering: Golden dataset evaluations, LangSmith telemetry, token cost optimization, and OWASP AI Security guardrails.
Stop learning AI as a collection of buzzwords. Learn how to engineer useful, production-ready AI applications today!
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Generative AI with JavaScript & TypeScript (Paperback)
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Paperback. Etat : new. Paperback. Unlock the Power of Generative AI Using Your Existing JavaScript & TypeScript Skills!If you are a JavaScript or TypeScript developer, you don't need to learn Python or machine learning mathematics to build modern AI applications. Generative AI with JavaScript & TypeScript delivers a clear, pragmatic engineering roadmap for software developers who want to move past simple API demos and build production-ready AI features.Authored by experienced software developer Garima Pandey, this book guides you step-by-step through building 10 real-world projects-from streaming API clients and Zod-validated structured outputs to vector database RAG pipelines, stateful LangGraph agent workflows, and Model Context Protocol (MCP) tool integrations.What You Will Learn: LLM Fundamentals: Tokenization, context windows, sampling parameters (temperature, top_p), and message roles.Type-Safe AI Applications: Building resilient Node.js & TypeScript integrations with Zod schemas and retry handlers.Prompt & Context Engineering: Grounding AI responses, decomposing prompts, and defending against prompt injection.Real-Time Streaming & Memory: Server-Sent Events (SSE) chatbots, sliding window sessions, and database-backed persistent user memory.Tool Calling: Giving AI models the ability to execute application functions and external APIs safely.Retrieval-Augmented Generation (RAG): Building vector search pipelines with Pinecone, parent-child chunking, hybrid search, and re-ranking.AI Agents & Workflows: ReAct agent loops, LangChain.js, and stateful cyclic graphs with LangGraph.js and human-in-the-loop approvals.Model Context Protocol (MCP): Interoperating with standardized MCP tool servers using atmodelcontextprotocol/sdk.Production Engineering: Golden dataset evaluations, LangSmith telemetry, token cost optimization, and OWASP AI Security guardrails.Stop learning AI as a collection of buzzwords. Learn how to engineer useful, production-ready AI applications today! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798194609130
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Generative AI with JavaScript & TypeScript : A Practical Developer's Guide to LLMs, Prompt Engineering, RAG, AI Agents, Tool Calling, LangChain, LangGraph, MCP, and Production AI Applications
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Generative AI with JavaScript & TypeScript (Paperback)
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Paperback. Etat : new. Paperback. Unlock the Power of Generative AI Using Your Existing JavaScript & TypeScript Skills!If you are a JavaScript or TypeScript developer, you don't need to learn Python or machine learning mathematics to build modern AI applications. Generative AI with JavaScript & TypeScript delivers a clear, pragmatic engineering roadmap for software developers who want to move past simple API demos and build production-ready AI features.Authored by experienced software developer Garima Pandey, this book guides you step-by-step through building 10 real-world projects-from streaming API clients and Zod-validated structured outputs to vector database RAG pipelines, stateful LangGraph agent workflows, and Model Context Protocol (MCP) tool integrations.What You Will Learn: LLM Fundamentals: Tokenization, context windows, sampling parameters (temperature, top_p), and message roles.Type-Safe AI Applications: Building resilient Node.js & TypeScript integrations with Zod schemas and retry handlers.Prompt & Context Engineering: Grounding AI responses, decomposing prompts, and defending against prompt injection.Real-Time Streaming & Memory: Server-Sent Events (SSE) chatbots, sliding window sessions, and database-backed persistent user memory.Tool Calling: Giving AI models the ability to execute application functions and external APIs safely.Retrieval-Augmented Generation (RAG): Building vector search pipelines with Pinecone, parent-child chunking, hybrid search, and re-ranking.AI Agents & Workflows: ReAct agent loops, LangChain.js, and stateful cyclic graphs with LangGraph.js and human-in-the-loop approvals.Model Context Protocol (MCP): Interoperating with standardized MCP tool servers using atmodelcontextprotocol/sdk.Production Engineering: Golden dataset evaluations, LangSmith telemetry, token cost optimization, and OWASP AI Security guardrails.Stop learning AI as a collection of buzzwords. Learn how to engineer useful, production-ready AI applications today! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798194609130
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