LLM-Engineers-Handbook and llm-apps-workshop
The LLM Engineers Handbook, a comprehensive practical guide, and the LLM Apps Workshop, focused on building real-world applications, are complements, with the former providing foundational knowledge and best practices that can be applied to the hands-on app development described in the latter, especially given both project's emphasis on AWS deployment.
About LLM-Engineers-Handbook
PacktPublishing/LLM-Engineers-Handbook
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
Implements a complete end-to-end LLM system using Domain-Driven Design principles, integrating ZenML for pipeline orchestration, Qdrant for vector search, and MongoDB for data management. Covers the full ML lifecycle from data collection and DPO-based model training to RAG implementation and inference via FastAPI, with CI/CD automation through GitHub Actions and deployment infrastructure for AWS.
About llm-apps-workshop
aws-samples/llm-apps-workshop
Use LLMs for building real-world apps
Demonstrates inference, embeddings generation, and retrieval-augmented generation (RAG) patterns using Amazon SageMaker JumpStart to host LLMs as managed endpoints. Includes practical examples integrating LangChain, OpenSearch, and Streamlit for question-answering applications. Covers prompt engineering techniques including zero-shot and few-shot learning approaches.
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