A practical course for developers on building applications with the Kerb Python LLM toolkit. This course teaches you how to implement text generation, Retrieval-Augmented Generation (RAG) systems, autonomous agents, and more. You will learn to manage prompts, handle data, optimize performance, and ensure application safety using Kerb's comprehensive set of modules.
Prerequisites Intermediate Python
Level:
LLM Generation
Generate text using multiple LLM providers through a unified interface.
Prompt Engineering
Construct effective prompts with templates, versioning, and few-shot examples.
RAG Systems
Build and optimize Retrieval-Augmented Generation (RAG) systems from scratch.
Autonomous Agents
Develop autonomous agents that can use tools to perform complex tasks.
Application Optimization
Implement caching, memory, and safety features in LLM applications.
Data Handling
Process and prepare various document types for use in LLM applications.
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