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Awesome GitHub RepositoriesOutput Citations
Mechanisms that require LLMs to reference specific source identifiers for the data used in their responses.
Distinguishing note: The candidates focus on data routing or code links, not LLM-generated source attribution.
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- brexhq/prompt-engineering
brexhq/prompt-engineering
9,538Auf GitHub ansehenThis project is a comprehensive guide and framework for large language model prompt engineering. It provides a collection of techniques and patterns for optimizing model responses through structured system prompts, context management, and a variety of implementation patterns. The project focuses on several specialized domains, including the creation of autonomous agents through reasoning loops and the implementation of retrieval augmented generation to inject semantic context into prompts. It also provides methods for enforcing structured outputs in serialization formats like JSON or YAML for
Directs the model to provide unique identifiers or links for specific data points used in its responses.
