Prompts

Note

Conceptual Guide

The new way of programming models is through prompts. A prompt refers to the input to the model. This input is often constructed from multiple components. A PromptTemplate is responsible for the construction of this input. LangChain provides several classes and functions to make constructing and working with prompts easy.

• Getting Started: An overview of the prompts.

• LLM Prompt Templates: How to use PromptTemplates to prompt Language Models.

• Chat Prompt Templates: How to use PromptTemplates to prompt Chat Models.

• Example Selectors: Often times it is useful to include examples in prompts. These examples can be dynamically selected. This section goes over example selection.

• Output Parsers: Language models (and Chat Models) output text. But many times you may want to get more structured information. This is where output parsers come in. Output Parsers:

  • instruct the model how output should be formatted,

  • parse output into the desired formatting (including retrying if necessary).