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).