Wrappers around Large Language Models (in particular, the `generate` ability of large language models) are some of the core functionality of LangChain.
These wrappers are classes that are callable: they take in an input string, and return the generated output string.
## Embeddings
These classes are very similar to the LLM classes in that they are wrappers around models,
but rather than return a string they return an embedding (list of floats). This are particularly useful when
implementing semantic search functionality. They expose separate methods for embedding queries versus embedding documents.
## Vectorstores
These are datastores that store documents. They expose a method for passing in a string and finding similar documents.
## Chains
These are pipelines that combine multiple of the above ideas.
They vary greatly in complexity and are combination of generic, highly configurable pipelines and more narrow (but usually more complex) pipelines.
