Chat and Language Models

LLMs are currently available in two API types:

• LanguageModels. Their API is very simple - they accept a String as input and return a String as output.
  This API is now becoming obsolete in favor of chat API (second API type).
• ChatLanguageModels. These accept either a single or multiple ChatMessages as input
  and return an AiMessage as output.
  ChatMessage usually contains text, but some LLMs also support a mix of text and Images.
  Examples of such chat models include OpenAI’s gpt-3.5-turbo and Google’s gemini-pro.

Support for LanguageModels will no longer be expanded in LangChain4j,
so in all new features, we will use a ChatLanguageModel API.

ChatLanguageModel is the low-level API in LangChain4j, offering the most power and flexibility.
There are also high-level APIs (Chains and AiServices) that we will cover later, after we go over the basics.

Apart from ChatLanguageModel and LanguageModel, LangChain4j supports the following types of models:

• EmbeddingModel - This model can translate text into an Embedding.
• ImageModel - This model can generate and edit Images.
• ModerationModel - This model can check if the text contains harmful content.
• ScoringModel - This model can score (or rank) multiple pieces of text against a query,
  essentially determining how relevant each piece of text is to the query. This is useful for RAG.
  These will be covered later.

Now, let’s take a closer look at the ChatLanguageModel API.

public interface ChatLanguageModel {
   

    String gen