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# OpenAI

This notebook covers how to get started with OpenAI chat models.

    from langchain.chat_models import ChatOpenAI
    from langchain.prompts.chat import (
        ChatPromptTemplate,
        SystemMessagePromptTemplate,
        AIMessagePromptTemplate,
        HumanMessagePromptTemplate,
    )
    from langchain.schema import (
        AIMessage,
        HumanMessage,
        SystemMessage
    )

    chat = ChatOpenAI(temperature=0)

    messages = [
        SystemMessage(content="You are a helpful assistant that translates English to French."),
        HumanMessage(content="Translate this sentence from English to French. I love programming.")
    ]
    chat(messages)

    AIMessage(content="J'aime programmer.", additional_kwargs={})

You can make use of templating by using a `MessagePromptTemplate`. You can build a `ChatPromptTemplate` from one or more `MessagePromptTemplates`. You can use `ChatPromptTemplate`’s `format_prompt` – this returns a `PromptValue`, which you can convert to a string or Message object, depending on whether you want to use the formatted value as input to an llm or chat model.

For convience, there is a `from_template` method exposed on the template. If you were to use this template, this is what it would look like:

    template="You are a helpful assistant that translates {input_language} to {output_language}."
    system_message_prompt = SystemMessagePromptTemplate.from_template(template)
    human_template="{text}"
    human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)

    chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])

    # get a chat completion from the formatted messages
    chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())

    AIMessage(content="J'adore la programmation.", additional_kwargs={})