object, depending on whether you want to use the formatted value as input to an llm or chat model.For convenience, 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 messageschat(    chat_prompt.format_prompt(        input_language="English", output_language="French", text="I love programming."    ).to_messages())    AIMessage(content="J'adore la programmation.", additional_kwargs={}, example=False)Fine-tuning‚ÄãYou can call fine-tuned OpenAI models by passing in your corresponding modelName parameter.This generally takes the form of ft:{OPENAI_MODEL_NAME}:{ORG_NAME}::{MODEL_ID}. For example:fine_tuned_model = ChatOpenAI(temperature=0, model_name="ft:gpt-3.5-turbo-0613:langchain::7qTVM5AR")fine_tuned_model(messages)    AIMessage(content="J'adore la programmation.", additional_kwargs={}, example=False)PreviousOllamaNextPromptLayer ChatOpenAIFine-tuningCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
This notebook covers how to get started with OpenAI chat models.
This notebook covers how to get started with OpenAI chat models. ->: object, depending on whether you want to use the formatted value as input to an llm or chat model.For convenience, 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 messageschat(    chat_prompt.format_prompt(        input_language="English", output_language="French", text="I love programming."    ).to_messages())    AIMessage(content="J'adore la programmation.", additional_kwargs={}, example=False)Fine-tuning‚ÄãYou can call fine-tuned OpenAI models by passing in your corresponding modelName parameter.This generally takes the form of ft:{OPENAI_MODEL_NAME}:{ORG_NAME}::{MODEL_ID}. For example:fine_tuned_model = ChatOpenAI(temperature=0, model_name="ft:gpt-3.5-turbo-0613:langchain::7qTVM5AR")fine_tuned_model(messages)    AIMessage(content="J'adore la programmation.", additional_kwargs={}, example=False)PreviousOllamaNextPromptLayer ChatOpenAIFine-tuningCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.