langchain_experimental.tabular_synthetic_data.openai.create_openai_data_generator¶
langchain_experimental.tabular_synthetic_data.openai.create_openai_data_generator(output_schema: Union[Dict[str, Any], Type[BaseModel]], llm: ChatOpenAI, prompt: BasePromptTemplate, output_parser: Optional[BaseLLMOutputParser] = None, **kwargs: Any) → SyntheticDataGenerator[source]¶
Create an instance of SyntheticDataGenerator tailored for OpenAI models.
This function creates an LLM chain designed for structured output based on the
provided schema, language model, and prompt template. The resulting chain is then
used to instantiate and return a SyntheticDataGenerator.
Parameters
output_schema (Union[Dict[str, Any], Type[BaseModel]]) – Schema for expected
a (output. This can be either a dictionary representing a valid JsonSchema or) – 
class. (Pydantic BaseModel) – 
llm (ChatOpenAI) – OpenAI language model to use.
prompt (BasePromptTemplate) – Template to be used for generating prompts.
output_parser (Optional[BaseLLMOutputParser], optional) – Parser for
provided (processing model outputs. If none is) – 
inferred (a default will be) – 
types. (from the function) – 
**kwargs – Additional keyword arguments to be passed to
create_structured_output_chain. – 
Returns: SyntheticDataGenerator: An instance of the data generator set up with
the constructed chain.
Usage:To generate synthetic data with a structured output, first define your desired
output schema. Then, use this function to create a SyntheticDataGenerator
instance. After obtaining the generator, you can utilize its methods to produce
the desired synthetic data.