Classes for working with language models.
Classes
ChatMessage
ChatMessage(content: str, author: str)A chat message.
Author of the message.
ChatSession
ChatSession(
model: vertexai.language_models._language_models.ChatModel,
context: typing.Optional[str] = None,
examples: typing.Optional[
typing.List[vertexai.language_models._language_models.InputOutputTextPair]
] = None,
max_output_tokens: int = 128,
temperature: float = 0.0,
top_k: int = 40,
top_p: float = 0.95,
message_history: typing.Optional[
typing.List[vertexai.language_models._language_models.ChatMessage]
] = None,
)ChatSession represents a chat session with a language model.
Within a chat session, the model keeps context and remembers the previous conversation.
CodeChatModel
CodeChatModel(model_id: str, endpoint_name: typing.Optional[str] = None)CodeChatModel represents a model that is capable of completing code.
.. rubric:: Examples
code_chat_model = CodeChatModel.from_pretrained("codechat-bison@001")
code_chat = code_chat_model.start_chat( max_output_tokens=128, temperature=0.2, )
code_chat.send_message("Please help write a function to calculate the min of two numbers")
CodeChatSession
CodeChatSession(
model: vertexai.language_models._language_models.CodeChatModel,
max_output_tokens: int = 128,
temperature: float = 0.5,
)CodeChatSession represents a chat session with code chat language model.
Within a code chat session, the model keeps context and remembers the previous converstion.
CodeGenerationModel
CodeGenerationModel(model_id: str, endpoint_name: typing.Optional[str] = None)A language model that generates code.
.. rubric:: Examples
Getting answers:
generation_model = CodeGenerationModel.from_pretrained("code-bison@001") print(generation_model.predict( prefix="Write a function that checks if a year is a leap year.", ))
completion_model = CodeGenerationModel.from_pretrained("code-gecko@001") print(completion_model.predict( prefix="def reverse_string(s):", ))
InputOutputTextPair
InputOutputTextPair(input_text: str, output_text: str)InputOutputTextPair represents a pair of input and output texts.
TextEmbedding
TextEmbedding(
values: typing.List[float], _prediction_response: typing.Optional[typing.Any] = None
)Contains text embedding vector.
TextGenerationResponse
TextGenerationResponse(text: str, _prediction_response: typing.Any, is_blocked: bool = False, safety_attributes: typing.Dict[str, float] = <factory>)TextGenerationResponse represents a response of a language model. .. attribute:: text
The generated text
Scores for safety attributes. Learn more about the safety attributes here: https://cloud.google.com/vertex-ai/docs/generative-ai/learn/responsible-ai#safety_attribute_descriptions