ChatModel(model_id: str, endpoint_name: typing.Optional[str] = None)ChatModel represents a language model that is capable of chat.
Examples::
chat_model = ChatModel.from_pretrained("chat-bison@001")
chat = chat_model.start_chat(
context="My name is Ned. You are my personal assistant. My favorite movies are Lord of the Rings and Hobbit.",
examples=[
InputOutputTextPair(
input_text="Who do you work for?",
output_text="I work for Ned.",
),
InputOutputTextPair(
input_text="What do I like?",
output_text="Ned likes watching movies.",
),
],
temperature=0.3,
)
chat.send_message("Do you know any cool events this weekend?")
Methods
ChatModel
ChatModel(model_id: str, endpoint_name: typing.Optional[str] = None)Creates a LanguageModel.
This constructor should not be called directly.
Use LanguageModel.from_pretrained(model_name=...) instead.
from_pretrained
from_pretrained(model_name: str) -> vertexai._model_garden._model_garden_models.TLoads a _ModelGardenModel.
| Exceptions | |
|---|---|
| Type | Description |
ValueError |
If model_name is unknown. |
ValueError |
If model does not support this class. |
start_chat
start_chat(
*,
context: typing.Optional[str] = None,
examples: typing.Optional[
typing.List[vertexai.language_models.InputOutputTextPair]
] = None,
max_output_tokens: typing.Optional[int] = None,
temperature: typing.Optional[float] = None,
top_k: typing.Optional[int] = None,
top_p: typing.Optional[float] = None,
message_history: typing.Optional[
typing.List[vertexai.language_models.ChatMessage]
] = None,
stop_sequences: typing.Optional[typing.List[str]] = None
) -> vertexai.language_models.ChatSessionStarts a chat session with the model.