Module llm (2.21.0)

LLM models.

Classes

Claude3TextGenerator

Claude3TextGenerator(
 *,
 model_name: typing.Optional[
 typing.Literal[
 "claude-3-sonnet", "claude-3-haiku", "claude-3-5-sonnet", "claude-3-opus"
 ]
 ] = None,
 session: typing.Optional[bigframes.session.Session] = None,
 connection_name: typing.Optional[str] = None
)

Claude3 text generator LLM model.

Go to Google Cloud Console -> Vertex AI -> Model Garden page to enable the models before use. Must have the Consumer Procurement Entitlement Manager Identity and Access Management (IAM) role to enable the models. https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-partner-models#grant-permissions

The models only available in specific regions. Check https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude#regions for details.

Parameters
Name	Description
`model_name`	`str, Default to "claude-3-sonnet"` The model for natural language tasks. Possible values are "claude-3-sonnet", "claude-3-haiku", "claude-3-5-sonnet" and "claude-3-opus". "claude-3-sonnet" (deprecated) is Anthropic's dependable combination of skills and speed. It is engineered to be dependable for scaled AI deployments across a variety of use cases. "claude-3-haiku" is Anthropic's fastest, most compact vision and text model for near-instant responses to simple queries, meant for seamless AI experiences mimicking human interactions. "claude-3-5-sonnet" is Anthropic's most powerful AI model and maintains the speed and cost of Claude 3 Sonnet, which is a mid-tier model. "claude-3-opus" is Anthropic's second-most powerful AI model, with strong performance on highly complex tasks. https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude#available-claude-models If no setting is provided, "claude-3-sonnet" will be used by default and a warning will be issued.
`session`	`bigframes.Session or None` BQ session to create the model. If None, use the global default session.
`connection_name`	`str or None` Connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.

GeminiTextGenerator

GeminiTextGenerator(
 *,
 model_name: typing.Optional[
 typing.Literal[
 "gemini-1.5-pro-preview-0514",
 "gemini-1.5-flash-preview-0514",
 "gemini-1.5-pro-001",
 "gemini-1.5-pro-002",
 "gemini-1.5-flash-001",
 "gemini-1.5-flash-002",
 "gemini-2.0-flash-exp",
 "gemini-2.0-flash-001",
 "gemini-2.0-flash-lite-001",
 ]
 ] = None,
 session: typing.Optional[bigframes.session.Session] = None,
 connection_name: typing.Optional[str] = None,
 max_iterations: int = 300
)

Gemini text generator LLM model.

Parameters
Name	Description
`model_name`	`str, Default to "gemini-2.0-flash-001"` The model for natural language tasks. Accepted values are "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514", "gemini-1.5-pro-001", "gemini-1.5-pro-002", "gemini-1.5-flash-001", "gemini-1.5-flash-002", "gemini-2.0-flash-exp", "gemini-2.0-flash-lite-001", and "gemini-2.0-flash-001". If no setting is provided, "gemini-2.0-flash-001" will be used by default and a warning will be issued.
`session`	`bigframes.Session or None` BQ session to create the model. If None, use the global default session.
`connection_name`	`str or None` Connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.
`max_iterations`	`Optional[int], Default to 300` The number of steps to run when performing supervised tuning.

MultimodalEmbeddingGenerator

MultimodalEmbeddingGenerator(
 *,
 model_name: typing.Optional[typing.Literal["multimodalembedding@001"]] = None,
 session: typing.Optional[bigframes.session.Session] = None,
 connection_name: typing.Optional[str] = None
)

Multimodal embedding generator LLM model.

Parameters
Name	Description
`model_name`	`str, Default to "multimodalembedding@001"` The model for multimodal embedding. Can set to "multimodalembedding@001". Multimodal-embedding models returns model embeddings for text, image and video inputs. If no setting is provided, "multimodalembedding@001" will be used by default and a warning will be issued.
`session`	`bigframes.Session or None` BQ session to create the model. If None, use the global default session.
`connection_name`	`str or None` Connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.

TextEmbeddingGenerator

TextEmbeddingGenerator(
 *,
 model_name: typing.Optional[
 typing.Literal[
 "text-embedding-005",
 "text-embedding-004",
 "text-multilingual-embedding-002",
 ]
 ] = None,
 session: typing.Optional[bigframes.session.Session] = None,
 connection_name: typing.Optional[str] = None
)

Text embedding generator LLM model.

Parameters
Name	Description
`model_name`	`str, Default to "text-embedding-004"` The model for text embedding. Possible values are "text-embedding-005", "text-embedding-004" or "text-multilingual-embedding-002". text-embedding models returns model embeddings for text inputs. text-multilingual-embedding models returns model embeddings for text inputs which support over 100 languages. If no setting is provided, "text-embedding-004" will be used by default and a warning will be issued.
`session`	`bigframes.Session or None` BQ session to create the model. If None, use the global default session.
`connection_name`	`str or None` Connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.