Class Claude3TextGenerator (2.5.0)

  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 enabe 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" 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>.

Methods

__repr__

  __repr__ 
 () 
 

Print the estimator's constructor with all non-default parameter values.

get_params

  get_params 
 ( 
 deep 
 : 
 bool 
 = 
 True 
 ) 
 - 
> typing 
 . 
 Dict 
 [ 
 str 
 , 
 typing 
 . 
 Any 
 ] 
 

Get parameters for this estimator.

Parameter
Name
Description
deep
bool, default True

Default True . If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns
Type
Description
Dictionary
A dictionary of parameter names mapped to their values.

predict

  predict 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 , 
 pandas 
 . 
 core 
 . 
 frame 
 . 
 DataFrame 
 , 
 pandas 
 . 
 core 
 . 
 series 
 . 
 Series 
 , 
 ], 
 * 
 , 
 max_output_tokens 
 : 
 int 
 = 
 128 
 , 
 top_k 
 : 
 int 
 = 
 40 
 , 
 top_p 
 : 
 float 
 = 
 0.95 
 , 
 max_retries 
 : 
 int 
 = 
 0 
 ) 
 - 
> bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 

Predict the result from input DataFrame.

Parameters
Name
Description
X
bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series

Input DataFrame or Series, can contain one or more columns. If multiple columns are in the DataFrame, it must contain a "prompt" column for prediction. Prompts can include preamble, questions, suggestions, instructions, or examples.

max_output_tokens
int, default 128

Maximum number of tokens that can be generated in the response. Specify a lower value for shorter responses and a higher value for longer responses. A token may be smaller than a word. A token is approximately four characters. 100 tokens correspond to roughly 60-80 words. Default 128. Possible values are in the range [1, 4096].

top_k
int, default 40

Top-k changes how the model selects tokens for output. A top-k of 1 means the selected token is the most probable among all tokens in the model's vocabulary (also called greedy decoding), while a top-k of 3 means that the next token is selected from among the 3 most probable tokens (using temperature). For each token selection step, the top K tokens with the highest probabilities are sampled. Then tokens are further filtered based on topP with the final token selected using temperature sampling. Specify a lower value for less random responses and a higher value for more random responses. Default 40. Possible values [1, 40].

top_p
float, default 0.95

Top-p changes how the model selects tokens for output. Tokens are selected from most K (see topK parameter) probable to least until the sum of their probabilities equals the top-p value. For example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-p value is 0.5, then the model will select either A or B as the next token (using temperature) and not consider C at all. Specify a lower value for less random responses and a higher value for more random responses. Default 0.95. Possible values [0.0, 1.0].

max_retries
int, default 0

Max number of retries if the prediction for any rows failed. Each try needs to make progress (i.e. has successfully predicted rows) to continue the retry. Each retry will append newly succeeded rows. When the max retries are reached, the remaining rows (the ones without successful predictions) will be appended to the end of the result.

Returns
Type
Description
DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.

to_gbq

  to_gbq 
 ( 
 model_name 
 : 
 str 
 , 
 replace 
 : 
 bool 
 = 
 False 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 llm 
 . 
 Claude3TextGenerator 
 

Save the model to BigQuery.

Parameters
Name
Description
model_name
str

The name of the model.

replace
bool, default False

Determine whether to replace if the model already exists. Default to False.

Returns
Type
Description
Claude3TextGenerator
Saved model.
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