rawwar commented on code in PR #37287: URL: https://github.com/apache/airflow/pull/37287#discussion_r1484824512
########## airflow/providers/google/cloud/operators/vertex_ai/generative_model.py: ########## @@ -0,0 +1,159 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +"""This module contains Google Vertex AI Generative AI operators.""" + +from __future__ import annotations + +from typing import TYPE_CHECKING, Sequence + +from airflow.providers.google.cloud.hooks.vertex_ai.generative_model import ( + LanguageModelHook, + MultimodalModelHook, +) +from airflow.providers.google.cloud.operators.cloud_base import GoogleCloudBaseOperator + +if TYPE_CHECKING: + from vertexai.preview.generative_models import ChatSession + from airflow.utils.context import Context + + +class LanguageModelGenerateTextOperator(GoogleCloudBaseOperator): + """ + Uses the Vertex AI PaLM API to generate natural language text. + + :param prompt: Required. Inputs or queries that a user or a program gives + to the Vertex AI PaLM API, in order to elicit a specific response. + :param pretrained_model: By default uses the pretrained_model text-bison, + optimized for performing natural language tasks such as classification, + summarization, extraction, content creation, and ideation. + :param temperature: Temperature controls the degree of randomness in token + selection. Defaults to 0.0. + :param max_output_tokens: Token limit determines the maximum amount of text + output. Defaults to 256. + :param top_p: Tokens are selected from most probable to least until the sum + of their probabilities equals the top_p value. Defaults to 0.8. + :param top_k: A top_k of 1 means the selected token is the most probable + among all tokens. Defaults to 0.4. + :param gcp_conn_id: The connection ID to use connecting to Google Cloud. + :param impersonation_chain: Optional service account to impersonate using short-term + credentials, or chained list of accounts required to get the access_token + of the last account in the list, which will be impersonated in the request. + If set as a string, the account must grant the originating account + the Service Account Token Creator IAM role. + If set as a sequence, the identities from the list must grant + Service Account Token Creator IAM role to the directly preceding identity, with first + account from the list granting this role to the originating account (templated). + """ + + def __init__( + self, + *, + prompt: str, + pretrained_model: str = "text-bison", + temperature: float = 0.0, + max_output_tokens: int = 256, + top_p: float = 0.8, + top_k: int = 40, + gcp_conn_id: str = "google_cloud_default", + impersonation_chain: str | Sequence[str] | None = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.prompt = prompt + self.pretrained_model = pretrained_model + self.temperature = temperature + self.max_output_tokens = max_output_tokens + self.top_p = top_p + self.top_k = top_k + self.gcp_conn_id = gcp_conn_id + self.impersonation_chain = impersonation_chain + + def execute(self, context: Context): + self.hook = LanguageModelHook( + gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain + ) + + self.log.info("Submitting prompt") + response = self.hook.generate_text( + prompt=self.prompt, + pretrained_model=self.pretrained_model, + temperature=self.temperature, + max_output_tokens=self.max_output_tokens, + top_p=self.top_p, + top_k=self.top_k, + ) + + self.log.info("Model response: %s", response) + self.xcom_push(context, key="prompt_response", value=response) + + return response + + +class MultimodalModelChatOperator(GoogleCloudBaseOperator): + """ + Uses a Vertex AI Multimodal model to generate natural language text. Review Comment: ```suggestion Use a Vertex AI Multimodal model to generate natural language text. ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
