CYarros10 opened a new pull request, #37721:
URL: https://github.com/apache/airflow/pull/37721

   Creating hooks, operators, and test for two Google Cloud generative model 
APIs. Namely, the [language model for text generation (PaLM 
2)](https://cloud.google.com/vertex-ai/docs/generative-ai/text/test-text-prompts)
 and the [multimodal model for content generation 
(Gemini)](https://cloud.google.com/vertex-ai/docs/generative-ai/multimodal/send-chat-prompts-gemini).
 This will help data engineers begin to incorporate generative AI into their 
pipelines.
   
   Note: 
   
   To use the Vertex AI SDK, this PR utilizes the [google-cloud-aiplatform PyPi 
package](https://pypi.org/project/google-cloud-aiplatform/) and imports the 
library `vertexai`. You can view the source code in the repo: 
[googleapis/python-aiplatform](https://github.com/googleapis/python-aiplatform/tree/main/vertexai)
 and review importing in the 
[README](https://github.com/googleapis/python-aiplatform?tab=readme-ov-file#importing).
   
   The GenerativeModelHook in this PR differs from the ModelServiceClient (used 
by ModelServiceHook). The latter is used for models that the user is creating, 
deploying, and maintaining. Whereas the GenerativeModelHook in this PR is for 
models that are directly serviced by Google. The ModelServiceHook uses a 
separate python library from `google.cloud.aiplatform_v1.types` whereas 
GenerativeModelHook currently uses from `vertexai`. There seemed to be 
separation between the two use cases so I opted to separate for now, with 
potentially merging down the line when/if Google unifies them into one package.
   
   ---
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