Kevin Yang

I have encountered the same issue as @daranable regarding the quota limit when working with embedding. This issue is because the prediction endpoint only accepts 20 requests per minute (in...

It is imported from `langchain.embeddings.vertexai` @pmcray. You can refer to the [document](https://python.langchain.com/en/latest/modules/models/text_embedding/examples/google_vertex_ai_palm.html). My LangChain version is 0.0.187

@pmcray Hope it helps. I am in the same situation as well, and I am still experimenting and learning the capabilities and limitations of PaLM.

@pmcray Yeah, the token limits is another issue that restricts the way we can do prompting. From my understanding, your case is more like content generation. I think embedding is...

@magnussentio probably you're lookng for this? [Google Cloud Platform Vertex AI PaLM](https://python.langchain.com/en/latest/modules/models/llms/integrations/google_vertex_ai_palm.html)

@Vansh1190 Is your region supported by Vertex AI in the [available regions](https://cloud.google.com/vertex-ai/docs/general/locations#vertex-ai-regions)?

Hi all, thank you very much again for all the constructive feedback. I've push some changes based on that. ### Design Principle 1. We want to prioritize on using the...

Attach unit test result. `pytest --log-cli-level=DEBUG airflow-core/tests/unit/serialization/` 

Thanks a lot for the thoughtful feedback. You're absolutely right about the risk of using `import_string()` in the `pydantic` serializer, or potentially distribute this import logic across multiple places. I...

> allow passing the loaded class to the deserializer. This requires refactoring of the other deserializers to accept a class. @bolkedebruin , I feel like this can be the way...