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When using the VertexAIGeminiGenerator, I believe it this piece of code here should run without issues, assuming that the GCP_PROJECT_ID and GOOGLE_APPLICATION_CREDENTIALS are also set:
fromhaystack_integrations.components.generators.google_verteximportVertexAIGeminiGeneratorgemini=VertexAIGeminiGenerator()
result=gemini.run(parts= ["What is the most interesting thing you know?"])
foranswerinresult["replies"]:
print(answer)
However, requiring project_id as a parameter hinders our ability to create a multi-LLM service abstraction that leverages various Haystack generators. We aim for generator-agnostic implementation to test and use the best performers.
As you can see in my console the variables are indeed set
The text was updated successfully, but these errors were encountered:
When using the VertexAIGeminiGenerator, I believe it this piece of code here should run without issues, assuming that the
GCP_PROJECT_ID
andGOOGLE_APPLICATION_CREDENTIALS
are also set:However, requiring project_id as a parameter hinders our ability to create a multi-LLM service abstraction that leverages various Haystack generators. We aim for generator-agnostic implementation to test and use the best performers.
As you can see in my console the variables are indeed set
The text was updated successfully, but these errors were encountered: