VertexAIImageQA
This component enables text generation (image captioning) using Google Vertex AI generative models.
Mandatory run variables | “image”: A ByteStream containing an image data”question”: A string of a question about the image |
Output variables | “replies”: A list of strings containing answers generated by the model |
API reference | Google Vertex |
GitHub link | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/google_vertex |
VertexAIImageQA
supports the imagetext
model.
Parameters Overview
VertexAIImageQA
uses Google Cloud Application Default Credentials (ADCs) for authentication. For more information on how to set up ADCs, see the official documentation.
Keep in mind that it’s essential to use an account that has access to a project authorized to use Google Vertex AI endpoints.
You can find your project ID in the GCP resource manager or locally by running gcloud projects list
in your terminal. For more info on the gcloud CLI, see its official documentation.
Usage
You need to install google-vertex-haystack
package to use the VertexAIImageQA
:
pip install google-vertex-haystack
On its own
Basic usage:
from haystack.dataclasses.byte_stream import ByteStream
from haystack_integrations.components.generators.google_vertex import VertexAIImageQA
qa = VertexAIImageQA()
image = ByteStream.from_file_path("dog.jpg")
res = qa.run(image=image, question="What color is this dog")
print(res["replies"][0])
>>> white
You can also set the number of answers generated:
from haystack.dataclasses.byte_stream import ByteStream
from haystack_integrations.components.generators.google_vertex import VertexAIImageQA
qa = VertexAIImageQA(
number_of_results=3,
)
image = ByteStream.from_file_path("dog.jpg")
res = qa.run(image=image, question="Tell me something about this dog")
for answer in res["replies"]:
print(answer)
>>> pomeranian
>>> white
>>> pomeranian puppy
Updated about 1 month ago