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81 lines
2.6 KiB
Plaintext
81 lines
2.6 KiB
Plaintext
---
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title: "VertexAIImageQA"
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id: vertexaiimageqa
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slug: "/vertexaiimageqa"
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description: "This component enables text generation (image captioning) using Google Vertex AI generative models."
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---
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# VertexAIImageQA
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This component enables text generation (image captioning) using Google Vertex AI generative models.
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<div className="key-value-table">
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| | |
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| --- | --- |
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| **Mandatory run variables** | `image`: A [`ByteStream`](../../concepts/data-classes.mdx#bytestream) containing an image data <br /> <br />`question`: A string of a question about the image |
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| **Output variables** | `replies`: A list of strings containing answers generated by the model |
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| **API reference** | [Google Vertex](/reference/integrations-google-vertex) |
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| **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/google_vertex |
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| **Package name** | `google-vertex-haystack` |
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</div>
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`VertexAIImageQA` supports the `imagetext` model.
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### Parameters Overview
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`VertexAIImageQA` uses Google Cloud Application Default Credentials (ADCs) for authentication. For more information on how to set up ADCs, see the [official documentation](https://cloud.google.com/docs/authentication/provide-credentials-adc).
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Keep in mind that it’s essential to use an account that has access to a project authorized to use Google Vertex AI endpoints.
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You can find your project ID in the [GCP resource manager](https://console.cloud.google.com/cloud-resource-manager) or locally by running `gcloud projects list` in your terminal. For more info on the gcloud CLI, see its [official documentation](https://cloud.google.com/cli).
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## Usage
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You need to install `google-vertex-haystack` package to use the `VertexAIImageQA`:
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```python
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pip install google-vertex-haystack
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```
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### On its own
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Basic usage:
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```python
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from haystack.dataclasses.byte_stream import ByteStream
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from haystack_integrations.components.generators.google_vertex import VertexAIImageQA
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qa = VertexAIImageQA()
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image = ByteStream.from_file_path("dog.jpg")
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res = qa.run(image=image, question="What color is this dog")
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print(res["replies"][0])
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>>> white
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```
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You can also set the number of answers generated:
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```python
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from haystack.dataclasses.byte_stream import ByteStream
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from haystack_integrations.components.generators.google_vertex import VertexAIImageQA
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qa = VertexAIImageQA(
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number_of_results=3,
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)
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image = ByteStream.from_file_path("dog.jpg")
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res = qa.run(image=image, question="Tell me something about this dog")
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for answer in res["replies"]:
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print(answer)
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>>> pomeranian
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>>> white
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>>> pomeranian puppy
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```
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