--- title: "VertexAITextGenerator" id: vertexaitextgenerator slug: "/vertexaitextgenerator" description: "This component enables text generation using Google Vertex AI generative models." --- # VertexAITextGenerator This component enables text generation using Google Vertex AI generative models.
| | | | --- | --- | | **Mandatory run variables** | `prompt`: A string containing the prompt for the model | | **Output variables** | `replies`: A list of strings containing answers generated by the model

`safety_attributes`: A dictionary containing scores for safety attributes

`citations`: A list of dictionaries containing grounding citations | | **API reference** | [Google Vertex](/reference/integrations-google-vertex) | | **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/google_vertex |
`VertexAITextGenerator` supports `text-bison`, `text-unicorn` and `text-bison-32k` models. ### Parameters Overview `VertexAITextGenerator` 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). 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](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). ## Usage You need to install `google-vertex-haystack` package to use the `VertexAITextGenerator`: ```python pip install google-vertex-haystack ``` ### On its own Basic usage: ````python from haystack_integrations.components.generators.google_vertex import VertexAITextGenerator generator = VertexAITextGenerator() res = generator.run("Tell me a good interview question for a software engineer.") print(res["replies"][0]) ```` You can also set other parameters like the number of answers generated, temperature to control the randomness, and stop sequences to stop generation. For a full list of possible parameters, see the documentation of [`TextGenerationModel.predict()`](https://cloud.google.com/python/docs/reference/aiplatform/latest/vertexai.language_models.TextGenerationModel#vertexai_language_models_TextGenerationModel_predict). ```python from haystack_integrations.components.generators.google_vertex import VertexAITextGenerator generator = VertexAITextGenerator( candidate_count=3, temperature=0.2, stop_sequences=["example", "Example"], ) res = generator.run("Tell me a good interview question for a software engineer.") for answer in res["replies"]: print(answer) print("-----") ```