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docs-website/docs/pipeline-components/generators/vertexaicodegenerator.mdx

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+---
+title: "VertexAICodeGenerator"
+id: vertexaicodegenerator
+slug: "/vertexaicodegenerator"
+description: "This component enables code generation using Google Vertex AI generative model."
+---
+
+# VertexAICodeGenerator
+
+This component enables code generation using Google Vertex AI generative model.
+
+<div className="key-value-table">
+
+|  |  |
+| --- | --- |
+| **Mandatory run variables** | `prefix`: A string of code before the current point  <br /> <br />`suffix`: An optional string of code after the current point |
+| **Output variables** | `replies`: Code generated by the model |
+| **API reference** | [Google Vertex](/reference/integrations-google-vertex) |
+| **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/google_vertex |
+| **Package name** | `google-vertex-haystack` |
+
+</div>
+
+`VertexAICodeGenerator` supports `code-bison`, `code-bison-32k`, and `code-gecko`.
+
+### Parameters Overview
+
+`VertexAICodeGenerator` 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 first to use the  `VertexAIImageCaptioner`:
+
+```shell
+pip install google-vertex-haystack
+```
+
+Basic usage:
+
+````python
+from haystack_integrations.components.generators.google_vertex import VertexAICodeGenerator
+
+generator = VertexAICodeGenerator()
+
+result = generator.run(prefix="def to_json(data):")
+
+for answer in result["replies"]:
+    print(answer)
+
+>>> ```python
+>>> import json
+>>>
+>>> def to_json(data):
+>>>   """Converts a Python object to a JSON string.
+>>>
+>>>   Args:
+>>>     data: The Python object to convert.
+>>>
+>>>   Returns:
+>>>     A JSON string representing the Python object.
+>>>   """
+>>>
+>>>   return json.dumps(data)
+>>> ```
+````
+
+You can also set other parameters like the number of output tokens, temperature, stop sequences, and the number of candidates.
+
+Let’s try a different model:
+
+```python
+from haystack_integrations.components.generators.google_vertex import VertexAICodeGenerator
+
+generator = VertexAICodeGenerator(
+	model="code-gecko",
+	temperature=0.8,
+	candidate_count=3
+)
+
+result = generator.run(prefix="def convert_temperature(degrees):")
+
+for answer in result["replies"]:
+    print(answer)
+
+>>>
+>>>     return degrees * (9/5) + 32
+
+>>>
+>>>     return round(degrees * (9.0 / 5.0) + 32, 1)
+
+>>>
+>>>     return 5 * (degrees - 32) /9
+>>>
+>>> def convert_temperature_back(degrees):
+>>>     return 9 * (degrees / 5) + 32
+```