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Copy file name to clipboardExpand all lines: docs/configs/model-config.md
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@@ -28,6 +28,16 @@ These settings are **required only** for generators that utilize Google Cloud Ve
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> Required*, you can globally set your GCP project_id and gcp_region using the environment variables `EVAL_GCP_PROJECT_ID` and `EVAL_GCP_PROJECT_REGION`.
These settings are **required only** for the `agent_runtime` generator, which connects to a live deployed Agent Runtime (Gemini Enterprise Agent Platform) instance.
|`resource_name`| Yes | N/A | The fully-qualified resource ID of the deployed Agent Engine resource, e.g. `projects/<GCP_PROJECT>/locations/<REGION>/reasoningEngines/<RESOURCE_ID>`. |
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|`gcp_project_id`| Optional |`""`| The Google Cloud Project ID that hosts your Vertex AI resources. Can also be set via `EVAL_GCP_PROJECT_ID` environment variable. |
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|`gcp_region`| Optional |`""`| The Google Cloud region where the Vertex AI service is deployed. Can also be set via `EVAL_GCP_PROJECT_REGION` environment variable. |
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## Important Notes
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-**Customization:** This configuration is fully customizable to the needs of the selected generator. You can add or remove keys as necessary.
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-**Rate Limiting & Retries:** The `execs_per_minute` and `max_attempts` keys help control the query generation process, ensuring that you can stay below project quota limits.
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## Example Configuration
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## Example Configurations
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Below is an example of the updated YAML configuration file:
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Below are examples of the YAML configuration files:
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