# Troubleshooting
URL: https://docs.datarobot.com/en/docs/reference/gen-ai-ref/genai-troubleshooting.html

> An overview of common errors and their handling in DataRobot GenAI functionality.

# Troubleshooting

When working with GenAI in DataRobot, you might encounter errors during creation, management, and use of the features that make up the capabilities. The sections below provide an overview of common errors and their handling. In case of errors, review the error messages and take appropriate action, such as revalidating external vector databases, creating duplicate LLM blueprints, or addressing issues with custom models.

## Vector database error handling

The following issues apply to vector databases.

### Creation failure

Errors might occur during the creation of a vector database, such as issues with data processing or model training. In this case, the system saves the execution status as `Error` and provides an error code and message to help identify and resolve the issue.

### Empty vector database

The vector database might be empty if the documents in the dataset contain no text or only consist of images in PDF files. The system sends a notification of the issue. See the list of [supported dataset types](https://docs.datarobot.com/en/docs/reference/gen-ai-ref/llm-availability.html#supported-dataset-types) for more information.

### Retrieval failure

Errors might occur while retrieving documents from the vector database, such as network glitches or internal errors in the custom model. If this occurs, follow the guidance in the error messages to diagnose and resolve the issue.

## LLM blueprint error handling

The following issues apply to blueprints and the playground.

### Vector database unlinked

If the connection with a vector database is broken, any LLM blueprint using it will be marked as `Unlinked`. Either revalidate/restore your external vector database connection or create a duplicate of the LLM blueprint and select a new database in the configuration.

### Vector database deleted

If a vector database is deleted, any LLM blueprints using it become invalid. To proceed, create a duplicate of the LLM blueprint and select a new database.

### Deployment fails

When exporting an LLM blueprint that includes a vector database to the [workshop](https://docs.datarobot.com/en/docs/workbench/nxt-registry/nxt-model-workshop/nxt-create-custom-model.html#configure-custom-model-resource-settings), if deployment fails, try increasing the resource bundle/memory.

### Custom model errors

If the custom model used in an LLM blueprint encounters an error, such as a model replacement, deletion, or access removal, the LLM blueprint is marked with an appropriate error status. Follow the provided in-app guidance to proceed.

When [adding a deployed LLM](https://docs.datarobot.com/en/docs/agentic-ai/playground-tools/build-llm-blueprints.html#add-a-deployed-llm) that supports the [Bolt-on Governance API](https://docs.datarobot.com/en/docs/api/code-first-tools/drum/structured-custom-models.html#chat), the playground uses the Bolt-on Governance API as the preferred communication method. Requests from the playground to the deployed LLM will [specify the value entered in theChat model IDfield as themodelparameter](https://docs.datarobot.com/en/docs/reference/gen-ai-ref/llm-availability.html). To disable the Bolt-on Governance API and use the predictions API instead, delete the `chat` function from the custom model and redeploy it.

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