TEXT).
To use the function, provide the model identifier, the request body as serialized JSON, and a LOCATION that holds AWS credentials.
For setup guidance and end-to-end examples, see Getting started with AI.
Syntax
Parameters
Make sure the
request JSON matches the syntax required by the model you select. See the Amazon Bedrock model parameters documentation for details.Return Type
TEXT
- Returns the raw Bedrock response payload as a JSON string.
- If
<request>isNULL, the function returnsNULL.
LLM Token Budget
The daily LLM token budget for each account is governed by theALTER ACCOUNT SET LLM_TOKEN_BUDGET command. If your account exceeds its allotted token budget, invocations of AWS_BEDROCK_AI_QUERY will fail until the budget is increased or the daily limit resets. The current limit and daily usage of the LLM token budget can be viewed in information_schema.quotas.
Counting tokens is done in a “best effort” manner. Some models provide the token count in the response, while others don’t. For those that don’t Firebolt estimates the token count. Supported model list:
LLM token budget accounting is not available in Firebolt Core.
Examples
Create a LOCATION with role ARN
For role-based AWS access you can additionally set an external ID. An external ID is a value you choose and control that AWS checks when Firebolt assumes your role, adding a second condition on top of your account’s unique IAM principal. Configuring one is a recommended best practice. See IAM roles.
Invoke a model using the LOCATION
Invoking the LLM on multiple values
Sentiment analysis
Check your LLM token quota usage
LLM_TOKEN_BUDGET row to view current usage and limits.