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## Description --- This introduces a breaking change. The bigquery-forecast tool will now enforce the allowed datasets setting from its BigQuery source configuration. Previously, this setting had no effect on the tool. ## PR Checklist --- > Thank you for opening a Pull Request! Before submitting your PR, there are a > few things you can do to make sure it goes smoothly: - [ ] Make sure you reviewed [CONTRIBUTING.md](https://github.com/googleapis/genai-toolbox/blob/main/CONTRIBUTING.md) - [ ] Make sure to open an issue as a [bug/issue](https://github.com/googleapis/genai-toolbox/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) - [ ] Make sure to add `!` if this involve a breaking change 🛠️ Fixes #<issue_number_goes_here> --------- Co-authored-by: Yuan Teoh <45984206+Yuan325@users.noreply.github.com>
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title, type, weight, description, aliases
| title | type | weight | description | aliases | |
|---|---|---|---|---|---|
| bigquery-forecast | docs | 1 | A "bigquery-forecast" tool forecasts time series data in BigQuery. |
|
About
A bigquery-forecast tool forecasts time series data in BigQuery.
It's compatible with the following sources:
bigquery-forecast constructs and executes a SELECT * FROM AI.FORECAST(...)
query based on the provided parameters:
- history_data (string, required): This specifies the source of the historical time series data. It can be either a fully qualified BigQuery table ID (e.g., my-project.my_dataset.my_table) or a SQL query that returns the data.
- timestamp_col (string, required): The name of the column in your history_data that contains the timestamps.
- data_col (string, required): The name of the column in your history_data that contains the numeric values to be forecasted.
- id_cols (array of strings, optional): If you are forecasting multiple time series at once (e.g., sales for different products), this parameter takes an array of column names that uniquely identify each series. It defaults to an empty array if not provided.
- horizon (integer, optional): The number of future time steps you want to predict. It defaults to 10 if not specified.
The tool's behavior regarding these parameters is influenced by the allowedDatasets restriction on the bigquery source:
- Without
allowedDatasetsrestriction: The tool can use any table or query for thehistory_dataparameter. - With
allowedDatasetsrestriction: The tool verifies that thehistory_dataparameter only accesses tables within the allowed datasets. Ifhistory_datais a table ID, the tool checks if the table's dataset is in the allowed list. Ifhistory_datais a query, the tool performs a dry run to analyze the query and rejects it if it accesses any table outside the allowed list.
Example
tools:
forecast_tool:
kind: bigquery-forecast
source: my-bigquery-source
description: Use this tool to forecast time series data in BigQuery.
Sample Prompt
You can use the following sample prompts to call this tool:
- Can you forecast the history time series data in bigquery table
bqml_tutorial.google_analytic? Use project_idmyproject. - What are the future
total_visitsin bigquery tablebqml_tutorial.google_analytic?
Reference
| field | type | required | description |
|---|---|---|---|
| kind | string | true | Must be "bigquery-forecast". |
| source | string | true | Name of the source the forecast tool should execute on. |
| description | string | true | Description of the tool that is passed to the LLM. |