Conversational Analytics API has the following known limitations on the number of data sources, style of visualizations, and size of datasets.
Data source limitations
This section describes the constraints and behaviors of the Conversational Analytics API when you connect to and query Looker and database sources— AlloyDB for PostgreSQL, Cloud SQL for MySQL, Cloud SQL for PostgreSQL, and Spanner.
Looker data source limitations
When you connect to a Looker data source, note the following:
- You can query any included Explore in a conversation.
- An agent can only query one Explore at a time. It is not possible to perform queries across multiple Explores simultaneously.
- An agent can query multiple Explores in the same conversation.
An agent can query multiple Explores in a conversation that includes questions with multiple parts, or in conversations that include follow-up questions.
For example: A user connects two Explores, one called
cat-exploreand one calleddog-explore. The user inputs the question "What's greater: the count of cats or the count of dogs?" This would create two queries: one to count the number of cats incat-exploreand one to count the number of dogs indog-explore. The agent compares the number from both queries after completing both queries.The
QueryDatamethod does not support BigQuery or Looker data sources.
Database data source limitations
When you connect to an AlloyDB, Cloud SQL for MySQL, Cloud SQL for PostgreSQL, or Spanner data sources, consider the following:
Data agents access the data using the credential of the user who is interacting with the data agent. If a user accesses a shared data agent for which they don't have access to the agent's configured tables, then the data agent can't access those tables.
The table selection for the data agent guides your agent about which tables to focus on. Table selection isn't a security setting. Even if you specify that the data source can only pull information from certain tables—like
table1andtable2—the system might still return data from an unintended table (table3) if the user running the query has general permissions to view the content oftable3in the same database.
Visualization limitations
- These visualization types are fully supported: Line chart, area chart, bar (horizontal, vertical, stacked) chart, scatterplots, pie chart
- These visualization types are partially supported and may exhibit unexpected behavior: Maps, heatmaps, charts with tooltips
Data processing limitations
- For Looker data sources, the Conversational Analytics API can return a maximum of 5,000 rows per query.
- For BigQuery data sources, the Conversational Analytics API limits data queries to 500 GB of bytes processed.
- For AlloyDB, Cloud SQL for MySQL, Cloud SQL for PostgreSQL, and Spanner data sources, the Conversational Analytics API can return a maximum of 1,000 rows per query.
- The Conversational Analytics API's Python-based reasoning and content retrieval capabilities can accommodate time complexities of up to
O(100k)rows. - Querying large amounts of data can cause reduced reasoning accuracy in data agents.
- The Conversational Analytics API has a maximum token output length of 8,192 tokens. Querying large amounts of data can return a
MAX_TOKENSerror. - The data returned within the
DataResultfield of a system message is subject to a size limit. Data results are truncated to a maximum of 3,000,000 bytes. This truncation process keeps as many full rows as possible within this size constraint.
Query limitations
- BigQuery's flexible column names feature is not supported.
- Structs in BigQuery are supported but may sometimes fail.
- For Looker data sources, the API cannot set the value of a filter-only field that is defined by using the LookML
parameterparameter. - Using the Conversational Analytics API to connect to a private IP Looker (Google Cloud core) instance using Looker Studio Pro when that Looker (Google Cloud core) instance is inside a VPC Service Controls perimeter is not a supported configuration and does not meet VPC Service Controls compliance requirements.
- For connections to Looker (Google Cloud core) instances with private IP configurations, Conversational Analytics API does not support Looker (Google Cloud core) instances that are configured to use CMEK or VPC Service Controls.
- For Conversational Analytics API resources, CMEK is supported only for Looker data sources.
- Conversational Analytics API doesn't work well with Looker Studio data sources that have field editing in reports disabled in because this setting prevents Conversational Analytics from creating calculated fields.
When a failure occurs during query validation or execution, the Conversation Analytics API may automatically retry the operation by generating a corrected query. This kind of retry will be attempted a maximum of three times per request.
If a query fails because of permission or authentication issues, the Conversational Analytics API won't retry the query. Retries are non-deterministic; if the error message suggests that a query is unrecoverable, then the API won't try the query again, even if it is still below the limit of three errors per request.
Conversational Analytics API has a maximum of 10 Queries Per Second (QPS). This results in a maximum of 600 Queries Per Minute (QPM) per project, and 600 QPM per user per project.
Conversational Analytics API for AlloyDB, Cloud SQL for MySQL, Cloud SQL for PostgreSQL, and Spanner has a 50 QPM limit per project. To increase these limits, contact Google Cloud Customer Care.
Question types limitations
Conversational Analytics API supports questions that can be answered by a single visualization, for example:
- Metric trends over time
- Breakdown or distribution of a metric by dimension
- Unique values for one or more dimensions
- Single metric values
- The top dimension values by metric
Conversational Analytics API doesn't yet support questions that can only be answered with the following types of complicated visualizations:
- Prediction and forecasting
- Advanced statistical analysis, including correlation and anomaly detection