Aparavi AQL
A RocketRide tool node that lets an agent retrieve Aparavi STORE metadata by asking questions in plain English. Pick it when the data is governed by an Aparavi server rather than stored in one of RocketRide's managed databases.
About Aparavi
Aparavi is a data governance platform whose server exposes a query API over metadata in its STORE table. This node uses Aparavi Query Language (AQL), an SQL-like language, to retrieve those rows without requiring the calling agent to construct the query itself.
What it does
The node is a pure tool node: it has no pipeline lanes. Its required LLM turns a natural-language request into a SELECT-only AQL query over the fixed STORE schema, then the node sends that query to the configured Aparavi server. Pick it over rocketride_sql when the authoritative data is Aparavi file metadata; use the SQL node for the managed relational tenant database.
Connections
| Connection | Required | Description |
|---|---|---|
| llm | yes | Generates AQL from natural-language questions. |
As a tool
The functions are registered under the bare names below; this node defines no configurable server-name prefix. question arguments must be non-empty strings in a JSON object.
| Function | Description |
|---|---|
| get_data | Generates safe AQL for required question, executes it, and returns STORE rows. |
| get_aql | Generates AQL for required question without executing it. |
| get_schema | Returns the fixed STORE table schema; use only after retrieval fails or is unexpected. |
get_data returns {rows, aql, count} when successful. If the client was not initialized, a generated query is unsafe, generation never succeeds, or all execution retries fail, it returns {error, aql, rows: []}. Invalid tool input raises ValueError. The node tries generation and execution up to three times; after an API error, the next LLM attempt receives the failed AQL and error.
get_aql returns {aql} and does not run the safety check or contact the API; invalid input or an LLM failure raises. get_schema accepts an empty object and returns {store: "STORE", columns: [...]}, where each column has a name, type, and description.
Configuration
The single built-in profile has no endpoint defaults. Supply the Aparavi server connection, then describe the data in terms that help the required LLM select the correct fixed STORE fields. Query retry count and result limit are fixed in the implementation rather than configurable fields.
Aparavi Server URL
Provide the base URL of the Aparavi server, including its scheme, for example https://aparavi.example.com. The node removes a trailing slash before adding its database-query path. Change this value when the target Aparavi deployment changes; an empty or unreachable URL leaves the tool client uninitialized or causes its HTTP calls to return errors after a 30-second timeout.
Username and password
Username and Password are sent as HTTP Basic Auth on every Aparavi database-query request. Set them to credentials accepted by the configured server. Change both together when switching servers or users; a mismatched endpoint and credentials becomes an API HTTP or connection error returned by get_data after its retry loop.
Data description
Data description is empty by default and is added as context to the LLM that writes AQL. Describe the collection's purpose, vocabulary, and useful metadata conventions when they are not evident from the fixed schema. This can improve query selection without giving the model a new table: STORE remains the only table in the generated-query prompt.
Authentication
The node uses HTTP Basic Auth with the configured username and password for the Aparavi database-query API. It sends POST requests to /server/api/v3/database/query and does not use a separate token field.
Limitations
This node runs on the RocketRide engine host and does not support remote execution. The engine host must be able to reach the configured Aparavi server using the supplied Basic Auth credentials. It only retrieves from the fixed STORE schema: the safety check permits one SELECT statement, rejects embedded multi-statement input, and blocks mutation and execution keywords before sending AQL to the server. The API request uses a fixed 250-object limit and a 30-second timeout.
Notes
Query generation and result normalization
The LLM prompt supplies the fixed STORE schema, AQL syntax rules, and examples. It asks for LIMIT 250 unless the question specifies another limit, while the HTTP client itself requests at most 250 objects. Accidental Markdown fences in the LLM output are removed. Timestamp values above 10,000,000,000 in the known Aparavi date fields are treated as milliseconds and normalized to seconds in returned rows.
Upstream docs
Schema
| Field | Type | Description | Default |
|---|---|---|---|
aparavi.db_description | string | Data description What is this data used for? Describe its content and purpose, this helps the LLM generate more accurate AQL queries. | "" |
aparavi.password | string | Password Aparavi login password | |
aparavi.profile | string | "default" | |
aparavi.url | string | Aparavi Server URL Base URL of the Aparavi server, e.g. https://aparavi.example.com | "" |
aparavi.user | string | Username Aparavi login username | "" |