--- title: "singlestore-sql" type: docs weight: 1 description: > A "singlestore-sql" tool executes a pre-defined SQL statement against a SingleStore database. --- ## About A `singlestore-execute-sql` tool executes a SQL statement against a SingleStore database. The specified SQL statement expects parameters in the SQL query to be in the form of placeholders `?`. ## Compatible Sources {{< compatible-sources >}} ## Example > **Note:** This tool uses parameterized queries to prevent SQL injections. > Query parameters can be used as substitutes for arbitrary expressions. > Parameters cannot be used as substitutes for identifiers, column names, table > names, or other parts of the query. ```yaml kind: tool name: search_flights_by_number type: singlestore-sql source: my-s2-instance statement: | SELECT * FROM flights WHERE airline = ? AND flight_number = ? LIMIT 10 description: | Use this tool to get information for a specific flight. Takes an airline code and flight number and returns info on the flight. Do NOT use this tool with a flight id. Do NOT guess an airline code or flight number. A airline code is a code for an airline service consisting of two-character airline designator and followed by flight number, which is 1 to 4 digit number. For example, if given CY 0123, the airline is "CY", and flight_number is "123". Another example for this is DL 1234, the airline is "DL", and flight_number is "1234". If the tool returns more than one option choose the date closes to today. Example: {{ "airline": "CY", "flight_number": "888", }} Example: {{ "airline": "DL", "flight_number": "1234", }} parameters: - name: airline type: string description: Airline unique 2 letter identifier - name: flight_number type: string description: 1 to 4 digit number ``` ### Example with Template Parameters > **Note:** This tool allows direct modifications to the SQL statement, > including identifiers, column names, and table names. **This makes it more > vulnerable to SQL injections**. Using basic parameters only (see above) is > recommended for performance and safety reasons. For more details, please check > [templateParameters](../../../documentation/configuration/tools/_index.md#template-parameters). ```yaml kind: tool name: list_table type: singlestore-sql source: my-s2-instance statement: | SELECT * FROM {{.tableName}}; description: | Use this tool to list all information from a specific table. Example: {{ "tableName": "flights", }} templateParameters: - name: tableName type: string description: Table to select from ``` ### Example with Vector Search SingleStore supports vector operations. When using an `embeddingModel` with a `singlestore-sql` tool, the tool automatically converts text parameters into a JSON string array. You can then use SingleStore's `JSON_ARRAY_PACK()` function in your SQL statement to pack this string into a binary vector format (BLOB) for vector storage and similarity search. #### Define the Embedding Model See [EmbeddingModels](../../../documentation/configuration/embedding-models/_index.md) for more information. ```yaml kind: embeddingModel name: gemini-model type: gemini model: gemini-embedding-001 apiKey: ${GOOGLE_API_KEY} dimension: 768 ``` #### Vector Ingestion Tool This tool stores both the raw text and its vector representation. It uses `valueFromParam` to hide the vector conversion logic from the LLM, ensuring the Agent only has to provide the content once. ```yaml kind: tool name: insert_doc_singlestore type: singlestore-sql source: my-s2-source statement: | INSERT INTO vector_table (id, content, embedding) VALUES (1, ?, JSON_ARRAY_PACK(?)) description: | Index new documents for semantic search in SingleStore. parameters: - name: content type: string description: The text content to store. - name: text_to_embed type: string # Automatically copies 'content' and converts it to a vector string array valueFromParam: content embeddedBy: gemini-model ``` #### Vector Search Tool This tool allows the Agent to perform a natural language search. The query string provided by the Agent is converted into a vector string array before the SQL is executed. ```yaml kind: tool name: search_docs_singlestore type: singlestore-sql source: my-s2-source statement: | SELECT id, content, DOT_PRODUCT(embedding, JSON_ARRAY_PACK(?)) AS score FROM vector_table ORDER BY score DESC LIMIT 1 description: | Search for documents in SingleStore using natural language. Returns the most semantically similar result. parameters: - name: query type: string description: The search query to be converted to a vector. embeddedBy: gemini-model ``` ## Reference | **field** | **type** | **required** | **description** | |--------------------|:--------------------------------------------:|:------------:|----------------------------------------------------------------------------------------------------------------------------------------| | type | string | true | Must be "singlestore-sql". | | source | string | true | Name of the source the SQL should execute on. | | description | string | true | Description of the tool that is passed to the LLM. | | statement | string | true | SQL statement to execute on. | | parameters | [parameters](../../../documentation/configuration/tools/_index.md#specifying-parameters) | false | List of [parameters](../../../documentation/configuration/tools/_index.md#specifying-parameters) that will be inserted into the SQL statement. | | templateParameters | [templateParameters](../../../documentation/configuration/tools/_index.md#template-parameters) | false | List of [templateParameters](../../../documentation/configuration/tools/_index.md#template-parameters) that will be inserted into the SQL statement before executing prepared statement. |