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