singlestore-sql

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

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

kind: embeddingModel
name: gemini-model
type: gemini
model: gemini-embedding-001
apiKey: ${GOOGLE_API_KEY}
dimension: 768

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

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