Create a Notebook in Personal Space

This example creates a notebook in personal space. Open Claude Desktop, and enter the following prompt:

Create a notebook named myrag in personal space. In this notebook, write a python code to create a RAG application. The RAG application will use arxiv papers as data source, SingleStore as vector database, Gemma model as the LLM, and use LangChain orchestration framework.

Once the prompt is submitted, the following tools will run to perform the relative task:

• choose_organization: Selects the organization.

• set_organization: Sets the organization.

• create_notebook_file: Creates a notebook with a comprehensive RAG application that uses ArXiv papers, SingleStore as the vector database, Gemma as the LLM, and LangChain orchestration framework.

• upload_notebook_file: Uploads the notebook to your personal space with the name myrag.

The notebook is created with the MCP integration. You can view the notebook in your personal space in the Cloud Portal.

Query a Database

This example creates a table, ingests data into the table, and queries the inserted data.Before proceeding with this example, create a database named sales and an associated table. Open Claude Desktop, and update your workspace, workspace group, and organization details in the following prompt:

Create a new database named sales in <your_workspace> under <your_workspace_group> of <your_organization>,  and then create a table called SalesData with the following columns:
- Date: Text
- Store_ID: Big integer (20), nullable
- ProductID: Text
- Product_Name: Text,
- Product_Category: Text
- Quantity_Sold: Big integer (20), nullable
- Price: Float, nullable
- Total_Sales: Float, nullable

Once the prompt is submitted, the following tools will run to perform the relative task:

• choose_organization: Checks the organization information.

• set_organization: Sets the organization to the specified organization.

• workspace_groups_info: Checks and finds information on the specified workspace group.

• workspaces_info: Checks and finds information on the specified workspace.

• run_sql: Creates the specified database.

• run_sql: Creates the specified tables.

To ingest data using a pipeline, enter the following prompt:

Create a pipeline SalesData_pipeline using 's3://singlestoreloaddata/SalesData/*.csv'

Once the prompt is submitted, the following tool will run to perform the relative task:

• run_sql: Creates the pipeline in the sales database.

To start the pipeline, enter the following prompt:

Start the pipeline

Once the prompt is submitted, the following tool will run to perform the relative task:

• run_sql: Starts the pipeline.

To query the data in the table, enter the following prompt:

Identify the top three stores with the highest sales in the Electronics category.

Once the prompt is submitted, the following tool will run to perform the relative task:

• run_sql: Queries the SalesData table to find the top three stores with the highest sales in the Electronics category.

Create a Scheduled Job

This example creates a notebook in shared space and schedules the job. Open Claude Desktop, and update your workspace, workspace group, and organization details in the following prompt:

Create a notebook named SalesData in the shared space. In the notebook, use the SalesData table from the sales database in <your_workspace> under <your_workspace_group> of <your_organization>, to generate appropriate visualizations based on the data.

Once the prompt is submitted, the following tools will run to perform the relative task:

• choose_organization: Checks the organization information.

• set_organization: Sets the organization to the specified organization.

• workspace_groups_info: Checks and finds information on the specified workspace group.

• workspaces_info: Checks and finds information on the specified workspace.

• run_sql: Explores SalesData table structure.

• run_sql: Understands the sample data of the table.

• run_sql: Understands the aggregate information of the table.

• run_sql: Explores the distinct product categories.

• create_notebook_file: Creates the SalesData notebook file.

• upload_notebook_file: Uploads the SalesData notebook file in shared space.

The notebook is created in the shared space in the Cloud Portal.

To schedule the notebook, enter the following prompt:

Create a schedule job using the SalesData notebook, with the name of job as SalesJob, start executions "Now", with "Weekly" "Recurring" schedule mode. Save all the execution results.

Once the prompt is submitted, the following tool will run to perform the relative task:

• create_job_from_notebook: Creates a scheduled job using SalesData notebook in weekly recurring schedule mode.