toolkit = PowerBIToolkit(
    powerbi=PowerBIDataset(dataset_id="<dataset_id>", table_names=['table1', 'table2'], credential=DefaultAzureCredential()), 
    llm=smart_llm
)
agent_executor = create_pbi_agent(
    llm=fast_llm,
    toolkit=toolkit,
    verbose=True,
)
Example: describing a table#
agent_executor.run("Describe table1")
Example: simple query on a table#
In this example, the agent actually figures out the correct query to get a row count of the table.
agent_executor.run("How many records are in table1?")
Example: running queries#
agent_executor.run("How many records are there by dimension1 in table2?")
agent_executor.run("What unique values are there for dimensions2 in table2")
Example: add your own few-shot prompts#
#fictional example
few_shots = """
Question: How many rows are in the table revenue?
DAX: EVALUATE ROW("Number of rows", COUNTROWS(revenue_details))
----
Question: How many rows are in the table revenue where year is not empty?
DAX: EVALUATE ROW("Number of rows", COUNTROWS(FILTER(revenue_details, revenue_details[year] <> "")))
----
Question: What was the average of value in revenue in dollars?
DAX: EVALUATE ROW("Average", AVERAGE(revenue_details[dollar_value]))
----
"""
toolkit = PowerBIToolkit(
    powerbi=PowerBIDataset(dataset_id="<dataset_id>", table_names=['table1', 'table2'], credential=DefaultAzureCredential()), 
    llm=smart_llm,
    examples=few_shots,
)
agent_executor = create_pbi_agent(
rtdocs_stable/api.python.langchain.com/en/stable/modules/agents/toolkits/examples/powerbi.html