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https://github.com/hwchase17/langchain
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06e524416c
# Powerbi API wrapper bug fix + integration tests - Bug fix by removing `TYPE_CHECKING` in in utilities/powerbi.py - Added integration test for power bi api in utilities/test_powerbi_api.py - Added integration test for power bi agent in agent/test_powerbi_agent.py - Edited .env.examples to help set up power bi related environment variables - Updated demo notebook with working code in docs../examples/powerbi.ipynb - AzureOpenAI -> ChatOpenAI Notes: Chat models (gpt3.5, gpt4) are much more capable than davinci at writing DAX queries, so that is important to getting the agent to work properly. Interestingly, gpt3.5-turbo needed the examples=DEFAULT_FEWSHOT_EXAMPLES to write consistent DAX queries, so gpt4 seems necessary as the smart llm. Fixes #4325 ## Before submitting Azure-core and Azure-identity are necessary dependencies check integration tests with the following: `pytest tests/integration_tests/utilities/test_powerbi_api.py` `pytest tests/integration_tests/agent/test_powerbi_agent.py` You will need a power bi account with a dataset id + table name in order to test. See .env.examples for details. ## Who can review? @hwchase17 @vowelparrot --------- Co-authored-by: aditya-pethe <adityapethe1@gmail.com>
48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
import pytest
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from langchain.agents.agent_toolkits import PowerBIToolkit, create_pbi_agent
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from langchain.chat_models import ChatOpenAI
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from langchain.utilities.powerbi import PowerBIDataset
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from langchain.utils import get_from_env
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def azure_installed() -> bool:
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try:
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from azure.core.credentials import TokenCredential # noqa: F401
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from azure.identity import DefaultAzureCredential # noqa: F401
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return True
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except Exception as e:
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print(f"azure not installed, skipping test {e}")
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return False
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@pytest.mark.skipif(not azure_installed(), reason="requires azure package")
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def test_daxquery() -> None:
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from azure.identity import DefaultAzureCredential
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DATASET_ID = get_from_env("", "POWERBI_DATASET_ID")
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TABLE_NAME = get_from_env("", "POWERBI_TABLE_NAME")
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NUM_ROWS = get_from_env("", "POWERBI_NUMROWS")
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fast_llm = ChatOpenAI(
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temperature=0.5, max_tokens=1000, model_name="gpt-3.5-turbo", verbose=True
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)
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smart_llm = ChatOpenAI(
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temperature=0, max_tokens=100, model_name="gpt-4", verbose=True
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)
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toolkit = PowerBIToolkit(
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powerbi=PowerBIDataset(
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dataset_id=DATASET_ID,
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table_names=[TABLE_NAME],
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credential=DefaultAzureCredential(),
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),
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llm=smart_llm,
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)
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agent_executor = create_pbi_agent(llm=fast_llm, toolkit=toolkit, verbose=True)
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output = agent_executor.run(f"How many rows are in the table, {TABLE_NAME}")
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assert NUM_ROWS in output
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