mirror of
https://github.com/hwchase17/langchain
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1cb04f2b26
# PowerBI major refinement in working of tool and tweaks in the rest I've gained some experience with more complex sets and the earlier implementation had too many tries by the agent to create DAX, so refactored the code to run the LLM to create dax based on a question and then immediately run the same against the dataset, with retries and a prompt that includes the error for the retry. This works much better! Also did some other refactoring of the inner workings, making things clearer, more concise and faster.
66 lines
1.5 KiB
Python
66 lines
1.5 KiB
Python
"""Test the public API of the tools package."""
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from langchain.tools import __all__ as public_api
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_EXPECTED = [
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"AIPluginTool",
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"APIOperation",
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"BaseTool",
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"BaseTool",
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"BaseTool",
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"BingSearchResults",
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"BingSearchRun",
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"ClickTool",
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"CopyFileTool",
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"CurrentWebPageTool",
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"DeleteFileTool",
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"DuckDuckGoSearchResults",
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"DuckDuckGoSearchRun",
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"ExtractHyperlinksTool",
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"ExtractTextTool",
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"FileSearchTool",
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"GetElementsTool",
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"GmailCreateDraft",
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"GmailGetMessage",
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"GmailGetThread",
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"GmailSearch",
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"GmailSendMessage",
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"GooglePlacesTool",
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"GoogleSearchResults",
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"GoogleSearchRun",
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"GoogleSerperResults",
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"GoogleSerperRun",
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"HumanInputRun",
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"IFTTTWebhook",
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"InfoPowerBITool",
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"ListDirectoryTool",
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"ListPowerBITool",
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"MetaphorSearchResults",
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"MoveFileTool",
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"NavigateBackTool",
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"NavigateTool",
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"OpenAPISpec",
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"OpenWeatherMapQueryRun",
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"QueryPowerBITool",
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"ReadFileTool",
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"SceneXplainTool",
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"ShellTool",
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"SteamshipImageGenerationTool",
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"StructuredTool",
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"Tool",
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"VectorStoreQATool",
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"VectorStoreQAWithSourcesTool",
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"WikipediaQueryRun",
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"WolframAlphaQueryRun",
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"WriteFileTool",
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"ZapierNLAListActions",
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"ZapierNLARunAction",
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"tool",
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"YouTubeSearchTool",
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]
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def test_public_api() -> None:
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"""Test for regressions or changes in the public API."""
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# Check that the public API is as expected
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assert sorted(public_api) == sorted(_EXPECTED)
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