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class langchain.tools.FileSearchTool(*, name='file_search', description='Recursively search for files in a subdirectory that match the regex pattern', args_schema=<class 'langchain.tools.file_management.file_search.FileSearchInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-42
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – root_dir (Optional[str]) – Return type None attribute args_schema: Type[pydantic.main.BaseModel] = <class 'langchain.tools.file_management.file_search.FileSearchInput'> Pydantic model class to validate and parse the...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-43
class langchain.tools.GetElementsTool(*, name='get_elements', description='Retrieve elements in the current web page matching the given CSS selector', args_schema=<class 'langchain.tools.playwright.get_elements.GetElementsToolInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_too...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-44
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – sync_browser (Optional['SyncBrowser']) – async_browser (Optional['AsyncBrowser']) – Return type None attribute args_schema: Type[BaseModel] = <class 'langchain.tools.playwright.get_elements.GetElementsToolInput'> P...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-45
class langchain.tools.GmailCreateDraft(*, name='create_gmail_draft', description='Use this tool to create a draft email with the provided message fields.', args_schema=<class 'langchain.tools.gmail.create_draft.CreateDraftSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_e...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-46
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_resource (Resource) – Return type None attribute args_schema: Type[langchain.tools.gmail.create_draft.CreateDraftSchema] = <class 'langchain.tools.gmail.create_draft.CreateDraftSchema'> Pydantic model class to v...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-47
class langchain.tools.GmailGetMessage(*, name='get_gmail_message', description='Use this tool to fetch an email by message ID. Returns the thread ID, snipet, body, subject, and sender.', args_schema=<class 'langchain.tools.gmail.get_message.SearchArgsSchema'>, return_direct=False, verbose=False, callbacks=None, callbac...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-48
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_resource (Resource) – Return type None attribute args_schema: Type[langchain.tools.gmail.get_message.SearchArgsSchema] = <class 'langchain.tools.gmail.get_message.SearchArgsSchema'> Pydantic model class to valid...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-49
class langchain.tools.GmailGetThread(*, name='get_gmail_thread', description='Use this tool to search for email messages. The input must be a valid Gmail query. The output is a JSON list of messages.', args_schema=<class 'langchain.tools.gmail.get_thread.GetThreadSchema'>, return_direct=False, verbose=False, callbacks=...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-50
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_resource (Resource) – Return type None attribute args_schema: Type[langchain.tools.gmail.get_thread.GetThreadSchema] = <class 'langchain.tools.gmail.get_thread.GetThreadSchema'> Pydantic model class to validate ...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-51
class langchain.tools.GmailSearch(*, name='search_gmail', description='Use this tool to search for email messages or threads. The input must be a valid Gmail query. The output is a JSON list of the requested resource.', args_schema=<class 'langchain.tools.gmail.search.SearchArgsSchema'>, return_direct=False, verbose=Fa...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-52
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_resource (Resource) – Return type None attribute args_schema: Type[langchain.tools.gmail.search.SearchArgsSchema] = <class 'langchain.tools.gmail.search.SearchArgsSchema'> Pydantic model class to validate and pa...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-53
class langchain.tools.GmailSendMessage(*, name='send_gmail_message', description='Use this tool to send email messages. The input is the message, recipents', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, api_resource=None)[source] Bases: langchain...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-54
api_resource (Resource) – Return type None attribute description: str = 'Use this tool to send email messages. The input is the message, recipents' Used to tell the model how/when/why to use the tool. You can provide few-shot examples as a part of the description. attribute name: str = 'send_gmail_message' The uniqu...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-55
Bases: langchain.tools.base.BaseTool Tool that adds the capability to query the Google places API. Parameters name (str) – description (str) – args_schema (Type[pydantic.main.BaseModel]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchai...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-56
attribute args_schema: Type[pydantic.main.BaseModel] = <class 'langchain.tools.google_places.tool.GooglePlacesSchema'> Pydantic model class to validate and parse the tool’s input arguments. class langchain.tools.GoogleSearchResults(*, name='Google Search Results JSON', description='A wrapper around Google Search. Usef...
https://api.python.langchain.com/en/latest/modules/tools.html
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return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.b...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-58
class langchain.tools.GoogleSearchRun(*, name='google_search', description='A wrapper around Google Search. Useful for when you need to answer questions about current events. Input should be a search query.', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=...
https://api.python.langchain.com/en/latest/modules/tools.html
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handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_wrapper (langchain.utilities.google_search.GoogleSearchAPIWrapper) – Return type None attribute api_wrapper: langchain.utilities.google_search.GoogleSearchAPIWrapper [Required] class langchain.tools.GoogleSerper...
https://api.python.langchain.com/en/latest/modules/tools.html
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Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks...
https://api.python.langchain.com/en/latest/modules/tools.html
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class langchain.tools.GoogleSerperRun(*, name='google_serper', description='A low-cost Google Search API.Useful for when you need to answer questions about current events.Input should be a search query.', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=Fals...
https://api.python.langchain.com/en/latest/modules/tools.html
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handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_wrapper (langchain.utilities.google_serper.GoogleSerperAPIWrapper) – Return type None attribute api_wrapper: langchain.utilities.google_serper.GoogleSerperAPIWrapper [Required] class langchain.tools.HumanInputRu...
https://api.python.langchain.com/en/latest/modules/tools.html
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description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-64
class langchain.tools.IFTTTWebhook(*, name, description, args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, url)[source] Bases: langchain.tools.base.BaseTool IFTTT Webhook. Parameters name (str) – name of the tool description (str) – description of the...
https://api.python.langchain.com/en/latest/modules/tools.html
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Return type None attribute url: str [Required] class langchain.tools.InfoPowerBITool(*, name='schema_powerbi', description='\nΒ Β Β  Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables.\nΒ Β Β  Be sure that the tables actually exist by calling list_tables_powerbi fir...
https://api.python.langchain.com/en/latest/modules/tools.html
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verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-67
class langchain.tools.InfoSQLDatabaseTool(*, name='sql_db_schema', description='\nΒ Β Β  Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables.Β Β Β  \n\nΒ Β Β  Example Input: "table1, table2, table3"\nΒ Β Β  ', args_schema=None, return_direct=False, verbose=False, callbacks=...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-68
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – db (langchain.sql_database.SQLDatabase) – Return type None class langchain.tools.InfoSparkSQLTool(*, name='schema_sql_db', description='\nΒ ...
https://api.python.langchain.com/en/latest/modules/tools.html
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Tool for getting metadata about a Spark SQL. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – c...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-70
Bases: langchain.tools.base.BaseTool Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-71
attribute mode: str [Required] class langchain.tools.JsonGetValueTool(*, name='json_spec_get_value', description='\nΒ Β Β  Can be used to see value in string format at a given path.\nΒ Β Β  Before calling this you should be SURE that the path to this exists.\nΒ Β Β  The input is a text representation of the path to the dict in...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-72
verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-73
class langchain.tools.JsonListKeysTool(*, name='json_spec_list_keys', description='\nΒ Β Β  Can be used to list all keys at a given path. \nΒ Β Β  Before calling this you should be SURE that the path to this exists.\nΒ Β Β  The input is a text representation of the path to the dict in Python syntax (e.g. data["key1"][0]["key2"]...
https://api.python.langchain.com/en/latest/modules/tools.html
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verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-75
Parameters name (str) – description (str) – args_schema (Type[pydantic.main.BaseModel]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.Base...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-76
Used to tell the model how/when/why to use the tool. You can provide few-shot examples as a part of the description. attribute name: str = 'list_directory' The unique name of the tool that clearly communicates its purpose. class langchain.tools.ListPowerBITool(*, name='list_tables_powerbi', description='Input is an em...
https://api.python.langchain.com/en/latest/modules/tools.html
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verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-78
Bases: langchain.tools.sql_database.tool.BaseSQLDatabaseTool, langchain.tools.base.BaseTool Tool for getting tables names. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.b...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-79
Return type None class langchain.tools.ListSparkSQLTool(*, name='list_tables_sql_db', description='Input is an empty string, output is a comma separated list of tables in the Spark SQL.', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, db)[source] B...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-80
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – db (langchain.utilities.spark_sql.SparkSQL) – Return type None class langchain.tools.MetaphorSearchResults(*, name='metaphor_search_results_json', description='A wrapper around Metaphor Search. Input should be a Meta...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-81
return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.b...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-82
class langchain.tools.MoveFileTool(*, name='move_file', description='Move or rename a file from one location to another', args_schema=<class 'langchain.tools.file_management.move.FileMoveInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, root_dir=None)[source] ...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-83
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – root_dir (Optional[str]) – Return type None attribute args_schema: Type[pydantic.main.BaseModel] = <class 'langchain.tools.file_management.move.FileMoveInput'> Pydantic model class to validate and parse the tool’s i...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-84
class langchain.tools.NavigateBackTool(*, name='previous_webpage', description='Navigate back to the previous page in the browser history', args_schema=<class 'pydantic.main.BaseModel'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, sync_browser=None, async_browser=...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-85
handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – sync_browser (Optional['SyncBrowser']) – async_browser (Optional['AsyncBrowser']) – Return type None attribute args_schema: Type[BaseModel] = <class 'pydantic.main.BaseModel'> Pydantic model class to validate and p...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-86
class langchain.tools.NavigateTool(*, name='navigate_browser', description='Navigate a browser to the specified URL', args_schema=<class 'langchain.tools.playwright.navigate.NavigateToolInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, sync_browser=None, async_...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-87
sync_browser (Optional['SyncBrowser']) – async_browser (Optional['AsyncBrowser']) – Return type None attribute args_schema: Type[BaseModel] = <class 'langchain.tools.playwright.navigate.NavigateToolInput'> Pydantic model class to validate and parse the tool’s input arguments. attribute description: str = 'Navigate a...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-88
class langchain.tools.OpenAPISpec(*, openapi='3.1.0', info, jsonSchemaDialect=None, servers=[Server(url='/', description=None, variables=None)], paths=None, webhooks=None, components=None, security=None, tags=None, externalDocs=None)[source] Bases: openapi_schema_pydantic.v3.v3_1_0.open_api.OpenAPI OpenAPI Model that ...
https://api.python.langchain.com/en/latest/modules/tools.html
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webhooks (Optional[Dict[str, Union[openapi_schema_pydantic.v3.v3_1_0.path_item.PathItem, openapi_schema_pydantic.v3.v3_1_0.reference.Reference]]]) – components (Optional[openapi_schema_pydantic.v3.v3_1_0.components.Components]) – security (Optional[List[Dict[str, List[str]]]]) – tags (Optional[List[openapi_schema_py...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-90
langchain.utilities.openapi.OpenAPISpec classmethod from_spec_dict(spec_dict)[source] Get an OpenAPI spec from a dict. Parameters spec_dict (dict) – Return type langchain.utilities.openapi.OpenAPISpec classmethod from_text(text)[source] Get an OpenAPI spec from a text. Parameters text (str) – Return type langchain....
https://api.python.langchain.com/en/latest/modules/tools.html
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path (str) – method (str) – Return type str get_methods_for_path(path)[source] Return a list of valid methods for the specified path. Parameters path (str) – Return type List[str] get_operation(path, method)[source] Get the operation object for a given path and HTTP method. Parameters path (str) – method (str) – ...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-92
Parameters path (str) – Return type List[openapi_schema_pydantic.v3.v3_1_0.parameter.Parameter] get_referenced_schema(ref)[source] Get a schema (or nested reference) or err. Parameters ref (openapi_schema_pydantic.v3.v3_1_0.reference.Reference) – Return type openapi_schema_pydantic.v3.v3_1_0.schema.Schema get_reques...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-93
Parameters schema (Union[openapi_schema_pydantic.v3.v3_1_0.reference.Reference, openapi_schema_pydantic.v3.v3_1_0.schema.Schema]) – Return type openapi_schema_pydantic.v3.v3_1_0.schema.Schema classmethod parse_obj(obj)[source] Parameters obj (dict) – Return type langchain.utilities.openapi.OpenAPISpec property base_...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-94
Bases: langchain.tools.base.BaseTool Tool that adds the capability to query using the OpenWeatherMap API. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackH...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-95
class langchain.tools.PubmedQueryRun(*, name='PubMed', description='A wrapper around PubMed.org Useful for when you need to answer questions about Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance, Statistics, Electrical Engineering, and Economics from scientific articles on PubMed.org....
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-96
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]]]) – api_wrapper (langchain.utilities.pupmed.PubMedAPIWrapper) – Return type None attribute api_wrapper: langchain.utilities.pupmed.PubMedAPIWra...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-97
Bases: langchain.tools.base.BaseTool A tool for running python code in a REPL. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callback...
https://api.python.langchain.com/en/latest/modules/tools.html
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attribute sanitize_input: bool = True class langchain.tools.PythonREPLTool(*, name='Python_REPL', description='A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`.', args_schema=None, return_dir...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-99
verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-100
class langchain.tools.QueryCheckerTool(*, name='query_checker_sql_db', description='\nΒ Β Β  Use this tool to double check if your query is correct before executing it.\nΒ Β Β  Always use this tool before executing a query with query_sql_db!\nΒ Β Β  ', args_schema=None, return_direct=False, verbose=False, callbacks=None, callba...
https://api.python.langchain.com/en/latest/modules/tools.html
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just reproduce the original query.', llm, llm_chain)[source]
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-102
Bases: langchain.tools.spark_sql.tool.BaseSparkSQLTool, langchain.tools.base.BaseTool Use an LLM to check if a query is correct. Adapted from https://www.patterns.app/blog/2023/01/18/crunchbot-sql-analyst-gpt/ Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_...
https://api.python.langchain.com/en/latest/modules/tools.html
1a14bb6b1a14-103
template (str) – llm (langchain.base_language.BaseLanguageModel) – llm_chain (langchain.chains.llm.LLMChain) – Return type None attribute llm: langchain.base_language.BaseLanguageModel [Required] attribute llm_chain: langchain.chains.llm.LLMChain [Required] attribute template: str = '\n{query}\nDouble check the Sp...
https://api.python.langchain.com/en/latest/modules/tools.html
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class langchain.tools.QueryPowerBITool(*, name='query_powerbi', description='\nΒ Β Β  Input to this tool is a detailed question about the dataset, output is a result from the dataset. It will try to answer the question using the dataset, and if it cannot, it will ask for clarification.\n\nΒ Β Β  Example Input: "How many rows...
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> are used in the text below it means that those values need to be replaced by table, columns or other things. If the question is not something you can answer with a DAX query, reply with "I cannot answer this" and the question will be escalated to a human.\n\nSome DAX functions return a table instead of a scalar, and ...
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<table> - At the most basic level, a DAX query is an EVALUATE statement containing a table expression. At least one EVALUATE statement is required, however, a query can contain any number of EVALUATE statements.\nEVALUATE <table> ORDER BY <expression> ASC or DESC - The optional ORDER BY keyword defines one or more expr...
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and are valid for all EVALUATE statements in the query. Definitions can be variables, measures, tables1, and columns1. Definitions can reference other definitions that appear before or after the current definition. At least one definition is required if the DEFINE keyword is included in a query.\nMEASURE <table name>[<...
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of the table. For example, [Amount] > 0 or [Region] = "France"\nROW(<name>, <expression>) - Returns a table with a single row containing values that result from the expressions given to each column.\nDISTINCT(<column>) - Returns a one-column table that contains the distinct values from the specified column. In other wo...
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uses the numeric values in a column. Functions names with an X in it can include a expression as an argument, this will be evaluated for each row in the table and the result will be used in the regular function calculation, these are the functions:\nCOUNT(<column>), COUNTA(<column>), COUNTX(<table>,<expression>), COUNT...
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MINA(<column>), MINX(<table>,<expression>) - these are all variantions of min functions.\nPRODUCT(<column>), PRODUCTX(<table>,<expression>) - these are all variantions of product functions.\nSUM(<column>), SUMX(<table>,<expression>) - these are all variantions of sum functions.\n\nDate and time functions:\nDATE(year, m...
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DAY(<date>), HOUR(<date>), MINUTE(<date>), SECOND(<date>) - Returns the part of the date for the specified date.\n\nFinally, make sure to escape double quotes with a single backslash, and make sure that only table names have single quotes around them, while names of measures or the values of columns that you want to co...
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examples='\nQuestion: How many rows are in the table <table>?\nDAX: EVALUATE ROW("Number of rows", COUNTROWS(<table>))\n----\nQuestion: How many rows are in the table <table> where <column> is not empty?\nDAX: EVALUATE ROW("Number of rows", COUNTROWS(FILTER(<table>, <table>[<column>] <> "")))\n----\nQuestion: What was ...
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Bases: langchain.tools.base.BaseTool Tool for querying a Power BI Dataset. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.ba...
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max_iterations (int) – Return type None attribute examples: Optional[str] = '\nQuestion: How many rows are in the table <table>?\nDAX: EVALUATE ROW("Number of rows", COUNTROWS(<table>))\n----\nQuestion: How many rows are in the table <table> where <column> is not empty?\nDAX: EVALUATE ROW("Number of rows", COUNTROWS(F...
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attribute powerbi: langchain.utilities.powerbi.PowerBIDataset [Required] attribute session_cache: Dict[str, Any] [Optional]
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attribute template: Optional[str] = '\nAnswer the question below with a DAX query that can be sent to Power BI. DAX queries have a simple syntax comprised of just one required keyword, EVALUATE, and several optional keywords: ORDER BY, START AT, DEFINE, MEASURE, VAR, TABLE, and COLUMN. Each keyword defines a statement ...
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scalar value. Most DAX functions require one or more arguments, which can include tables, columns, expressions, and values. However, some functions, such as PI, do not require any arguments, but always require parentheses to indicate the null argument. For example, you must always type PI(), not PI. You can also nest f...
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ORDER BY <expression> ASC or DESC START AT <value> or <parameter> - The optional START AT keyword is used inside an ORDER BY clause. It defines the value at which the query results begin.\nDEFINE MEASURE | VAR; EVALUATE <table> - The optional DEFINE keyword introduces one or more calculated entity definitions that exis...
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expression as a named variable, which can then be passed as an argument to other measure expressions. Once resultant values have been calculated for a variable expression, those values do not change, even if the variable is referenced in another expression.\n\nFILTER(<table>,<filter>) - Returns a table that represents ...
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you nest the DISTINCT function within a formula, to get a list of distinct values that can be passed to another function and then counted, summed, or used for other operations.\nDISTINCT(<table>) - Returns a table by removing duplicate rows from another table or expression.\n\nAggregation functions, names with a A in i...
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(<column>) - these are all variantions of count functions.\nAVERAGE(<column>), AVERAGEA(<column>), AVERAGEX(<table>,<expression>) - these are all variantions of average functions.\nMAX(<column>), MAXA(<column>), MAXX(<table>,<expression>) - these are all variantions of max functions.\nMIN(<column>), MINA(<column>), MIN...
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date2, <interval>) - Returns the difference between two date values, in the specified interval, that can be SECOND, MINUTE, HOUR, DAY, WEEK, MONTH, QUARTER, YEAR.\nDATEVALUE(<date_text>) - Returns a date value that represents the specified date.\nYEAR(<date>), QUARTER(<date>), MONTH(<date>), DAY(<date>), HOUR(<date>), ...
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will get a question, a DAX query and a error, in that case you need to rewrite the DAX query to get the correct answer.\n\nThe following tables exist: {tables}\n\nand the schema\'s for some are given here:\n{schemas}\n\nExamples:\n{examples}\n\nQuestion: {tool_input}\nDAX: \n'
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class langchain.tools.QuerySQLCheckerTool(*, name='sql_db_query_checker', description='\nΒ Β Β  Use this tool to double check if your query is correct before executing it.\nΒ Β Β  Always use this tool before executing a query with query_sql_db!\nΒ Β Β  ', args_schema=None, return_direct=False, verbose=False, callbacks=None, cal...
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just reproduce the original query.', llm, llm_chain)[source]
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Bases: langchain.tools.sql_database.tool.BaseSQLDatabaseTool, langchain.tools.base.BaseTool Use an LLM to check if a query is correct. Adapted from https://www.patterns.app/blog/2023/01/18/crunchbot-sql-analyst-gpt/ Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – r...
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template (str) – llm (langchain.base_language.BaseLanguageModel) – llm_chain (langchain.chains.llm.LLMChain) – Return type None attribute llm: langchain.base_language.BaseLanguageModel [Required] attribute llm_chain: langchain.chains.llm.LLMChain [Required]
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attribute template: str = '\n{query}\nDouble check the {dialect} query above for common mistakes, including:\n- Using NOT IN with NULL values\n- Using UNION when UNION ALL should have been used\n- Using BETWEEN for exclusive ranges\n- Data type mismatch in predicates\n- Properly quoting identifiers\n- Using the correct...
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class langchain.tools.QuerySQLDataBaseTool(*, name='sql_db_query', description='\nΒ Β Β  Input to this tool is a detailed and correct SQL query, output is a result from the database.\nΒ Β Β  If the query is not correct, an error message will be returned.\nΒ Β Β  If an error is returned, rewrite the query, check the query, and t...
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verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
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Return type None class langchain.tools.QuerySparkSQLTool(*, name='query_sql_db', description='\nΒ Β Β  Input to this tool is a detailed and correct SQL query, output is a result from the Spark SQL.\nΒ Β Β  If the query is not correct, an error message will be returned.\nΒ Β Β  If an error is returned, rewrite the query, check t...
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verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.base.ToolException], str]...
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description (str) – args_schema (Type[pydantic.main.BaseModel]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – hand...
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You can provide few-shot examples as a part of the description. attribute name: str = 'read_file' The unique name of the tool that clearly communicates its purpose. class langchain.tools.RequestsDeleteTool(*, name='requests_delete', description='A portal to the internet. Use this when you need to make a DELETE request...
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return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – handle_tool_error (Optional[Union[bool, str, Callable[[langchain.tools.b...
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Bases: langchain.tools.requests.tool.BaseRequestsTool, langchain.tools.base.BaseTool Tool for making a GET request to an API endpoint. Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain...
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Return type None class langchain.tools.RequestsPatchTool(*, name='requests_patch', description='Use this when you want to PATCH to a website.\nΒ Β Β  Input should be a json string with two keys: "url" and "data".\nΒ Β Β  The value of "url" should be a string, and the value of "data" should be a dictionary of \nΒ Β Β  key-value ...
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Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks...
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Return type None class langchain.tools.RequestsPostTool(*, name='requests_post', description='Use this when you want to POST to a website.\nΒ Β Β  Input should be a json string with two keys: "url" and "data".\nΒ Β Β  The value of "url" should be a string, and the value of "data" should be a dictionary of \nΒ Β Β  key-value pai...
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Parameters name (str) – description (str) – args_schema (Optional[Type[pydantic.main.BaseModel]]) – return_direct (bool) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks...
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