o {q i% @sdZddlZddlmZddlmZmZddlmZdede fdede e e efffd d Z d edee fdedee e e efffd d Z dededefddZdS)z.Custom tool decorator for OpenAI custom tools.N) Awaitable)AnyCallable)toolfunc.returncs&dtdttttfffdd }|S)Nxrcsd|dgSNZcustom_tool_call_output)typeoutput)rrr i/home/app/PaddleOCR-VL/.venv_paddleocr/lib/python3.10/site-packages/langchain_openai/tools/custom_tool.pywrapped sz#_make_wrapped_func..wrapped)strlistdictr)rrr r r_make_wrapped_func s"r coroutinec s*dtdtdttttfffdd }|S)Nargskwargsrcs"|i|IdH}d|dgSr r )rrresultrr rrs z(_make_wrapped_coroutine..wrapped)rrrr)rrr rr_make_wrapped_coroutines&rrrcsBdtdtfdtffdd }|rt|drs||dS|S)ajDecorator to create an OpenAI custom tool. Custom tools allow for tools with (potentially long) freeform string inputs. See below for an example using LangGraph: .. code-block:: python @custom_tool def execute_code(code: str) -> str: """Execute python code.""" return "27" llm = ChatOpenAI(model="gpt-5", output_version="responses/v1") agent = create_react_agent(llm, [execute_code]) input_message = {"role": "user", "content": "Use the tool to calculate 3^3."} for step in agent.stream( {"messages": [input_message]}, stream_mode="values", ): step["messages"][-1].pretty_print() You can also specify a format for a corresponding context-free grammar using the ``format`` kwarg: .. code-block:: python from langchain_openai import ChatOpenAI, custom_tool from langgraph.prebuilt import create_react_agent grammar = """ start: expr expr: term (SP ADD SP term)* -> add | term term: factor (SP MUL SP factor)* -> mul | factor factor: INT SP: " " ADD: "+" MUL: "*" %import common.INT """ format = {"type": "grammar", "syntax": "lark", "definition": grammar} # highlight-next-line @custom_tool(format=format) def do_math(input_string: str) -> str: """Do a mathematical operation.""" return "27" llm = ChatOpenAI(model="gpt-5", output_version="responses/v1") agent = create_react_agent(llm, [do_math]) input_message = {"role": "user", "content": "Use the tool to calculate 3^3."} for step in agent.stream( {"messages": [input_message]}, stream_mode="values", ): step["messages"][-1].pretty_print() r.rcshddi}dvrd|d<tdddi|}||_|j|_t|r-t||_|St ||_ |S)Nr custom_toolformatZ infer_schemaFr ) poprmetadata__doc__ descriptioninspectiscoroutinefunctionrrrr)rrZtool_objrr r decorator_s   zcustom_tool..decoratorr)rrcallable)rrr#r r"rrsD r)rr collections.abcrtypingrrZlangchain_core.toolsrrrrrrrr r r rs  .