g3fi#dZddlmZmZddlmZmZddlmZm Z m Z m Z ddl m Z ddlmZddlmZmZddlmZdd lmZdd lmZdd lmZmZdd lmZdd lmZddlm Z de!de de"ee"ezde#fdZ$e deGddeZ%y)aThis module provides a ValidationNode class that can be used to validate tool calls in a langchain graph. It applies a pydantic schema to tool_calls in the models' outputs, and returns a ToolMessage with the validated content. If the schema is not valid, it returns a ToolMessage with the error message. The ValidationNode can be used in a StateGraph with a "messages" key. If multiple tool calls are requested, they will be run in parallel. )CallableSequence)Anycast) AIMessage AnyMessageToolCall ToolMessage)RunnableConfig)get_executor_for_config)BaseToolcreate_schema_from_function)is_basemodel_subclass)RunnableCallable)LangGraphDeprecatedSinceV10) BaseModelValidationError)r)r) deprecatederrorcallschemareturnct|dS)z"Default error formatting function.z- Respond after fixing all validation errors.)repr)rrrs _/var/www/auto_recruiter/arenv/lib/python3.12/site-packages/langgraph/prebuilt/tool_validator.py_default_format_errorr"s 5k]I JJzpValidationNode is deprecated. Please use `create_agent` from `langchain.agents` with custom tool error handling.)categoryc eZdZdZdddddeeeezezdee e eege fdzde de e dzd df fd Z d e eee efzd ee effd Zd e eee efzd ed efdZxZS)ValidationNodea A node that validates all tools requests from the last `AIMessage`. It can be used either in `StateGraph` with a `'messages'` key. !!! note This node does not actually **run** the tools, it only validates the tool calls, which is useful for extraction and other use cases where you need to generate structured output that conforms to a complex schema without losing the original messages and tool IDs (for use in multi-turn conversations). Returns: (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of `ToolMessage` objects with the validated content or error messages. Example: ```python title="Example usage for re-prompting the model to generate a valid response:" from typing import Literal, Annotated from typing_extensions import TypedDict from langchain_anthropic import ChatAnthropic from pydantic import BaseModel, field_validator from langgraph.graph import END, START, StateGraph from langgraph.prebuilt import ValidationNode from langgraph.graph.message import add_messages class SelectNumber(BaseModel): a: int @field_validator("a") def a_must_be_meaningful(cls, v): if v != 37: raise ValueError("Only 37 is allowed") return v builder = StateGraph(Annotated[list, add_messages]) llm = ChatAnthropic(model="claude-3-5-haiku-latest").bind_tools([SelectNumber]) builder.add_node("model", llm) builder.add_node("validation", ValidationNode([SelectNumber])) builder.add_edge(START, "model") def should_validate(state: list) -> Literal["validation", "__end__"]: if state[-1].tool_calls: return "validation" return END builder.add_conditional_edges("model", should_validate) def should_reprompt(state: list) -> Literal["model", "__end__"]: for msg in state[::-1]: # None of the tool calls were errors if msg.type == "ai": return END if msg.additional_kwargs.get("is_error"): return "model" return END builder.add_conditional_edges("validation", should_reprompt) graph = builder.compile() res = graph.invoke(("user", "Select a number, any number")) # Show the retry logic for msg in res: msg.pretty_print() ``` N validation) format_errornametagsschemasr"r#r$rct||jd||d|xst|_i|_|D]O}t |tr|jtd|jdt |jtrt|js&td|jd|jd|j|j |j<t |trFt|ttfr0t!tt||j |j"<t%|r't'd |}||j |j"<:td t|dy) aInitialize the ValidationNode. Args: schemas: A list of schemas to validate the tool calls with. These can be any of the following: - A pydantic BaseModel class - A BaseTool instance (the args_schema will be used) - A function (a schema will be created from the function signature) format_error: A function that takes an exception, a ToolCall, and a schema and returns a formatted error string. By default, it returns the exception repr and a message to respond after fixing validation errors. name: The name of the node. tags: A list of tags to add to the node. NF)r#r$tracezTool z& does not have an args_schema defined.zVValidation node only works with tools that have a pydantic BaseModel args_schema. Got z with args_schema: . ValidationzPUnsupported input to ValidationNode. Expected BaseModel, tool or function. Got: )super__init___funcr _format_errorschemas_by_name isinstancer args_schema ValueErrorr#typer issubclassr BaseModelV1r__name__callabler)selfr%r"r#r$r base_model __class__s rr+zValidationNode.__init__tsq. T4uM)B-B;= F&(+%%-$ },RS$&&.v/A/AB$%{{m+>v?Q?Q>RRSU5;4F4F$$V[[1FD)jK0/9=T)_f8U$$V__5&!8vN 8B$$V__5 fgklrgsfttuv- rinputct|trd}|}n"|jdgx}rd}n td|d}t|ts td||fS)z*Extract the last AIMessage from the input.listmessagesdictzNo message found in inputz Last message is not an AIMessage)r/r<getr1r)r7r: output_typer=messages r _get_messagezValidationNode._get_messagesi eT " K"H:r2 2X 2 K89 9&rl'9-?@ @G##rconfigcj|\}}dtdtffd }t|5}g|j ||j }|dk(r |cdddSd|icdddS#1swYyxYw)z*Validate and run tool calls synchronously.rrc j|d} t|tr%|j|d}|j }nMt|t r%|j |d}|j}ntdt|dt||dtt|dS#ttf$r@}tj||||dtt|dddi cYd}~Sd}~wwxYw) Nr#argszUnsupported schema type: z$. Expected BaseModel or BaseModelV1.id)contentr# tool_call_idis_errorT)rIr#rJadditional_kwargs)r.r3rmodel_validatemodel_dump_jsonr4validatejsonr1r2r rstrrValidationErrorV1r-)rroutputrIer7s rrun_onez%ValidationNode._func..run_ones))$v,7F fi0#224<@F$446G 4#__T&\:F$kkmG$3DL>Aef##f!%c4:!6 $%67 " ..q$?f!%c4:!6'14&8  sB#B99D5D=DDr<Nr=)rCr r r map tool_calls)r7r:rDrArBrUexecutoroutputss` rr,zValidationNode._funcs $007 W ( { 4%V , -B Wg.@.@ABGf$ - - #G,  - - -s%A/"A//A8)r5 __module__ __qualname____doc__rr r2rr BaseExceptionr rQr<r+rr>rtuplerrCr r, __classcell__)r9s@rr r +s BR !%2(T)_4x?@2 xiI3NO  2  23i$2 2h$*%S#X6$ sI~ $ %-*%S#X6%-@N%- %-rr N)&r\collections.abcrrtypingrrlangchain_core.messagesrrr r langchain_core.runnablesr langchain_core.runnables.configr langchain_core.toolsr rlangchain_core.utils.pydanticrlanggraph._internal._runnablerlanggraph.warningsrpydanticrr pydantic.v1r4rRtyping_extensionsrr]r2rQrr rrrms/  DF?::/0<(K K K Od;/ /K K v (n-%n- n-r