@'h( dZddlmZmZmZmZmZmZmZm Z m Z ddl m Z m Z mZmZddlmZddlmZddlmZmZddlmZddlmZmZdd lmZdd lmZdd lm Z d e!d ede eeeefde"fdZ#Gdde Z$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 or in a MessageGraph. If multiple tool calls are requested, they will be run in parallel. ) AnyCallableDictOptionalSequenceTupleTypeUnioncast) AIMessage AnyMessageToolCall ToolMessage)RunnableConfig)get_executor_for_config)BaseToolcreate_schema_from_function)is_basemodel_subclass) BaseModelValidationError)r)r)RunnableCallableerrorcallschemareturnct|dS)z"Default error formatting function.z- Respond after fixing all validation errors.)repr)rrrs h/home/kushmeetdev/Regenta/Chatbot/venv/lib/python3.12/site-packages/langgraph/prebuilt/tool_validator.py_default_format_errorr(s 5k]I JJc eZdZdZdddddeeeeee fde e e e eege fde de ee d df fd Zd eeeee effd ee effd Zd eeeee effd ed efdZxZS)ValidationNodeaA node that validates all tools requests from the last AIMessage. It can be used either in StateGraph with a "messages" key or in MessageGraph. !!! 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). 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. Returns: (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of ToolMessages with the validated content or error messages. Examples: 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() ================================ Human Message ================================= Select a number, any number ================================== Ai Message ================================== [{'id': 'toolu_01JSjT9Pq8hGmTgmMPc6KnvM', 'input': {'a': 42}, 'name': 'SelectNumber', 'type': 'tool_use'}] Tool Calls: SelectNumber (toolu_01JSjT9Pq8hGmTgmMPc6KnvM) Call ID: toolu_01JSjT9Pq8hGmTgmMPc6KnvM Args: a: 42 ================================= Tool Message ================================= Name: SelectNumber ValidationError(model='SelectNumber', errors=[{'loc': ('a',), 'msg': 'Only 37 is allowed', 'type': 'value_error'}]) Respond after fixing all validation errors. ================================== Ai Message ================================== [{'id': 'toolu_01PkxSVxNxc5wqwCPW1FiSmV', 'input': {'a': 37}, 'name': 'SelectNumber', 'type': 'tool_use'}] Tool Calls: SelectNumber (toolu_01PkxSVxNxc5wqwCPW1FiSmV) Call ID: toolu_01PkxSVxNxc5wqwCPW1FiSmV Args: a: 37 ================================= Tool Message ================================= Name: SelectNumber {"a": 37} 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!t"t||j |j$<t'|r't)d|}||j |j$<:td t|dy) 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 r __name__callabler)selfr'r$r%r&r base_model __class__s rr-zValidationNode.__init__sq T4uM)B-B;= F&(+%%-$ },RS$&&.v/A/AB$%{{m+>v?Q?Q>RRSU5;4F4F$$V[[1FD)jK0/9=T)_f8U$$V__5&!8vN 8B$$V__5 fgklrgsfttuv- r inputct|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)r1r>getr3r )r9r< output_typer?messages r _get_messagezValidationNode._get_messagesi eT " K"H:r2 2X 2 K89 9&rl'9-?@ @G##r configcj|\}}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)rKr%rLadditional_kwargs)r0r5rmodel_validatemodel_dump_jsonr6validatejsonr3r4rr strrValidationErrorV1r/)rroutputrKer9s 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?)rErrrmap tool_calls)r9r<rFrCrDrWexecutoroutputss` rr.zValidationNode._funcs $007 W ( { 4%V , -B Wg.@.@ABGf$ - - #G,  - - -s%A/"A//A8)r7 __module__ __qualname____doc__rr rr rrr BaseExceptionrrSr>r-r r@rrr rErr. __classcell__)r;s@rr"r"1skf  $(%%$y/8 CDE% mXtI?D E %%tCy!% %N$4 +T#s(^;<$ sI~ $ %-4 +T#s(^;<%-FT%- %-r r"N)%r^typingrrrrrrr r r langchain_core.messagesr r rrlangchain_core.runnablesrlangchain_core.runnables.configrlangchain_core.toolsrrlangchain_core.utils.pydanticrpydanticrr pydantic.v1r6rTlanggraph.utils.runnablerr_rSrr"r rrks    DF?/0<5K K K $y/4 #44 5K KJ-%J-r