[jSrSSKrSSKrSSKJrJrJrJrJrJ r SSK J r SSK J r S\\ S\\\44S jrS \S \\\4S\4S jrS\\ S\4S jrS\\ S\\\44SjrS\\\\\4\\ 4S\\\44Sjrg)z Schema utilities for the ADE SDK. This module provides utility functions for converting Pydantic models to JSON schemas that can be used with the ADE API endpoints. N)AnyDictTypeUnionMappingcast) BaseModel) PYDANTIC_V1modelreturnc[(a@[R"UR55nSU;aUR S5US'U$[R"UR 55$)afReturn a model's JSON schema, keyed the same way regardless of pydantic major. Pydantic v2 exposes `model_json_schema()` and nests shared definitions under `$defs`; pydantic v1 only has `.schema()` and nests them under `definitions`. We normalize to `$defs` here so callers (and `_resolve_refs`) don't need to know which pydantic major produced the schema. definitions$defs)r copydeepcopyschemapopmodel_json_schema)r rs [/home/mande/repo/quber/.venv/lib/python3.13/site-packages/landingai_ade/lib/schema_utils.py_model_json_schemarsX{ u||~. F "$jj7F7O  ==002 33objdefsc [U[5(aSU;aQ[US[5(a9USRS5Sn[ [ R "X5U5$UR5VVs0sHup4U[ XA5_M snn$[U[5(aUVs/sHn[ XQ5PM sn$U$s snnfs snf)aW Resolve JSON Schema $refs to create a flat schema. This function recursively resolves all $ref references in a JSON schema by replacing them with their definitions from the $defs section. Args: obj: The schema object (or part of it) to process defs: Dictionary of schema definitions Returns: The schema with all $refs resolved z$ref/) isinstancedictstrsplit _resolve_refsrritemslist)rrref_namekvitems rr"r"(s#t S=ZF S996{((-b1H t~!>E E69iikBkda=))kBB C  69:cd d)c:: JC:s C5Cc[U[5(a[U[5(d [ S5e[ U5nUR S05n[X5n[R"U5$)aL Convert a Pydantic model to a JSON schema string. This utility function takes a Pydantic BaseModel class and converts it to a JSON schema string with all $refs resolved, suitable for use with the ADE API. Args: model: A Pydantic BaseModel class defining the schema Returns: JSON string representation of the schema Raises: TypeError: If model is not a Pydantic BaseModel subclass Example: >>> from pydantic import BaseModel, Field >>> from landingai_ade.lib.schema_utils import pydantic_to_json_schema >>> >>> class Person(BaseModel): ... name: str = Field(description="Person's name") ... age: int = Field(description="Person's age") >>> schema_json = pydantic_to_json_schema(Person) >>> # Now use schema_json with the SDK: >>> # client.extract(schema=schema_json, markdown="...") +model must be a Pydantic BaseModel subclassr) rtype issubclassr TypeErrorrrr"jsondumpsr rrs rpydantic_to_json_schemar1@s]< 5$ ui ( (EFF  &F ::gr "D 6 (F ::f rc[U[5(a[U[5(d [ S5e[ U5nUR S05n[[[[4[X55$)zFLike `pydantic_to_json_schema` but returns a dict with $refs resolved.r*r) rr+r,r r-rrrrr rr"r0s rpydantic_to_schema_dictr3is^ 5$ ui ( (EFF  &F ::gr "D S#X f ; <r=s 88!4d9o4$sCx.4.s$sCx.S0&4 ?&s&R =4 ? =tCH~ =B%WS#X->Y(O"PBUYZ]_bZbUcBr