from __future__ import annotations as _annotations

import re
from abc import ABC, abstractmethod
from copy import deepcopy
from dataclasses import dataclass
from typing import Any, Literal

from .exceptions import UserError

JsonSchema = dict[str, Any]


@dataclass(init=False)
class JsonSchemaTransformer(ABC):
    """Walks a JSON schema, applying transformations to it at each level.

    The transformer is called during a model's prepare_request() step to build the JSON schema
    before it is sent to the model provider.

    Note: We may eventually want to rework tools to build the JSON schema from the type directly, using a subclass of
    pydantic.json_schema.GenerateJsonSchema, rather than making use of this machinery.
    """

    def __init__(
        self,
        schema: JsonSchema,
        *,
        strict: bool | None = None,
        prefer_inlined_defs: bool = False,
        simplify_nullable_unions: bool = False,  # TODO (v2): Remove this, no longer used
    ):
        self.schema = schema

        self.strict = strict
        """The `strict` parameter forces the conversion of the original JSON schema (`self.schema`) of a `ToolDefinition` or `OutputObjectDefinition` to a format supported by the model provider.

        The "strict mode" offered by model providers ensures that the model's output adheres closely to the defined schema. However, not all model providers offer it, and their support for various schema features may differ. For example, a model provider's required schema may not support certain validation constraints like `minLength` or `pattern`.
        """
        self.is_strict_compatible = True
        """Whether the schema is compatible with strict mode.

        This value is used to set `ToolDefinition.strict` or `OutputObjectDefinition.strict` when their values are `None`.
        """
        self.prefer_inlined_defs = prefer_inlined_defs
        self.simplify_nullable_unions = simplify_nullable_unions

        self.defs: dict[str, JsonSchema] = deepcopy(self.schema.get('$defs', {}))
        self.refs_stack: list[str] = []
        self.recursive_refs = set[str]()

    @abstractmethod
    def transform(self, schema: JsonSchema) -> JsonSchema:
        """Make changes to the schema."""
        return schema

    def walk(self) -> JsonSchema:
        schema = deepcopy(self.schema)

        # First, handle everything but $defs:
        schema.pop('$defs', None)
        handled = self._handle(schema)

        if not self.prefer_inlined_defs and self.defs:
            handled['$defs'] = {k: self._handle(v) for k, v in self.defs.items()}

        elif self.recursive_refs:
            # If we are preferring inlined defs and there are recursive refs, we _have_ to use a $defs+$ref structure
            # We try to use whatever the original root key was, but if it is already in use,
            # we modify it to avoid collisions.
            defs = {key: self.defs[key] for key in self.recursive_refs}
            root_ref = self.schema.get('$ref')
            root_key = None if root_ref is None else re.sub(r'^#/\$defs/', '', root_ref)
            if root_key is None:  # pragma: no cover
                root_key = self.schema.get('title', 'root')
                while root_key in defs:
                    # Modify the root key until it is not already in use
                    root_key = f'{root_key}_root'

            defs[root_key] = handled
            return {'$defs': defs, '$ref': f'#/$defs/{root_key}'}

        return handled

    def _handle(self, schema: JsonSchema) -> JsonSchema:
        nested_refs = 0
        if self.prefer_inlined_defs:
            while ref := schema.get('$ref'):
                key = re.sub(r'^#/\$defs/', '', ref)
                if key in self.recursive_refs:
                    break
                if key in self.refs_stack:
                    self.recursive_refs.add(key)
                    break  # recursive ref can't be unpacked
                self.refs_stack.append(key)
                nested_refs += 1

                def_schema = self.defs.get(key)
                if def_schema is None:  # pragma: no cover
                    raise UserError(f'Could not find $ref definition for {key}')
                schema = def_schema

        # Handle the schema based on its type / structure
        type_ = schema.get('type')
        if type_ == 'object':
            schema = self._handle_object(schema)
        elif type_ == 'array':
            schema = self._handle_array(schema)
        elif type_ is None:
            schema = self._handle_union(schema, 'anyOf')
            schema = self._handle_union(schema, 'oneOf')

        # Apply the base transform
        schema = self.transform(schema)

        if nested_refs > 0:
            self.refs_stack = self.refs_stack[:-nested_refs]

        return schema

    def _handle_object(self, schema: JsonSchema) -> JsonSchema:
        if properties := schema.get('properties'):
            handled_properties = {}
            for key, value in properties.items():
                handled_properties[key] = self._handle(value)
            schema['properties'] = handled_properties

        if (additional_properties := schema.get('additionalProperties')) is not None:
            if isinstance(additional_properties, bool):
                schema['additionalProperties'] = additional_properties
            else:
                schema['additionalProperties'] = self._handle(additional_properties)

        if (pattern_properties := schema.get('patternProperties')) is not None:
            handled_pattern_properties = {}
            for key, value in pattern_properties.items():
                handled_pattern_properties[key] = self._handle(value)
            schema['patternProperties'] = handled_pattern_properties

        return schema

    def _handle_array(self, schema: JsonSchema) -> JsonSchema:
        if prefix_items := schema.get('prefixItems'):
            schema['prefixItems'] = [self._handle(item) for item in prefix_items]

        if items := schema.get('items'):
            schema['items'] = self._handle(items)

        return schema

    def _handle_union(self, schema: JsonSchema, union_kind: Literal['anyOf', 'oneOf']) -> JsonSchema:
        try:
            members = schema.pop(union_kind)
        except KeyError:
            return schema

        handled = [self._handle(member) for member in members]

        # TODO (v2): Remove this feature, no longer used
        if self.simplify_nullable_unions:
            handled = self._simplify_nullable_union(handled)
        if len(handled) == 1:
            # In this case, no need to retain the union
            return handled[0] | schema

        # If we have keys besides the union kind (such as title or discriminator), keep them without modifications
        schema = schema.copy()
        schema[union_kind] = handled
        return schema

    @staticmethod
    def _simplify_nullable_union(cases: list[JsonSchema]) -> list[JsonSchema]:
        # TODO (v2): Remove this method, no longer used
        if len(cases) == 2 and {'type': 'null'} in cases:
            # Find the non-null schema
            non_null_schema = next(
                (item for item in cases if item != {'type': 'null'}),
                None,
            )
            if non_null_schema:
                # Create a new schema based on the non-null part, mark as nullable
                new_schema = deepcopy(non_null_schema)
                new_schema['nullable'] = True
                return [new_schema]
            else:  # pragma: no cover
                # they are both null, so just return one of them
                return [cases[0]]

        return cases


class InlineDefsJsonSchemaTransformer(JsonSchemaTransformer):
    """Transforms the JSON Schema to inline $defs."""

    def __init__(self, schema: JsonSchema, *, strict: bool | None = None):
        super().__init__(schema, strict=strict, prefer_inlined_defs=True)

    def transform(self, schema: JsonSchema) -> JsonSchema:
        return schema