fixes json schema issue

pandera/typing/pandas.py

@@ -19,6 +19,7 @@
 import numpy as np
 import pandas as pd
 
+from pandera.config import config_context
 from pandera.engines import PYDANTIC_V2
 from pandera.errors import SchemaError, SchemaInitError
 from pandera.typing.common import (
@@ -30,12 +31,6 @@
 )
 from pandera.typing.formats import Formats
 
-try:
-    from typing import get_args
-except ImportError:
-    from typing_extensions import get_args
-
-
 try:
     from typing import _GenericAlias  # type: ignore[attr-defined]
 except ImportError:  # pragma: no cover
@@ -190,13 +185,38 @@
         def __get_pydantic_core_schema__(
             cls, _source_type: Any, _handler: GetCoreSchemaHandler
         ) -> core_schema.CoreSchema:
-            schema_model = get_args(_source_type)[0]
-            return core_schema.no_info_plain_validator_function(
-                functools.partial(
-                    cls.pydantic_validate,
-                    schema_model=schema_model,
-                ),
-            )
+
+            with config_context(validation_enabled=False):
+                schema_model = _source_type().__orig_class__.__args__[0]
+            if (schema_model.Config.from_format == "dict") and (
+                schema_model.Config.from_format_kwargs == {"orient": "records"}
+            ):
+                schema = schema_model.to_schema()
+                type_map = {
+                    "str": core_schema.str_schema(),
+                    "int64": core_schema.int_schema(),
+                    "float64": core_schema.float_schema(),
+                    "bool": core_schema.bool_schema(),
+                    "datetime64[ns]": core_schema.datetime_schema(),
+                }
+
+                return core_schema.list_schema(
+                    core_schema.typed_dict_schema(
+                        {
+                            i: core_schema.typed_dict_field(
+                                type_map[str(j.dtype)]
+                            )
+                            for i, j in schema.columns.items()
+                        },
+                    )
+                )
+            else:
+                return core_schema.no_info_plain_validator_function(
+                    functools.partial(
+                        cls.pydantic_validate,
+                        schema_model=schema_model,
+                    ),
+                )
 
     else: