From d6d04717c264c6ee7895beccbe30353501bd2f4c Mon Sep 17 00:00:00 2001
From: Greyson LaLonde <greyson.r.lalonde@gmail.com>
Date: Tue, 21 Apr 2026 03:15:06 +0800
Subject: [PATCH] fix: serialize Task class-reference fields for checkpointing

Task fields that store class references (output_pydantic, output_json,
response_model, converter_cls) caused PydanticSerializationError when
RuntimeState serialized Crew entities during checkpointing. Serialize
to model_json_schema() and hydrate back via create_model_from_schema.
---
 lib/crewai/src/crewai/task.py | 49 ++++++++++++++++++++++++++++++++---
 1 file changed, 45 insertions(+), 4 deletions(-)

diff --git a/lib/crewai/src/crewai/task.py b/lib/crewai/src/crewai/task.py
index 1cac87cb8..04bbf3718 100644
--- a/lib/crewai/src/crewai/task.py
+++ b/lib/crewai/src/crewai/task.py
@@ -32,6 +32,7 @@ from pydantic import (
     field_validator,
     model_validator,
 )
+from pydantic.functional_serializers import PlainSerializer
 from pydantic_core import PydanticCustomError
 from typing_extensions import Self
 
@@ -86,6 +87,22 @@ from crewai.utilities.printer import PRINTER
 from crewai.utilities.string_utils import interpolate_only
 
 
+def _serialize_model_class(v: type[BaseModel] | None) -> dict[str, Any] | None:
+    """Serialize a Pydantic model class reference to its JSON schema."""
+    return v.model_json_schema() if v else None
+
+
+def _deserialize_model_class(v: Any) -> type[BaseModel] | None:
+    """Hydrate a model class reference from checkpoint data."""
+    if v is None or isinstance(v, type):
+        return v
+    if isinstance(v, dict):
+        from crewai.utilities.pydantic_schema_utils import create_model_from_schema
+
+        return create_model_from_schema(v)
+    return None
+
+
 class Task(BaseModel):
     """Class that represents a task to be executed.
 
@@ -141,15 +158,33 @@ class Task(BaseModel):
         description="Whether the task should be executed asynchronously or not.",
         default=False,
     )
-    output_json: type[BaseModel] | None = Field(
+    output_json: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model to be used to create a JSON output.",
         default=None,
     )
-    output_pydantic: type[BaseModel] | None = Field(
+    output_pydantic: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model to be used to create a Pydantic output.",
         default=None,
     )
-    response_model: type[BaseModel] | None = Field(
+    response_model: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model for structured LLM outputs using native provider features.",
         default=None,
     )
@@ -189,7 +224,13 @@ class Task(BaseModel):
         description="Whether the task should instruct the agent to return the final answer formatted in Markdown",
         default=False,
     )
-    converter_cls: type[Converter] | None = Field(
+    converter_cls: Annotated[
+        type[Converter] | None,
+        BeforeValidator(lambda v: v if v is None or isinstance(v, type) else None),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A converter class used to export structured output",
         default=None,
     )