fix scheduled-tasks create/update against Prisma input shape

Two bugs surfaced on first real proxy invocation:

1. owner_token: prisma-client-python rejected the bare scalar with
   "owner_key: A value is required but not set". Prisma exposes the FK
   via the relation field, not the scalar column. Switched create_task
   to {"owner_key": {"connect": {"token": owner_token}}}.

2. action_args: prisma-client-python rejected the bare Python dict on
   the Json? column ("Invalid argument type. action_args should be of
   any of the following types: NullableJsonNullValueInput, Json"). Added
   _serialize_json_for_prisma helper (same pattern as
   memory_endpoints._serialize_metadata_for_prisma) and applied to both
   create and update paths. Read path round-trips back to native Python.

Updated the in-memory fake in tests to mirror real Prisma write
semantics: owner_key.connect.token unfolds to the owner_token column,
and Json strings are deserialised back on read.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

litellm/proxy/scheduled_tasks/store.py

@@ -8,11 +8,26 @@ is required for multi-pod tick safety.
 
 from __future__ import annotations
 
+import json
 from datetime import datetime, timedelta, timezone
 from typing import Any, Dict, List, Optional
 
 from litellm.proxy.scheduled_tasks.schedule import compute_next_run
 
+
+def _serialize_json_for_prisma(value: Any) -> Optional[str]:
+    """
+    Encode a value bound for a Prisma `Json?` column. prisma-client-python
+    rejects raw Python dicts/lists on Json columns
+    (`MissingRequiredValueError` / `DataError`); always json.dumps so the
+    driver hands a string to Postgres jsonb. Read path round-trips back
+    to native Python.
+    """
+    if value is None:
+        return None
+    return json.dumps(value)
+
+
 # Whitelist of fields PATCH can touch. Anything outside this set would let
 # a buggy caller rewrite scheduling state (status, fired flags, ...).
 UPDATABLE_FIELDS = frozenset(
@@ -62,13 +77,15 @@ async def create_task(
 ) -> Any:
     return await prisma_client.db.litellm_scheduledtasktable.create(
         data={
-            "owner_token": owner_token,
+            # Prisma exposes the FK via the relation field (`owner_key`),
+            # not the scalar column. Use connect to satisfy the input type.
+            "owner_key": {"connect": {"token": owner_token}},
             "user_id": user_id,
             "team_id": team_id,
             "agent_id": agent_id,
             "title": title,
             "action": action,
-            "action_args": action_args,
+            "action_args": _serialize_json_for_prisma(action_args),
             "check_prompt": check_prompt,
             "format_prompt": format_prompt,
             "schedule_kind": schedule_kind,
@@ -133,6 +150,15 @@ async def update_task_for_owner(
     )
     if existing is None:
         return None
+
+    # Mirror the create path: Json columns must be json-encoded for
+    # prisma-client-python.
+    if "action_args" in fields:
+        fields = {
+            **fields,
+            "action_args": _serialize_json_for_prisma(fields["action_args"]),
+        }
+
     return await prisma_client.db.litellm_scheduledtasktable.update(
         where={"task_id": task_id},
         data=fields,

tests/test_litellm/proxy/scheduled_tasks/test_endpoints.py

@@ -4,6 +4,7 @@ prisma scheduled-tasks table. The /due test path uses a fake of query_raw +
 tx() that exercises the same Python-side schedule advance logic.
 """
 
+import json
 import os
 import sys
 from datetime import datetime, timedelta, timezone
@@ -80,8 +81,23 @@ class _FakeScheduledTaskTable:
         return [r for r in self.rows if self._matches(r, where)]
 
     async def create(self, data: Dict[str, Any]) -> MagicMock:
+        # Mirror real Prisma write semantics:
+        #  - relation field `owner_key: {connect: {token: X}}` becomes the
+        #    scalar `owner_token` column on the row;
+        #  - Json columns (`action_args`) come in as JSON strings and are
+        #    deserialized back to Python on read.
+        normalized = dict(data)
+        if "owner_key" in normalized:
+            connect = normalized.pop("owner_key", {}).get("connect", {})
+            if "token" in connect:
+                normalized["owner_token"] = connect["token"]
+        if isinstance(normalized.get("action_args"), str):
+            try:
+                normalized["action_args"] = json.loads(normalized["action_args"])
+            except ValueError:
+                pass
         self._counter += 1
-        row = _make_row(task_id=f"task-{self._counter}", **data)
+        row = _make_row(task_id=f"task-{self._counter}", **normalized)
         self.rows.append(row)
         return row
 
@@ -106,6 +122,11 @@ class _FakeScheduledTaskTable:
         for r in self.rows:
             if r.task_id == where["task_id"]:
                 for k, v in data.items():
+                    if k == "action_args" and isinstance(v, str):
+                        try:
+                            v = json.loads(v)
+                        except ValueError:
+                            pass
                     setattr(r, k, v)
                 return r
         raise Exception("Not found")