Fix pydantic field serialization and error handling

src/backend/langflow/services/monitor/schema.py

@@ -2,7 +2,7 @@ import json
 from datetime import datetime
 from typing import Any, Optional
 
-from pydantic import BaseModel, Field, validator
+from pydantic import BaseModel, Field, field_serializer, validator
 
 
 class TransactionModel(BaseModel):
@@ -60,6 +60,13 @@ class VertexBuildModel(BaseModel):
         from_attributes = True
         populate_by_name = True
 
+    @field_serializer("data", "artifacts")
+    def serialize_dict(v):
+        if isinstance(v, dict):
+            # map_dict = to_map(v)
+            return json.dumps(v)
+        return v
+
     @validator("params", pre=True)
     def validate_params(cls, v):
         if isinstance(v, str):
@@ -82,6 +89,24 @@ class VertexBuildModel(BaseModel):
         return v
 
 
+# create a function that turns dicts into a
+# dict like this:
+#     my_map_dict = {
+#     "key": [
+#         1, 2, 3
+#     ],
+#     "value": [
+#         "one", "two", "three"
+#     ]
+# }
+# so map has a "key" and a "value" list
+# containing the keys and values of the dict
+def to_map(value: dict):
+    keys = list(value.keys())
+    values = list(value.values())
+    return {"key": keys, "value": values}
+
+
 class VertexBuildMapModel(BaseModel):
     vertex_builds: dict[str, list[VertexBuildModel]]
 

src/backend/langflow/services/monitor/service.py

@@ -29,7 +29,7 @@ class MonitorService(Service):
         try:
             self.ensure_tables_exist()
         except Exception as e:
-            logger.error(f"Error initializing monitor service: {e}")
+            logger.exception(f"Error initializing monitor service: {e}")
 
     def to_df(self, table_name):
         return self.load_table_as_dataframe(table_name)
@@ -145,3 +145,4 @@ class MonitorService(Service):
             df = conn.execute(query).df()
 
         return df.to_dict(orient="records")
+        return df.to_dict(orient="records")

src/backend/langflow/services/monitor/utils.py

@@ -1,11 +1,10 @@
 from typing import TYPE_CHECKING, Any, Dict, Optional, Type
 
 import duckdb
+from langflow.services.deps import get_monitor_service
 from loguru import logger
 from pydantic import BaseModel
 
-from langflow.services.deps import get_monitor_service
-
 if TYPE_CHECKING:
     from langflow.api.v1.schemas import ResultDict
 
@@ -35,7 +34,7 @@ def model_to_sql_column_definitions(model: Type[BaseModel]) -> dict:
         elif field_info.__name__ == "bool":
             sql_type = "BOOLEAN"
         elif field_info.__name__ == "dict":
-            sql_type = "JSON"
+            sql_type = "VARCHAR"
         elif field_info.__name__ == "Any":
             sql_type = "VARCHAR"
         else:
@@ -91,7 +90,14 @@ def add_row_to_table(
     insert_sql = f"INSERT INTO {table_name} ({columns}) VALUES ({values_placeholders})"
 
     # Execute the insert statement
-    conn.execute(insert_sql, values)
+    try:
+        conn.execute(insert_sql, values)
+    except Exception as e:
+        # Log values types
+        for key, value in validated_dict.items():
+            logger.error(f"{key}: {type(value)}")
+
+        logger.error(f"Error adding row to table: {e}")
 
 
 async def log_message(
@@ -131,6 +137,7 @@ async def log_vertex_build(
 ):
     try:
         monitor_service = get_monitor_service()
+
         row = {
             "flow_id": flow_id,
             "id": vertex_id,