feat: Add default value support for table columns (#4043)

* Add 'type', 'description', and 'default' fields to Table schema and enhance formatter validation

* Add type-based mapping to formatter validator in table schema

* Add default value support for new table rows in TableNodeComponent

* Add optional 'description' and 'default' fields to ColumnField interface

* Add default value inference for table columns in utils.ts

- Initialize 'default' property for table columns to null.
- Infer default value from the first row of data if available.
- Adjust column formatter determination based on sample value.

* Add default table input validation and update formatter logic in Column model

* Add unit tests for Column class in table schema module

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

src/backend/base/langflow/schema/table.py

@@ -1,6 +1,8 @@
 from enum import Enum
 
-from pydantic import BaseModel, Field, field_validator
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
+
+VALID_TYPES = ["date", "number", "text", "json", "integer", "int", "float", "str", "string"]
 
 
 class FormatterType(str, Enum):
@@ -11,19 +13,35 @@ class FormatterType(str, Enum):
 
 
 class Column(BaseModel):
-    display_name: str
+    model_config = ConfigDict(populate_by_name=True)
     name: str
+    display_name: str = Field(default="")
     sortable: bool = Field(default=True)
     filterable: bool = Field(default=True)
-    formatter: FormatterType | str | None = None
+    formatter: FormatterType | str | None = Field(default=None, alias="type")
+    description: str | None = None
+    default: str | None = None
 
-    @field_validator("formatter")
+    @model_validator(mode="after")
+    def set_display_name(self):
+        if not self.display_name:
+            self.display_name = self.name
+        return self
+
+    @field_validator("formatter", mode="before")
+    @classmethod
     def validate_formatter(cls, value):
+        if value in ["integer", "int", "float"]:
+            value = FormatterType.number
+        if value in ["str", "string"]:
+            value = FormatterType.text
+        if value == "dict":
+            value = FormatterType.json
         if isinstance(value, str):
             return FormatterType(value)
         if isinstance(value, FormatterType):
             return value
-        msg = "Invalid formatter type"
+        msg = f"Invalid formatter type: {value}. Valid types are: {FormatterType}"
         raise ValueError(msg)