add pydantic model from json

backend/utils/schemas.py

@@ -0,0 +1,104 @@
+from pydantic import BaseModel, Field, create_model
+from typing import Any, Optional, Type
+
+
+def json_schema_to_model(tool_dict: dict[str, Any]) -> Type[BaseModel]:
+    """
+    Converts a JSON schema to a Pydantic BaseModel class.
+
+    Args:
+        json_schema: The JSON schema to convert.
+
+    Returns:
+        A Pydantic BaseModel class.
+    """
+
+    # Extract the model name from the schema title.
+    model_name = tool_dict["name"]
+    schema = tool_dict["parameters"]
+
+    # Extract the field definitions from the schema properties.
+    field_definitions = {
+        name: json_schema_to_pydantic_field(name, prop, schema.get("required", []))
+        for name, prop in schema.get("properties", {}).items()
+    }
+
+    # Create the BaseModel class using create_model().
+    return create_model(model_name, **field_definitions)
+
+
+def json_schema_to_pydantic_field(
+    name: str, json_schema: dict[str, Any], required: list[str]
+) -> Any:
+    """
+    Converts a JSON schema property to a Pydantic field definition.
+
+    Args:
+        name: The field name.
+        json_schema: The JSON schema property.
+
+    Returns:
+        A Pydantic field definition.
+    """
+
+    # Get the field type.
+    type_ = json_schema_to_pydantic_type(json_schema)
+
+    # Get the field description.
+    description = json_schema.get("description")
+
+    # Get the field examples.
+    examples = json_schema.get("examples")
+
+    # Create a Field object with the type, description, and examples.
+    # The 'required' flag will be set later when creating the model.
+    return (
+        type_,
+        Field(
+            description=description,
+            examples=examples,
+            default=... if name in required else None,
+        ),
+    )
+
+
+def json_schema_to_pydantic_type(json_schema: dict[str, Any]) -> Any:
+    """
+    Converts a JSON schema type to a Pydantic type.
+
+    Args:
+        json_schema: The JSON schema to convert.
+
+    Returns:
+        A Pydantic type.
+    """
+
+    type_ = json_schema.get("type")
+
+    if type_ == "string" or type_ == "str":
+        return str
+    elif type_ == "integer" or type_ == "int":
+        return int
+    elif type_ == "number" or type_ == "float":
+        return float
+    elif type_ == "boolean" or type_ == "bool":
+        return bool
+    elif type_ == "array":
+        items_schema = json_schema.get("items")
+        if items_schema:
+            item_type = json_schema_to_pydantic_type(items_schema)
+            return list[item_type]
+        else:
+            return list
+    elif type_ == "object":
+        # Handle nested models.
+        properties = json_schema.get("properties")
+        if properties:
+            nested_model = json_schema_to_model(json_schema)
+            return nested_model
+        else:
+            return dict
+    elif type_ == "null":
+        return Optional[Any]  # Use Optional[Any] for nullable fields
+    else:
+        raise ValueError(f"Unsupported JSON schema type: {type_}")

backend/utils/tools.py

@@ -6,6 +6,8 @@ from apps.webui.models.tools import Tools
 from apps.webui.models.users import UserModel
 from apps.webui.utils import load_toolkit_module_by_id
 
+from utils.schemas import json_schema_to_model
+
 log = logging.getLogger(__name__)
 
 
@@ -70,6 +72,7 @@ def get_tools(
                 "toolkit_id": tool_id,
                 "callable": callable,
                 "spec": spec,
+                "pydantic_model": json_schema_to_model(spec),
                 "file_handler": hasattr(module, "file_handler") and module.file_handler,
                 "citation": hasattr(module, "citation") and module.citation,
             }