Merge pull request #450 from kreneskyp/json_schema_to_typed_dict

Adding jsonschema_to_typeddict helper

ix/utils/json_schema.py

@@ -0,0 +1,90 @@
+from typing import Any, Dict, List, Optional, Type
+from typing_extensions import TypedDict, Annotated
+import operator
+
+
+# Mapping of operators available to annotate fields with
+# i.e. Annotated[str, operator.add]. LangGraph state machine
+# applies the operator to the field value on state updates.
+operator_mapping = {
+    "add": operator.add,
+}
+
+
+def resolve_reference(ref: str, definitions: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Resolve a $ref to the actual schema it refers to within definitions.
+    """
+    ref_path = ref.split("/")
+    ref_name = ref_path[-1]
+    return definitions.get(ref_name, {})
+
+
+def combine_schemas(
+    allOf: List[Dict[str, Any]], definitions: Dict[str, Any]
+) -> Dict[str, Any]:
+    """
+    Combine schemas specified in allOf by merging their properties.
+    """
+    combined_schema = {"properties": {}, "required": [], "type": "object"}
+    for schema in allOf:
+        if "$ref" in schema:
+            ref_schema = resolve_reference(schema["$ref"], definitions)
+            schema = ref_schema
+        combined_schema["properties"].update(schema.get("properties", {}))
+        combined_schema["required"].extend(schema.get("required", []))
+    return combined_schema
+
+
+def convert_type(prop: Dict[str, Any], definitions: Dict[str, Any]) -> Any:
+    """
+    Convert a JSON schema property to a Python type, handling references,
+    allOf, anyOf, and custom annotations for operations.
+    """
+    if "$ref" in prop:
+        ref_schema = resolve_reference(prop["$ref"], definitions)
+        return convert_type(ref_schema, definitions)
+
+    if "allOf" in prop:
+        combined_schema = combine_schemas(prop["allOf"], definitions)
+        return jsonschema_to_typeddict(combined_schema, definitions)
+
+    # Simplified type conversion for demonstration
+    type_mapping = {
+        "string": str,
+        "number": float,
+        "integer": int,
+        "boolean": bool,
+        "array": List[Any],  # Note: Items not handled in this example
+        "object": Dict[str, Any],
+    }
+
+    prop_type = type_mapping.get(prop.get("type"), Any)
+
+    # Handle custom operation annotations within the field definition
+    if "operation" in prop:
+        operation = operator_mapping.get(prop["operation"])
+        if operation:
+            return Annotated[prop_type, operation]
+
+    return prop_type
+
+
+def jsonschema_to_typeddict(
+    schema: Dict[str, Any], definitions: Optional[Dict[str, Any]] = None
+) -> Type[TypedDict]:
+    if definitions is None:
+        definitions = schema.get("definitions", {})
+
+    title = schema.get("title", "DynamicTypedDict")
+    properties = schema.get("properties", {})
+
+    annotations = {}
+    for name, prop in properties.items():
+        python_type = convert_type(prop, definitions)
+        annotations[name] = python_type
+
+    # Dynamically create TypedDict
+    TypedDictClass = TypedDict(title, annotations)
+
+    return TypedDictClass