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semantic-kernel/python/semantic_kernel/schema/kernel_json_schema_builder.py
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Eduard van Valkenburg 05dcb29dea Python: Support for image content and chat message content with image content (#6520)
### Motivation and Context

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  1. Why is this change required?
  2. What problem does it solve?
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Introduces a ImageContent class
Allows that type to be part of ChatMessageContent
Adds a sample for both local and online images
Adds many tests with data uri edge cases, and binary parsing edge cases.

Closes #6536 

### Description

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄
2024-06-13 15:09:25 +00:00

177 lines
6.7 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
from typing import Any, Union, get_args, get_origin, get_type_hints
from semantic_kernel.kernel_pydantic import KernelBaseModel
TYPE_MAPPING = {
int: "integer",
str: "string",
bool: "boolean",
float: "number",
list: "array",
dict: "object",
set: "array",
tuple: "array",
"int": "integer",
"str": "string",
"bool": "boolean",
"float": "number",
"list": "array",
"dict": "object",
"set": "array",
"tuple": "array",
"object": "object",
"array": "array",
}
class KernelJsonSchemaBuilder:
@classmethod
def build(cls, parameter_type: type | str, description: str | None = None) -> dict[str, Any]:
"""Builds the JSON schema for a given parameter type and description.
Args:
parameter_type (type | str): The parameter type.
description (str, optional): The description of the parameter. Defaults to None.
Returns:
dict[str, Any]: The JSON schema for the parameter type.
"""
if isinstance(parameter_type, str):
return cls.build_from_type_name(parameter_type, description)
if isinstance(parameter_type, KernelBaseModel):
return cls.build_model_schema(parameter_type, description)
if hasattr(parameter_type, "__annotations__"):
return cls.build_model_schema(parameter_type, description)
if hasattr(parameter_type, "__args__"):
return cls.handle_complex_type(parameter_type, description)
schema = cls.get_json_schema(parameter_type)
if description:
schema["description"] = description
return schema
@classmethod
def build_model_schema(cls, model: type, description: str | None = None) -> dict[str, Any]:
"""Builds the JSON schema for a given model and description.
Args:
model (type): The model type.
description (str, optional): The description of the model. Defaults to None.
Returns:
dict[str, Any]: The JSON schema for the model.
"""
# TODO (moonbox3): add support for handling forward references, which is not currently tested
# https://github.com/microsoft/semantic-kernel/issues/6464
properties = {}
required = []
hints = get_type_hints(model, globals(), locals())
for field_name, field_type in hints.items():
field_description = None
if hasattr(model, "model_fields") and field_name in model.model_fields:
field_info = model.model_fields[field_name]
if isinstance(field_info.metadata, dict):
field_description = field_info.metadata.get("description")
elif isinstance(field_info.metadata, list) and field_info.metadata:
field_description = field_info.metadata[0]
elif hasattr(field_info, "description"):
field_description = field_info.description
if not cls._is_optional(field_type):
required.append(field_name)
properties[field_name] = cls.build(field_type, field_description)
schema = {"type": "object", "properties": properties}
if required:
schema["required"] = required
if description:
schema["description"] = description
return schema
@classmethod
def _is_optional(cls, field_type: Any) -> bool:
return get_origin(field_type) is Union and type(None) in get_args(field_type)
@classmethod
def build_from_type_name(cls, parameter_type: str, description: str | None = None) -> dict[str, Any]:
"""Builds the JSON schema for a given parameter type name and description.
Args:
parameter_type (str): The parameter type name.
description (str, optional): The description of the parameter. Defaults to None.
Returns:
dict[str, Any]: The JSON schema for the parameter type.
"""
type_name = TYPE_MAPPING.get(parameter_type, "object")
schema = {"type": type_name}
if description:
schema["description"] = description
return schema
@classmethod
def get_json_schema(cls, parameter_type: type) -> dict[str, Any]:
"""Gets JSON schema for a given parameter type.
Args:
parameter_type (type): The parameter type.
Returns:
dict[str, Any]: The JSON schema for the parameter type.
"""
type_name = TYPE_MAPPING.get(parameter_type, "object")
return {"type": type_name}
@classmethod
def handle_complex_type(cls, parameter_type: type, description: str | None = None) -> dict[str, Any]:
"""Handles building the JSON schema for complex types.
Args:
parameter_type (type): The parameter type.
description (str, optional): The description of the parameter. Defaults to None.
Returns:
dict[str, Any]: The JSON schema for the parameter type.
"""
origin = get_origin(parameter_type)
args = get_args(parameter_type)
if origin is list or origin is set:
item_type = args[0]
schema = {"type": "array", "items": cls.build(item_type)}
if description:
schema["description"] = description
return schema
if origin is dict:
_, value_type = args
additional_properties = cls.build(value_type)
if additional_properties == {"type": "object"}:
additional_properties["properties"] = {} # Account for differences in Python 3.10 dict
schema = {"type": "object", "additionalProperties": additional_properties}
if description:
schema["description"] = description
return schema
if origin is tuple:
items = [cls.build(arg) for arg in args]
schema = {"type": "array", "items": items} # type: ignore
if description:
schema["description"] = description
return schema
if origin is Union:
# Handle Optional[T] (Union[T, None]) by making schema nullable
if len(args) == 2 and type(None) in args:
non_none_type = args[0] if args[1] is type(None) else args[1]
schema = cls.build(non_none_type)
schema["nullable"] = True # type: ignore
if description:
schema["description"] = description
return schema
schemas = [cls.build(arg) for arg in args]
schema = {"anyOf": schemas} # type: ignore
if description:
schema["description"] = description
return schema
return cls.get_json_schema(parameter_type)