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chore: import upstream snapshot with attribution
2026-07-13 11:59:26 +08:00

56 lines
1.8 KiB
Python

# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
from typing import List, Union
from typing_extensions import override
from mcp.types import ImageContent, TextContent
from ..inference.types import InferenceResult, OCRResult
from .base import Task
class OCRTask(Task):
@property
@override
def tool_name(self) -> str:
return "ocr"
@override
def _format_result(
self, result: InferenceResult, detailed: bool, **kwargs
) -> Union[str, List[Union[TextContent, ImageContent]]]:
if not isinstance(result, OCRResult):
raise TypeError(f"OCRTask expected OCRResult, got {type(result).__name__}")
if not result.text.strip():
return (
"No text detected"
if not detailed
else json.dumps({"error": "No text detected"}, ensure_ascii=False)
)
if detailed:
return json.dumps(result.to_dict(), ensure_ascii=False, indent=2)
confidence = result.confidence
text_line_count = len(result.text_lines)
output = result.text
if confidence > 0:
output += f"\n\nConfidence: {(confidence * 100):.1f}% | {text_line_count} text lines"
return output