🪄 ImageSorcery MCP

import cv2 import numpy as np import pytest from fastmcp import Client, FastMCP from imagesorcery_mcp.server import mcp as image_sorcery_mcp_server # Add this line to filter out the PyTorch warnings pytestmark = pytest.mark.filterwarnings("ignore:.*'pin_memory' argument is set as true but no accelerator is found.*:UserWarning") @pytest.fixture def mcp_server(): # Use the existing server instance return image_sorcery_mcp_server @pytest.fixture def test_image_path(tmp_path): """Create a test image with text for OCR.""" img_path = tmp_path / "test_ocr_image.png" # Create a white image img = np.ones((300, 600, 3), dtype=np.uint8) * 255 # Add text to the image font = cv2.FONT_HERSHEY_SIMPLEX cv2.putText(img, "Hello World", (50, 50), font, 1, (0, 0, 0), 2) cv2.putText(img, "OCR Test", (50, 150), font, 2, (0, 0, 0), 3) cv2.putText(img, "12345", (50, 250), font, 1.5, (0, 0, 0), 2) # Save the image cv2.imwrite(str(img_path), img) return str(img_path) class TestOcrToolDefinition: """Tests for the OCR tool definition and metadata.""" @pytest.mark.asyncio async def test_ocr_in_tools_list(self, mcp_server: FastMCP): """Tests that OCR tool is in the list of available tools.""" async with Client(mcp_server) as client: tools = await client.list_tools() # Verify that tools list is not empty assert tools, "Tools list should not be empty" # Check if OCR is in the list of tools tool_names = [tool.name for tool in tools] assert "ocr" in tool_names, ( "OCR tool should be in the list of available tools" ) @pytest.mark.asyncio async def test_ocr_description(self, mcp_server: FastMCP): """Tests that OCR tool has the correct description.""" async with Client(mcp_server) as client: tools = await client.list_tools() ocr_tool = next((tool for tool in tools if tool.name == "ocr"), None) # Check description assert ocr_tool.description, "OCR tool should have a description" assert "ocr" in ocr_tool.description.lower() or "optical character recognition" in ocr_tool.description.lower(), ( "Description should mention that it performs OCR on an image" ) @pytest.mark.asyncio async def test_ocr_parameters(self, mcp_server: FastMCP): """Tests that OCR tool has the correct parameter structure.""" async with Client(mcp_server) as client: tools = await client.list_tools() ocr_tool = next((tool for tool in tools if tool.name == "ocr"), None) # Check input schema assert hasattr(ocr_tool, "inputSchema"), ( "OCR tool should have an inputSchema" ) assert "properties" in ocr_tool.inputSchema, ( "inputSchema should have properties field" ) # Check required parameters required_params = ["input_path"] for param in required_params: assert param in ocr_tool.inputSchema["properties"], ( f"OCR tool should have a '{param}' property in its inputSchema" ) # Check optional parameters optional_params = ["language"] for param in optional_params: assert param in ocr_tool.inputSchema["properties"], ( f"OCR tool should have a '{param}' property in its inputSchema" ) # Check parameter types assert ( ocr_tool.inputSchema["properties"]["input_path"].get("type") == "string" ), "input_path should be of type string" # Check optional parameter (now has anyOf structure with null) language_schema = ocr_tool.inputSchema["properties"]["language"] assert "anyOf" in language_schema, "language should have anyOf structure for optional parameter" assert any(item.get("type") == "string" for item in language_schema["anyOf"]), "language should allow string type" assert any(item.get("type") == "null" for item in language_schema["anyOf"]), "language should allow null type" class TestOcrToolExecution: """Tests for the OCR tool execution and results.""" @pytest.mark.asyncio async def test_ocr_tool_execution(self, mcp_server: FastMCP, test_image_path): """Tests the OCR tool execution and return value.""" try: import easyocr # noqa: F401 except ImportError: pytest.skip("EasyOCR is not installed") async with Client(mcp_server) as client: result = await client.call_tool( "ocr", { "input_path": test_image_path, "language": "en", }, ) # Check that the tool returned a result # Parse the result ocr_result = result.structured_content # Basic structure checks assert "image_path" in ocr_result assert "text_segments" in ocr_result assert ocr_result["image_path"] == test_image_path assert isinstance(ocr_result["text_segments"], list) # Check that we have at least some text segments assert len(ocr_result["text_segments"]) > 0, ( "No text segments detected in the test image" ) # Check the structure of a text segment segment = ocr_result["text_segments"][0] assert "text" in segment, "Text segment should have text content" assert "confidence" in segment, "Text segment should have a confidence score" assert "bbox" in segment, "Text segment should have a bounding box" # Check that the confidence is within expected range assert 0 <= segment["confidence"] <= 1, ( "Confidence should be between 0 and 1" ) # Check that the bounding box has 4 coordinates assert len(segment["bbox"]) == 4, "Bounding box should have 4 coordinates" # Check for expected text in the image # We expect at least one of these texts to be detected expected_texts = ["Hello World", "OCR Test", "12345"] detected_texts = [segment["text"] for segment in ocr_result["text_segments"]] # Check if any of our expected texts are detected (allowing for partial matches) matches_found = False for expected in expected_texts: for detected in detected_texts: if expected.lower() in detected.lower() or detected.lower() in expected.lower(): matches_found = True break if matches_found: break assert matches_found, ( f"None of the expected texts {expected_texts} were detected. " f"Detected texts: {detected_texts}" )