tests/test_mcp.py

"""Tests for MCP context and response validation."""
import json
import pytest
from pathlib import Path
from jsonschema import validate, ValidationError

from schema import MCP_CONTEXT_SCHEMA, MCP_PREDICT_RESPONSE_SCHEMA
from utils import format_results_to_mcp, get_mcp_context

def test_mcp_context_schema():
    """Test that the MCP context follows the schema."""
    context = get_mcp_context()
    validate(instance=context, schema=MCP_CONTEXT_SCHEMA)
    
    # Test required fields
    assert "app" in context
    assert "id" in context["app"]
    assert "name" in context["app"]
    assert "version" in context["app"]
    
    # Test windows configuration
    assert "windows" in context
    assert len(context["windows"]) > 0
    assert "objects" in context["windows"][0]["view"]
    
    # Test objects configuration
    assert "objects" in context
    file_objects = [obj for obj in context["objects"] if obj["type"] == "file"]
    assert len(file_objects) >= 2  # At least ligand and protein
    
    # Test actions configuration
    assert "actions" in context
    assert len(context["actions"]) >= 1
    for action in context["actions"]:
        assert "parameters" in action
        assert "output" in action

def test_mcp_response_format():
    """Test that the MCP response formatter produces valid output."""
    # Test successful case
    csv_text = "molecule,test1,test2\nmol1,True,False\n"
    response = format_results_to_mcp(csv_text, "", "mol1")
    validate(instance=response, schema=MCP_PREDICT_RESPONSE_SCHEMA)
    
    assert response["object_id"] == "validation_results"
    assert "columns" in response["data"]
    assert "rows" in response["data"]
    assert len(response["data"]["rows"]) == 1
    
    # Test error case
    response = format_results_to_mcp("", "Error occurred", "mol1")
    validate(instance=response, schema=MCP_PREDICT_RESPONSE_SCHEMA)
    assert response["data"]["rows"][0][1] == "❌"  # Status should be fail

def test_mcp_response_content():
    """Test the content of MCP responses for different scenarios."""
    # Test all tests passing
    csv_text = "molecule,test1,test2\nmol1,True,True\n"
    response = format_results_to_mcp(csv_text, "", "mol1")
    row = response["data"]["rows"][0]
    assert row[1] == "✅"  # Status
    assert row[2] == "2/2"  # Passed/Total
    assert row[3] == "All tests passed"  # Details
    
    # Test some tests failing
    csv_text = "molecule,test1,test2,test3\nmol1,True,False,False\n"
    response = format_results_to_mcp(csv_text, "", "mol1")
    row = response["data"]["rows"][0]
    assert row[1] == "❌"  # Status
    assert row[2] == "1/3"  # Passed/Total
    assert "test2" in row[3] and "test3" in row[3]  # Failed tests in details

def test_invalid_mcp_context():
    """Test that invalid MCP context raises ValidationError."""
    invalid_context = {
        "app": {"name": "Test"}  # Missing required fields
    }
    with pytest.raises(ValidationError):
        validate(instance=invalid_context, schema=MCP_CONTEXT_SCHEMA)

def test_invalid_mcp_response():
    """Test that invalid MCP response raises ValidationError."""
    invalid_response = {
        "object_id": "validation_results",
        "data": {
            "columns": ["col1"],
            "rows": [["too", "many", "columns"]]  # Inconsistent columns
        }
    }
    
    with pytest.raises(ValidationError) as exc_info:
        # First validate that rows match column count
        columns_count = len(invalid_response["data"]["columns"])
        for row in invalid_response["data"]["rows"]:
            if len(row) != columns_count:
                raise ValidationError(f"Row length {len(row)} does not match columns length {columns_count}")
                
        # Then validate schema
        validate(instance=invalid_response, schema=MCP_PREDICT_RESPONSE_SCHEMA)
    
    assert "Row length" in str(exc_info.value)