## 🚀 Major Improvements ### Docker Environment Simplification - **BREAKING**: Simplified Docker configuration by auto-detecting sandbox from WORKSPACE_ROOT - Removed redundant MCP_PROJECT_ROOT requirement for Docker setups - Updated all Docker config examples and setup scripts - Added security validation for dangerous WORKSPACE_ROOT paths ### Security Enhancements - **CRITICAL**: Fixed insecure PROJECT_ROOT fallback to use current directory instead of home - Enhanced path validation with proper Docker environment detection - Removed information disclosure in error messages - Strengthened symlink and path traversal protection ### File Handling Optimization - **PERFORMANCE**: Optimized read_files() to return content only (removed summary) - Unified file reading across all tools using standardized file_utils routines - Fixed review_changes tool to use consistent file loading patterns - Improved token management and reduced unnecessary processing ### Tool Improvements - **UX**: Enhanced ReviewCodeTool to require user context for targeted reviews - Removed deprecated _get_secure_container_path function and _sanitize_filename - Standardized file access patterns across analyze, review_changes, and other tools - Added contextual prompting to align reviews with user expectations ### Code Quality & Testing - Updated all tests for new function signatures and requirements - Added comprehensive Docker path integration tests - Achieved 100% test coverage (95 tests passing) - Full compliance with ruff, black, and isort linting standards ### Configuration & Deployment - Added pyproject.toml for modern Python packaging - Streamlined Docker setup removing redundant environment variables - Updated setup scripts across all platforms (Windows, macOS, Linux) - Improved error handling and validation throughout ## 🔧 Technical Changes - **Removed**: `_get_secure_container_path()`, `_sanitize_filename()`, unused SANDBOX_MODE - **Enhanced**: Path translation, security validation, token management - **Standardized**: File reading patterns, error handling, Docker detection - **Updated**: All tool prompts for better context alignment ## 🛡️ Security Notes This release significantly improves the security posture by: - Eliminating broad filesystem access defaults - Adding validation for Docker environment variables - Removing information disclosure in error paths - Strengthening path traversal and symlink protections 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
329 lines
13 KiB
Python
329 lines
13 KiB
Python
"""
|
|
Regression tests to ensure normal prompt handling still works after large prompt changes.
|
|
|
|
This test module verifies that all tools continue to work correctly with
|
|
normal-sized prompts after implementing the large prompt handling feature.
|
|
"""
|
|
|
|
import json
|
|
from unittest.mock import MagicMock, patch
|
|
|
|
import pytest
|
|
|
|
from tools.analyze import AnalyzeTool
|
|
from tools.chat import ChatTool
|
|
from tools.debug_issue import DebugIssueTool
|
|
from tools.review_changes import ReviewChanges
|
|
from tools.review_code import ReviewCodeTool
|
|
from tools.think_deeper import ThinkDeeperTool
|
|
|
|
|
|
class TestPromptRegression:
|
|
"""Regression test suite for normal prompt handling."""
|
|
|
|
@pytest.fixture
|
|
def mock_model_response(self):
|
|
"""Create a mock model response."""
|
|
|
|
def _create_response(text="Test response"):
|
|
mock_response = MagicMock()
|
|
mock_response.candidates = [
|
|
MagicMock(
|
|
content=MagicMock(parts=[MagicMock(text=text)]),
|
|
finish_reason="STOP",
|
|
)
|
|
]
|
|
return mock_response
|
|
|
|
return _create_response
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_chat_normal_prompt(self, mock_model_response):
|
|
"""Test chat tool with normal prompt."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response("This is a helpful response about Python.")
|
|
mock_create_model.return_value = mock_model
|
|
|
|
result = await tool.execute({"prompt": "Explain Python decorators"})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
assert "helpful response about Python" in output["content"]
|
|
|
|
# Verify model was called
|
|
mock_model.generate_content.assert_called_once()
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_chat_with_files(self, mock_model_response):
|
|
"""Test chat tool with files parameter."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
# Mock file reading
|
|
with patch("tools.chat.read_files") as mock_read_files:
|
|
mock_read_files.return_value = "File content here"
|
|
|
|
result = await tool.execute({"prompt": "Analyze this code", "files": ["/path/to/file.py"]})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
mock_read_files.assert_called_once_with(["/path/to/file.py"])
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_think_deeper_normal_analysis(self, mock_model_response):
|
|
"""Test think_deeper tool with normal analysis."""
|
|
tool = ThinkDeeperTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response(
|
|
"Here's a deeper analysis with edge cases..."
|
|
)
|
|
mock_create_model.return_value = mock_model
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"current_analysis": "I think we should use a cache for performance",
|
|
"problem_context": "Building a high-traffic API",
|
|
"focus_areas": ["scalability", "reliability"],
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
assert "Extended Analysis by Gemini" in output["content"]
|
|
assert "deeper analysis" in output["content"]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_review_code_normal_review(self, mock_model_response):
|
|
"""Test review_code tool with normal inputs."""
|
|
tool = ReviewCodeTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response(
|
|
"Found 3 issues: 1) Missing error handling..."
|
|
)
|
|
mock_create_model.return_value = mock_model
|
|
|
|
# Mock file reading
|
|
with patch("tools.review_code.read_files") as mock_read_files:
|
|
mock_read_files.return_value = "def main(): pass"
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"files": ["/path/to/code.py"],
|
|
"review_type": "security",
|
|
"focus_on": "Look for SQL injection vulnerabilities",
|
|
"context": "Test code review for validation purposes",
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
assert "Found 3 issues" in output["content"]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_review_changes_normal_request(self, mock_model_response):
|
|
"""Test review_changes tool with normal original_request."""
|
|
tool = ReviewChanges()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response(
|
|
"Changes look good, implementing feature as requested..."
|
|
)
|
|
mock_create_model.return_value = mock_model
|
|
|
|
# Mock git operations
|
|
with patch("tools.review_changes.find_git_repositories") as mock_find_repos:
|
|
with patch("tools.review_changes.get_git_status") as mock_git_status:
|
|
mock_find_repos.return_value = ["/path/to/repo"]
|
|
mock_git_status.return_value = {
|
|
"modified": ["file.py"],
|
|
"untracked": [],
|
|
}
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"path": "/path/to/repo",
|
|
"original_request": "Add user authentication feature with JWT tokens",
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_debug_issue_normal_error(self, mock_model_response):
|
|
"""Test debug_issue tool with normal error description."""
|
|
tool = DebugIssueTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response(
|
|
"Root cause: The variable is undefined. Fix: Initialize it..."
|
|
)
|
|
mock_create_model.return_value = mock_model
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"error_description": "TypeError: Cannot read property 'name' of undefined",
|
|
"error_context": "at line 42 in user.js\n console.log(user.name)",
|
|
"runtime_info": "Node.js v16.14.0",
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
assert "Debug Analysis" in output["content"]
|
|
assert "Root cause" in output["content"]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_normal_question(self, mock_model_response):
|
|
"""Test analyze tool with normal question."""
|
|
tool = AnalyzeTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response(
|
|
"The code follows MVC pattern with clear separation..."
|
|
)
|
|
mock_create_model.return_value = mock_model
|
|
|
|
# Mock file reading
|
|
with patch("tools.analyze.read_files") as mock_read_files:
|
|
mock_read_files.return_value = "class UserController: ..."
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"files": ["/path/to/project"],
|
|
"question": "What design patterns are used in this codebase?",
|
|
"analysis_type": "architecture",
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
assert "MVC pattern" in output["content"]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_empty_optional_fields(self, mock_model_response):
|
|
"""Test tools work with empty optional fields."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
# Test with no files parameter
|
|
result = await tool.execute({"prompt": "Hello"})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_thinking_modes_work(self, mock_model_response):
|
|
"""Test that thinking modes are properly passed through."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
result = await tool.execute({"prompt": "Test", "thinking_mode": "high", "temperature": 0.8})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
|
|
# Verify create_model was called with correct parameters
|
|
mock_create_model.assert_called_once()
|
|
call_args = mock_create_model.call_args
|
|
assert call_args[0][2] == "high" # thinking_mode
|
|
assert call_args[0][1] == 0.8 # temperature
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_special_characters_in_prompts(self, mock_model_response):
|
|
"""Test prompts with special characters work correctly."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
special_prompt = 'Test with "quotes" and\nnewlines\tand tabs'
|
|
result = await tool.execute({"prompt": special_prompt})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_mixed_file_paths(self, mock_model_response):
|
|
"""Test handling of various file path formats."""
|
|
tool = AnalyzeTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
with patch("tools.analyze.read_files") as mock_read_files:
|
|
mock_read_files.return_value = "Content"
|
|
|
|
result = await tool.execute(
|
|
{
|
|
"files": [
|
|
"/absolute/path/file.py",
|
|
"/Users/name/project/src/",
|
|
"/home/user/code.js",
|
|
],
|
|
"question": "Analyze these files",
|
|
}
|
|
)
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
mock_read_files.assert_called_once()
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_unicode_content(self, mock_model_response):
|
|
"""Test handling of unicode content in prompts."""
|
|
tool = ChatTool()
|
|
|
|
with patch.object(tool, "create_model") as mock_create_model:
|
|
mock_model = MagicMock()
|
|
mock_model.generate_content.return_value = mock_model_response()
|
|
mock_create_model.return_value = mock_model
|
|
|
|
unicode_prompt = "Explain this: 你好世界 مرحبا بالعالم"
|
|
result = await tool.execute({"prompt": unicode_prompt})
|
|
|
|
assert len(result) == 1
|
|
output = json.loads(result[0].text)
|
|
assert output["status"] == "success"
|
|
|
|
|
|
if __name__ == "__main__":
|
|
pytest.main([__file__, "-v"])
|