Files
my-pal-mcp-server/tests/test_large_prompt_handling.py
Fahad 7ea790ef88 fix: Docker path translation for review_changes and code deduplication
- Fixed review_changes tool to properly translate host paths to container paths in Docker
- Prevents "No such file or directory" errors when running in Docker containers
- Added proper error handling with clear messages when paths are inaccessible

refactor: Centralized token limit validation across all tools
- Added _validate_token_limit method to BaseTool to eliminate code duplication
- Reduced ~25 lines of duplicated code across 5 tools (analyze, chat, debug_issue, review_code, think_deeper)
- Maintains exact same error messages and behavior

feat: Enhanced large prompt handling
- Added support for prompts >50K chars by requesting file-based input
- Preserves MCP's ~25K token capacity for responses
- All tools now check prompt size before processing

test: Added comprehensive Docker path integration tests
- Tests for path translation, security validation, and error handling
- Tests for review_changes tool specifically with Docker paths
- Fixed failing think_deeper test (updated default from "max" to "high")

chore: Code quality improvements
- Applied black formatting across all files
- Fixed import sorting with isort
- All tests passing (96 tests)
- Standardized error handling follows MCP TextContent format

The changes ensure consistent behavior across all environments while reducing code duplication and improving maintainability.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-06-10 07:20:24 +04:00

314 lines
12 KiB
Python

"""
Tests for large prompt handling functionality.
This test module verifies that the MCP server correctly handles
prompts that exceed the 50,000 character limit by requesting
Claude to save them to a file and resend.
"""
import json
import os
import shutil
import tempfile
from unittest.mock import MagicMock, patch
import pytest
from mcp.types import TextContent
from config import MCP_PROMPT_SIZE_LIMIT
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 TestLargePromptHandling:
"""Test suite for large prompt handling across all tools."""
@pytest.fixture
def large_prompt(self):
"""Create a prompt larger than MCP_PROMPT_SIZE_LIMIT characters."""
return "x" * (MCP_PROMPT_SIZE_LIMIT + 1000)
@pytest.fixture
def normal_prompt(self):
"""Create a normal-sized prompt."""
return "This is a normal prompt that should work fine."
@pytest.fixture
def temp_prompt_file(self, large_prompt):
"""Create a temporary prompt.txt file with large content."""
# Create temp file with exact name "prompt.txt"
temp_dir = tempfile.mkdtemp()
file_path = os.path.join(temp_dir, "prompt.txt")
with open(file_path, "w") as f:
f.write(large_prompt)
return file_path
@pytest.mark.asyncio
async def test_chat_large_prompt_detection(self, large_prompt):
"""Test that chat tool detects large prompts."""
tool = ChatTool()
result = await tool.execute({"prompt": large_prompt})
assert len(result) == 1
assert isinstance(result[0], TextContent)
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
assert f"{MCP_PROMPT_SIZE_LIMIT:,} characters" in output["content"]
assert output["metadata"]["prompt_size"] == len(large_prompt)
assert output["metadata"]["limit"] == MCP_PROMPT_SIZE_LIMIT
@pytest.mark.asyncio
async def test_chat_normal_prompt_works(self, normal_prompt):
"""Test that chat tool works normally with regular prompts."""
tool = ChatTool()
# Mock the model to avoid actual API calls
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(
parts=[MagicMock(text="This is a test response")]
),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
result = await tool.execute({"prompt": normal_prompt})
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "success"
assert "This is a test response" in output["content"]
@pytest.mark.asyncio
async def test_chat_prompt_file_handling(self, temp_prompt_file, large_prompt):
"""Test that chat tool correctly handles prompt.txt files."""
tool = ChatTool()
# Mock the model
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(parts=[MagicMock(text="Processed large prompt")]),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
# Mock read_file_content to avoid security checks
with patch("tools.base.read_file_content") as mock_read_file:
mock_read_file.return_value = large_prompt
# Execute with empty prompt and prompt.txt file
result = await tool.execute({"prompt": "", "files": [temp_prompt_file]})
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "success"
# Verify read_file_content was called with the prompt file
mock_read_file.assert_called_once_with(temp_prompt_file)
# Verify the large content was used
call_args = mock_model.generate_content.call_args[0][0]
assert large_prompt in call_args
# Cleanup
temp_dir = os.path.dirname(temp_prompt_file)
shutil.rmtree(temp_dir)
@pytest.mark.asyncio
async def test_think_deeper_large_analysis(self, large_prompt):
"""Test that think_deeper tool detects large current_analysis."""
tool = ThinkDeeperTool()
result = await tool.execute({"current_analysis": large_prompt})
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_review_code_large_focus(self, large_prompt):
"""Test that review_code tool detects large focus_on field."""
tool = ReviewCodeTool()
result = await tool.execute(
{"files": ["/some/file.py"], "focus_on": large_prompt}
)
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_review_changes_large_original_request(self, large_prompt):
"""Test that review_changes tool detects large original_request."""
tool = ReviewChanges()
result = await tool.execute(
{"path": "/some/path", "original_request": large_prompt}
)
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_debug_issue_large_error_description(self, large_prompt):
"""Test that debug_issue tool detects large error_description."""
tool = DebugIssueTool()
result = await tool.execute({"error_description": large_prompt})
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_debug_issue_large_error_context(self, large_prompt, normal_prompt):
"""Test that debug_issue tool detects large error_context."""
tool = DebugIssueTool()
result = await tool.execute(
{"error_description": normal_prompt, "error_context": large_prompt}
)
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_analyze_large_question(self, large_prompt):
"""Test that analyze tool detects large question."""
tool = AnalyzeTool()
result = await tool.execute(
{"files": ["/some/file.py"], "question": large_prompt}
)
assert len(result) == 1
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_multiple_files_with_prompt_txt(self, temp_prompt_file):
"""Test handling of prompt.txt alongside other files."""
tool = ChatTool()
other_file = "/some/other/file.py"
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(parts=[MagicMock(text="Success")]),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
# Mock read_files to avoid file system access
with patch("tools.chat.read_files") as mock_read_files:
mock_read_files.return_value = ("File content", "Summary")
await tool.execute(
{"prompt": "", "files": [temp_prompt_file, other_file]}
)
# Verify prompt.txt was removed from files list
mock_read_files.assert_called_once()
files_arg = mock_read_files.call_args[0][0]
assert len(files_arg) == 1
assert files_arg[0] == other_file
temp_dir = os.path.dirname(temp_prompt_file)
shutil.rmtree(temp_dir)
@pytest.mark.asyncio
async def test_boundary_case_exactly_at_limit(self):
"""Test prompt exactly at MCP_PROMPT_SIZE_LIMIT characters (should pass)."""
tool = ChatTool()
exact_prompt = "x" * MCP_PROMPT_SIZE_LIMIT
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(parts=[MagicMock(text="Success")]),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
result = await tool.execute({"prompt": exact_prompt})
output = json.loads(result[0].text)
assert output["status"] == "success"
@pytest.mark.asyncio
async def test_boundary_case_just_over_limit(self):
"""Test prompt just over MCP_PROMPT_SIZE_LIMIT characters (should trigger file request)."""
tool = ChatTool()
over_prompt = "x" * (MCP_PROMPT_SIZE_LIMIT + 1)
result = await tool.execute({"prompt": over_prompt})
output = json.loads(result[0].text)
assert output["status"] == "requires_file_prompt"
@pytest.mark.asyncio
async def test_empty_prompt_no_file(self):
"""Test empty prompt without prompt.txt file."""
tool = ChatTool()
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(parts=[MagicMock(text="Success")]),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
result = await tool.execute({"prompt": ""})
output = json.loads(result[0].text)
assert output["status"] == "success"
@pytest.mark.asyncio
async def test_prompt_file_read_error(self):
"""Test handling when prompt.txt can't be read."""
tool = ChatTool()
bad_file = "/nonexistent/prompt.txt"
with patch.object(tool, "create_model") as mock_create_model:
mock_model = MagicMock()
mock_response = MagicMock()
mock_response.candidates = [
MagicMock(
content=MagicMock(parts=[MagicMock(text="Success")]),
finish_reason="STOP",
)
]
mock_model.generate_content.return_value = mock_response
mock_create_model.return_value = mock_model
# Should continue with empty prompt when file can't be read
result = await tool.execute({"prompt": "", "files": [bad_file]})
output = json.loads(result[0].text)
assert output["status"] == "success"
if __name__ == "__main__":
pytest.main([__file__, "-v"])