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>
This commit is contained in:
Fahad
313
tests/test_large_prompt_handling.py
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313
tests/test_large_prompt_handling.py
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"""
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Tests for large prompt handling functionality.
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This test module verifies that the MCP server correctly handles
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prompts that exceed the 50,000 character limit by requesting
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Claude to save them to a file and resend.
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"""
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import json
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import os
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import shutil
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import tempfile
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from unittest.mock import MagicMock, patch
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import pytest
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from mcp.types import TextContent
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from config import MCP_PROMPT_SIZE_LIMIT
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from tools.analyze import AnalyzeTool
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from tools.chat import ChatTool
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from tools.debug_issue import DebugIssueTool
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from tools.review_changes import ReviewChanges
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from tools.review_code import ReviewCodeTool
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from tools.think_deeper import ThinkDeeperTool
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class TestLargePromptHandling:
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"""Test suite for large prompt handling across all tools."""
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@pytest.fixture
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def large_prompt(self):
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"""Create a prompt larger than MCP_PROMPT_SIZE_LIMIT characters."""
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return "x" * (MCP_PROMPT_SIZE_LIMIT + 1000)
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@pytest.fixture
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def normal_prompt(self):
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"""Create a normal-sized prompt."""
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return "This is a normal prompt that should work fine."
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@pytest.fixture
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def temp_prompt_file(self, large_prompt):
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"""Create a temporary prompt.txt file with large content."""
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# Create temp file with exact name "prompt.txt"
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temp_dir = tempfile.mkdtemp()
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file_path = os.path.join(temp_dir, "prompt.txt")
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with open(file_path, "w") as f:
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f.write(large_prompt)
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return file_path
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@pytest.mark.asyncio
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async def test_chat_large_prompt_detection(self, large_prompt):
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"""Test that chat tool detects large prompts."""
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tool = ChatTool()
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result = await tool.execute({"prompt": large_prompt})
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assert len(result) == 1
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assert isinstance(result[0], TextContent)
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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assert f"{MCP_PROMPT_SIZE_LIMIT:,} characters" in output["content"]
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assert output["metadata"]["prompt_size"] == len(large_prompt)
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assert output["metadata"]["limit"] == MCP_PROMPT_SIZE_LIMIT
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@pytest.mark.asyncio
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async def test_chat_normal_prompt_works(self, normal_prompt):
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"""Test that chat tool works normally with regular prompts."""
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tool = ChatTool()
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# Mock the model to avoid actual API calls
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(
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parts=[MagicMock(text="This is a test response")]
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),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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result = await tool.execute({"prompt": normal_prompt})
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "success"
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assert "This is a test response" in output["content"]
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@pytest.mark.asyncio
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async def test_chat_prompt_file_handling(self, temp_prompt_file, large_prompt):
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"""Test that chat tool correctly handles prompt.txt files."""
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tool = ChatTool()
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# Mock the model
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(parts=[MagicMock(text="Processed large prompt")]),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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# Mock read_file_content to avoid security checks
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with patch("tools.base.read_file_content") as mock_read_file:
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mock_read_file.return_value = large_prompt
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# Execute with empty prompt and prompt.txt file
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result = await tool.execute({"prompt": "", "files": [temp_prompt_file]})
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "success"
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# Verify read_file_content was called with the prompt file
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mock_read_file.assert_called_once_with(temp_prompt_file)
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# Verify the large content was used
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call_args = mock_model.generate_content.call_args[0][0]
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assert large_prompt in call_args
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# Cleanup
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temp_dir = os.path.dirname(temp_prompt_file)
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shutil.rmtree(temp_dir)
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@pytest.mark.asyncio
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async def test_think_deeper_large_analysis(self, large_prompt):
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"""Test that think_deeper tool detects large current_analysis."""
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tool = ThinkDeeperTool()
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result = await tool.execute({"current_analysis": large_prompt})
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_review_code_large_focus(self, large_prompt):
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"""Test that review_code tool detects large focus_on field."""
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tool = ReviewCodeTool()
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result = await tool.execute(
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{"files": ["/some/file.py"], "focus_on": large_prompt}
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)
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_review_changes_large_original_request(self, large_prompt):
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"""Test that review_changes tool detects large original_request."""
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tool = ReviewChanges()
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result = await tool.execute(
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{"path": "/some/path", "original_request": large_prompt}
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)
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_debug_issue_large_error_description(self, large_prompt):
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"""Test that debug_issue tool detects large error_description."""
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tool = DebugIssueTool()
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result = await tool.execute({"error_description": large_prompt})
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_debug_issue_large_error_context(self, large_prompt, normal_prompt):
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"""Test that debug_issue tool detects large error_context."""
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tool = DebugIssueTool()
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result = await tool.execute(
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{"error_description": normal_prompt, "error_context": large_prompt}
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)
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_analyze_large_question(self, large_prompt):
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"""Test that analyze tool detects large question."""
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tool = AnalyzeTool()
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result = await tool.execute(
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{"files": ["/some/file.py"], "question": large_prompt}
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)
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assert len(result) == 1
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_multiple_files_with_prompt_txt(self, temp_prompt_file):
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"""Test handling of prompt.txt alongside other files."""
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tool = ChatTool()
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other_file = "/some/other/file.py"
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(parts=[MagicMock(text="Success")]),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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# Mock read_files to avoid file system access
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with patch("tools.chat.read_files") as mock_read_files:
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mock_read_files.return_value = ("File content", "Summary")
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await tool.execute(
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{"prompt": "", "files": [temp_prompt_file, other_file]}
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)
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# Verify prompt.txt was removed from files list
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mock_read_files.assert_called_once()
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files_arg = mock_read_files.call_args[0][0]
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assert len(files_arg) == 1
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assert files_arg[0] == other_file
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temp_dir = os.path.dirname(temp_prompt_file)
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shutil.rmtree(temp_dir)
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@pytest.mark.asyncio
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async def test_boundary_case_exactly_at_limit(self):
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"""Test prompt exactly at MCP_PROMPT_SIZE_LIMIT characters (should pass)."""
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tool = ChatTool()
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exact_prompt = "x" * MCP_PROMPT_SIZE_LIMIT
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(parts=[MagicMock(text="Success")]),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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result = await tool.execute({"prompt": exact_prompt})
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output = json.loads(result[0].text)
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assert output["status"] == "success"
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@pytest.mark.asyncio
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async def test_boundary_case_just_over_limit(self):
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"""Test prompt just over MCP_PROMPT_SIZE_LIMIT characters (should trigger file request)."""
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tool = ChatTool()
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over_prompt = "x" * (MCP_PROMPT_SIZE_LIMIT + 1)
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result = await tool.execute({"prompt": over_prompt})
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output = json.loads(result[0].text)
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assert output["status"] == "requires_file_prompt"
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@pytest.mark.asyncio
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async def test_empty_prompt_no_file(self):
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"""Test empty prompt without prompt.txt file."""
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tool = ChatTool()
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(parts=[MagicMock(text="Success")]),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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result = await tool.execute({"prompt": ""})
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output = json.loads(result[0].text)
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assert output["status"] == "success"
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@pytest.mark.asyncio
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async def test_prompt_file_read_error(self):
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"""Test handling when prompt.txt can't be read."""
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tool = ChatTool()
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bad_file = "/nonexistent/prompt.txt"
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with patch.object(tool, "create_model") as mock_create_model:
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mock_model = MagicMock()
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mock_response = MagicMock()
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mock_response.candidates = [
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MagicMock(
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content=MagicMock(parts=[MagicMock(text="Success")]),
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finish_reason="STOP",
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)
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]
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mock_model.generate_content.return_value = mock_response
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mock_create_model.return_value = mock_model
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# Should continue with empty prompt when file can't be read
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result = await tool.execute({"prompt": "", "files": [bad_file]})
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output = json.loads(result[0].text)
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assert output["status"] == "success"
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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