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
2025-06-10 07:20:24 +04:00
parent ab007fb4b2
commit 7ea790ef88
36 changed files with 1540 additions and 176 deletions

View File

@@ -16,13 +16,15 @@ Key Features:
from typing import Any, Dict, List, Optional
from mcp.types import TextContent
from pydantic import Field
from config import MAX_CONTEXT_TOKENS, TEMPERATURE_ANALYTICAL
from config import TEMPERATURE_ANALYTICAL
from prompts import REVIEW_CODE_PROMPT
from utils import check_token_limit, read_files
from utils import read_files
from .base import BaseTool, ToolRequest
from .models import ToolOutput
class ReviewCodeRequest(ToolRequest):
@@ -128,6 +130,25 @@ class ReviewCodeTool(BaseTool):
def get_request_model(self):
return ReviewCodeRequest
async def execute(self, arguments: Dict[str, Any]) -> List[TextContent]:
"""Override execute to check focus_on size before processing"""
# First validate request
request_model = self.get_request_model()
request = request_model(**arguments)
# Check focus_on size if provided
if request.focus_on:
size_check = self.check_prompt_size(request.focus_on)
if size_check:
return [
TextContent(
type="text", text=ToolOutput(**size_check).model_dump_json()
)
]
# Continue with normal execution
return await super().execute(arguments)
async def prepare_prompt(self, request: ReviewCodeRequest) -> str:
"""
Prepare the code review prompt with customized instructions.
@@ -144,16 +165,22 @@ class ReviewCodeTool(BaseTool):
Raises:
ValueError: If the code exceeds token limits
"""
# Check for prompt.txt in files
prompt_content, updated_files = self.handle_prompt_file(request.files)
# If prompt.txt was found, use it as focus_on
if prompt_content:
request.focus_on = prompt_content
# Update request files list
if updated_files is not None:
request.files = updated_files
# Read all requested files, expanding directories as needed
file_content, summary = read_files(request.files)
# Validate that the code fits within model context limits
within_limit, estimated_tokens = check_token_limit(file_content)
if not within_limit:
raise ValueError(
f"Code too large (~{estimated_tokens:,} tokens). "
f"Maximum is {MAX_CONTEXT_TOKENS:,} tokens."
)
self._validate_token_limit(file_content, "Code")
# Build customized review instructions based on review type
review_focus = []