- 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>
136 lines
4.6 KiB
Python
136 lines
4.6 KiB
Python
"""
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Chat tool - General development chat and collaborative thinking
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"""
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from typing import Any, Dict, List, Optional
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from mcp.types import TextContent
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from pydantic import Field
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from config import TEMPERATURE_BALANCED
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from prompts import CHAT_PROMPT
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from utils import read_files
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from .base import BaseTool, ToolRequest
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from .models import ToolOutput
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class ChatRequest(ToolRequest):
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"""Request model for chat tool"""
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prompt: str = Field(
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...,
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description="Your question, topic, or current thinking to discuss with Gemini",
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)
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files: Optional[List[str]] = Field(
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default_factory=list,
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description="Optional files for context (must be absolute paths)",
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)
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class ChatTool(BaseTool):
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"""General development chat and collaborative thinking tool"""
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def get_name(self) -> str:
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return "chat"
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def get_description(self) -> str:
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return (
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"GENERAL CHAT & COLLABORATIVE THINKING - Use Gemini as your thinking partner! "
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"Perfect for: bouncing ideas during your own analysis, getting second opinions on your plans, "
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"collaborative brainstorming, validating your checklists and approaches, exploring alternatives. "
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"Also great for: explanations, comparisons, general development questions. "
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"Triggers: 'ask gemini', 'brainstorm with gemini', 'get gemini's opinion', 'discuss with gemini', "
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"'share my thinking with gemini', 'explain', 'what is', 'how do I'."
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)
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def get_input_schema(self) -> Dict[str, Any]:
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return {
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"type": "object",
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"properties": {
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"prompt": {
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"type": "string",
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"description": "Your question, topic, or current thinking to discuss with Gemini",
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},
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"files": {
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"type": "array",
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"items": {"type": "string"},
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"description": "Optional files for context (must be absolute paths)",
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},
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"temperature": {
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"type": "number",
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"description": "Response creativity (0-1, default 0.5)",
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"minimum": 0,
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"maximum": 1,
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},
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"thinking_mode": {
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"type": "string",
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"enum": ["minimal", "low", "medium", "high", "max"],
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"description": "Thinking depth: minimal (128), low (2048), medium (8192), high (16384), max (32768)",
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},
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},
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"required": ["prompt"],
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}
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def get_system_prompt(self) -> str:
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return CHAT_PROMPT
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def get_default_temperature(self) -> float:
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return TEMPERATURE_BALANCED
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def get_request_model(self):
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return ChatRequest
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async def execute(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Override execute to check prompt size before processing"""
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# First validate request
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request_model = self.get_request_model()
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request = request_model(**arguments)
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# Check prompt size
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size_check = self.check_prompt_size(request.prompt)
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if size_check:
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return [
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TextContent(
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type="text", text=ToolOutput(**size_check).model_dump_json()
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)
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]
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# Continue with normal execution
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return await super().execute(arguments)
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async def prepare_prompt(self, request: ChatRequest) -> str:
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"""Prepare the chat prompt with optional context files"""
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# Check for prompt.txt in files
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prompt_content, updated_files = self.handle_prompt_file(request.files)
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# Use prompt.txt content if available, otherwise use the prompt field
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user_content = prompt_content if prompt_content else request.prompt
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# Update request files list
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if updated_files is not None:
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request.files = updated_files
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# Add context files if provided
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if request.files:
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file_content, _ = read_files(request.files)
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user_content = f"{user_content}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ===="
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# Check token limits
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self._validate_token_limit(user_content, "Content")
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# Combine system prompt with user content
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full_prompt = f"""{self.get_system_prompt()}
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=== USER REQUEST ===
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{user_content}
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=== END REQUEST ===
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Please provide a thoughtful, comprehensive response:"""
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return full_prompt
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def format_response(self, response: str, request: ChatRequest) -> str:
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"""Format the chat response (no special formatting needed)"""
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return response
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