156 lines
6.2 KiB
Python
156 lines
6.2 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, 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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"Use this when you want to ask Gemini questions, brainstorm ideas, get opinions, discuss topics, "
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"share your thinking, or need explanations about concepts and approaches."
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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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"use_websearch": {
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"type": "boolean",
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"description": "Enable web search for documentation, best practices, and current information. Particularly useful for: brainstorming sessions, architectural design discussions, exploring industry best practices, working with specific frameworks/technologies, researching solutions to complex problems, or when current documentation and community insights would enhance the analysis.",
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"default": True,
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},
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"continuation_id": {
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"type": "string",
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"description": "Thread continuation ID for multi-turn conversations. Can be used to continue conversations across different tools. Only provide this if continuing a previous conversation thread.",
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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 [TextContent(type="text", text=ToolOutput(**size_check).model_dump_json())]
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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 (using centralized file handling with filtering)
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if request.files:
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file_content = self._prepare_file_content_for_prompt(
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request.files,
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request.continuation_id,
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"Context files"
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)
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if file_content:
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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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# Add web search instruction if enabled
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websearch_instruction = self.get_websearch_instruction(
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request.use_websearch,
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"""When discussing topics, consider if searches for these would help:
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- Documentation for any technologies or concepts mentioned
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- Current best practices and patterns
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- Recent developments or updates
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- Community discussions and solutions""",
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)
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# Combine system prompt with user content
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full_prompt = f"""{self.get_system_prompt()}{websearch_instruction}
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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 with actionable guidance"""
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return f"{response}\n\n---\n\n**Claude's Turn:** Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand."
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