""" Chat tool - General development chat and collaborative thinking This tool provides a conversational interface for general development assistance, brainstorming, problem-solving, and collaborative thinking. It supports file context, images, and conversation continuation for seamless multi-turn interactions. """ from typing import TYPE_CHECKING, Any, Optional from pydantic import Field if TYPE_CHECKING: from tools.models import ToolModelCategory from config import TEMPERATURE_BALANCED from systemprompts import CHAT_PROMPT from tools.shared.base_models import COMMON_FIELD_DESCRIPTIONS, ToolRequest from .simple.base import SimpleTool # Field descriptions matching the original Chat tool exactly CHAT_FIELD_DESCRIPTIONS = { "prompt": ( "Your question or idea for collaborative thinking. Provide detailed context, including your goal, what you've tried, and any specific challenges. " "CRITICAL: To discuss code, provide file paths using the 'files' parameter instead of pasting large code blocks here." ), "files": "Absolute full-paths to existing files / folders for context. DO NOT SHORTEN.", "images": ( "Optional images for visual context (must be FULL absolute paths to real files / folders - DO NOT SHORTEN - OR these can be bas64 data)" ), } class ChatRequest(ToolRequest): """Request model for Chat tool""" prompt: str = Field(..., description=CHAT_FIELD_DESCRIPTIONS["prompt"]) files: Optional[list[str]] = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["files"]) images: Optional[list[str]] = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["images"]) class ChatTool(SimpleTool): """ General development chat and collaborative thinking tool using SimpleTool architecture. This tool provides identical functionality to the original Chat tool but uses the new SimpleTool architecture for cleaner code organization and better maintainability. Migration note: This tool is designed to be a drop-in replacement for the original Chat tool with 100% behavioral compatibility. """ def get_name(self) -> str: return "chat" def get_description(self) -> str: return ( "General chat and collaborative thinking partner for brainstorming, development discussion, getting second opinions, and exploring ideas. " "Use for bouncing ideas, validating approaches, asking questions, and getting explanations. " ) def get_system_prompt(self) -> str: return CHAT_PROMPT def get_default_temperature(self) -> float: return TEMPERATURE_BALANCED def get_model_category(self) -> "ToolModelCategory": """Chat prioritizes fast responses and cost efficiency""" from tools.models import ToolModelCategory return ToolModelCategory.FAST_RESPONSE def get_request_model(self): """Return the Chat-specific request model""" return ChatRequest # === Schema Generation === # For maximum compatibility, we override get_input_schema() to match the original Chat tool exactly def get_input_schema(self) -> dict[str, Any]: """ Generate input schema matching the original Chat tool exactly. This maintains 100% compatibility with the original Chat tool by using the same schema generation approach while still benefiting from SimpleTool convenience methods. """ schema = { "type": "object", "properties": { "prompt": { "type": "string", "description": CHAT_FIELD_DESCRIPTIONS["prompt"], }, "files": { "type": "array", "items": {"type": "string"}, "description": CHAT_FIELD_DESCRIPTIONS["files"], }, "images": { "type": "array", "items": {"type": "string"}, "description": CHAT_FIELD_DESCRIPTIONS["images"], }, "model": self.get_model_field_schema(), "temperature": { "type": "number", "description": COMMON_FIELD_DESCRIPTIONS["temperature"], "minimum": 0, "maximum": 1, }, "thinking_mode": { "type": "string", "enum": ["minimal", "low", "medium", "high", "max"], "description": COMMON_FIELD_DESCRIPTIONS["thinking_mode"], }, "use_websearch": { "type": "boolean", "description": COMMON_FIELD_DESCRIPTIONS["use_websearch"], "default": True, }, "continuation_id": { "type": "string", "description": COMMON_FIELD_DESCRIPTIONS["continuation_id"], }, }, "required": ["prompt"] + (["model"] if self.is_effective_auto_mode() else []), } return schema # === Tool-specific field definitions (alternative approach for reference) === # These aren't used since we override get_input_schema(), but they show how # the tool could be implemented using the automatic SimpleTool schema building def get_tool_fields(self) -> dict[str, dict[str, Any]]: """ Tool-specific field definitions for ChatSimple. Note: This method isn't used since we override get_input_schema() for exact compatibility, but it demonstrates how ChatSimple could be implemented using automatic schema building. """ return { "prompt": { "type": "string", "description": CHAT_FIELD_DESCRIPTIONS["prompt"], }, "files": { "type": "array", "items": {"type": "string"}, "description": CHAT_FIELD_DESCRIPTIONS["files"], }, "images": { "type": "array", "items": {"type": "string"}, "description": CHAT_FIELD_DESCRIPTIONS["images"], }, } def get_required_fields(self) -> list[str]: """Required fields for ChatSimple tool""" return ["prompt"] # === Hook Method Implementations === async def prepare_prompt(self, request: ChatRequest) -> str: """ Prepare the chat prompt with optional context files. This implementation matches the original Chat tool exactly while using SimpleTool convenience methods for cleaner code. """ # Use SimpleTool's Chat-style prompt preparation return self.prepare_chat_style_prompt(request) def format_response(self, response: str, request: ChatRequest, model_info: Optional[dict] = None) -> str: """ Format the chat response to match the original Chat tool exactly. """ return ( f"{response}\n\n---\n\nAGENT'S TURN: Evaluate this perspective alongside your analysis to " "form a comprehensive solution and continue with the user's request and task at hand." ) def get_websearch_guidance(self) -> str: """ Return Chat tool-style web search guidance. """ return self.get_chat_style_websearch_guidance()