"""reply 内置工具。""" from typing import Any, Optional import traceback from src.chat.replyer.replyer_manager import replyer_manager from src.cli.maisaka_cli_sender import CLI_PLATFORM_NAME, render_cli_message from src.common.data_models.reply_generation_data_models import ReplyGenerationResult from src.common.logger import get_logger from src.config import config as config_module from src.core.tooling import ToolExecutionContext, ToolExecutionResult, ToolInvocation, ToolSpec from src.maisaka.message_adapter import build_visible_text_from_sequence from src.services import send_service from .context import BuiltinToolRuntimeContext logger = get_logger("maisaka_builtin_reply") async def _run_expression_selector(tool_ctx: BuiltinToolRuntimeContext, system_prompt: str) -> str: """运行 replyer 侧表达方式选择子代理，并返回文本结果。""" response = await tool_ctx.runtime.run_sub_agent( context_message_limit=10, system_prompt=system_prompt, request_kind="expression_selector", max_tokens=256, ) return (response.content or "").strip() def get_tool_spec() -> ToolSpec: """获取 reply 工具声明。""" return ToolSpec( name="reply", brief_description="根据当前思考生成并发送一条可见回复。", detailed_description=( "参数说明：\n" "- msg_id：string，必填。要回复的目标用户消息编号。\n" "- set_quote：boolean，可选。以引用回复的方式发送，默认 true。\n" "- reference_info：string，可选。上文中有助于回复的所有参考信息，使用平文本格式。" ), parameters_schema={ "type": "object", "properties": { "msg_id": { "type": "string", "description": "要回复的目标用户消息编号。", }, "set_quote": { "type": "boolean", "description": "以引用回复的方式发送这条回复，不用每句都引用。", "default": True, }, "reference_info": { "type": "string", "description": "有助于回复的信息，之前搜集得到的事实性信息，记忆等，使用平文本格式。", "default": True, }, }, "required": ["msg_id"], }, provider_name="maisaka_builtin", provider_type="builtin", ) def _build_monitor_metadata(reply_result: ReplyGenerationResult) -> dict[str, object]: """从 reply 结果中提取统一监控详情。""" monitor_detail = reply_result.monitor_detail if isinstance(monitor_detail, dict): return {"monitor_detail": monitor_detail} return {} def _build_send_result( *, index: int, segment: str, set_quote: bool, success: bool, message_id: str = "", ) -> dict[str, Any]: """构建分段回复的轻量发送结果。""" return { "index": index, "segment": segment, "set_quote": set_quote, "success": success, "message_id": message_id, } async def handle_tool( tool_ctx: BuiltinToolRuntimeContext, invocation: ToolInvocation, context: Optional[ToolExecutionContext] = None, ) -> ToolExecutionResult: """执行 reply 内置工具。""" latest_thought = context.reasoning if context is not None else invocation.reasoning reference_info = str(invocation.arguments.get("reference_info") or "").strip() target_message_id = str(invocation.arguments.get("msg_id") or "").strip() set_quote = bool(invocation.arguments.get("set_quote", True)) enable_reply_quote = bool(config_module.global_config.chat.enable_reply_quote) effective_set_quote = set_quote and enable_reply_quote if not target_message_id: return tool_ctx.build_failure_result( invocation.tool_name, "reply 工具需要提供有效的 `msg_id` 参数。", ) target_message = tool_ctx.runtime._source_messages_by_id.get(target_message_id) if target_message is None: return tool_ctx.build_failure_result( invocation.tool_name, f"未找到要回复的目标消息，msg_id={target_message_id}", ) try: replyer = replyer_manager.get_replyer( chat_stream=tool_ctx.runtime.chat_stream, request_type="maisaka_replyer", replyer_type="maisaka", ) except Exception: logger.exception( f"{tool_ctx.runtime.log_prefix} 获取回复生成器时发生异常: 目标消息编号={target_message_id}" ) logger.info(traceback.format_exc()) return tool_ctx.build_failure_result( invocation.tool_name, "获取 Maisaka 回复生成器时发生异常。", ) if replyer is None: logger.error(f"{tool_ctx.runtime.log_prefix} 获取 Maisaka 回复生成器失败") return tool_ctx.build_failure_result( invocation.tool_name, "Maisaka 回复生成器当前不可用。", ) replyer_chat_history = list(tool_ctx.runtime._chat_history) try: success, reply_result = await replyer.generate_reply_with_context( reply_reason=latest_thought, reference_info=reference_info, stream_id=tool_ctx.runtime.session_id, reply_message=target_message, chat_history=replyer_chat_history, sub_agent_runner=lambda system_prompt: _run_expression_selector( tool_ctx, system_prompt, ), log_reply=False, ) except Exception as exc: logger.exception( f"{tool_ctx.runtime.log_prefix} 回复生成器执行异常: 目标消息编号={target_message_id} 异常={exc}" ) return tool_ctx.build_failure_result( invocation.tool_name, "生成可见回复时发生异常。", ) reply_metadata = _build_monitor_metadata(reply_result) reply_text = reply_result.completion.response_text.strip() if success else "" if not reply_text: logger.warning( f"{tool_ctx.runtime.log_prefix} 回复生成器返回空文本: " f"目标消息编号={target_message_id} 错误信息={reply_result.error_message!r}" ) return tool_ctx.build_failure_result( invocation.tool_name, "生成可见回复失败。", metadata=reply_metadata, ) reply_sequences = tool_ctx.post_process_reply_message_sequences(reply_text) reply_segments = [build_visible_text_from_sequence(sequence) for sequence in reply_sequences] combined_reply_text = "".join(reply_segments) sent_message_ids: list[str] = [] send_results: list[dict[str, Any]] = [] try: sent = False if tool_ctx.runtime.chat_stream.platform == CLI_PLATFORM_NAME: for index, segment in enumerate(reply_segments): render_cli_message(segment) send_results.append( _build_send_result( index=index, segment=segment, set_quote=effective_set_quote if index == 0 else False, success=True, ) ) sent = True else: for index, reply_sequence in enumerate(reply_sequences): segment = reply_segments[index] segment_set_quote = effective_set_quote if index == 0 else False sent_message = await send_service._send_to_target_with_message( message_sequence=reply_sequence, stream_id=tool_ctx.runtime.session_id, processed_plain_text=segment, set_reply=segment_set_quote, reply_message=target_message if segment_set_quote else None, selected_expressions=reply_result.selected_expression_ids or None, typing=index > 0, sync_to_maisaka_history=True, maisaka_source_kind="guided_reply", ) sent = sent_message is not None if not sent: send_results.append( _build_send_result( index=index, segment=segment, set_quote=segment_set_quote, success=False, ) ) break sent_message_id = str(getattr(sent_message, "message_id", "") or "").strip() if sent_message_id: sent_message_ids.append(sent_message_id) send_results.append( _build_send_result( index=index, segment=segment, set_quote=segment_set_quote, success=True, message_id=sent_message_id, ) ) except Exception: logger.exception( f"{tool_ctx.runtime.log_prefix} 发送文字消息时发生异常，目标消息编号={target_message_id}" ) return tool_ctx.build_failure_result( invocation.tool_name, "发送可见回复时发生异常。", metadata=reply_metadata, ) if not sent: return tool_ctx.build_failure_result( invocation.tool_name, "可见回复生成成功，但发送失败。", structured_content={ "msg_id": target_message_id, "set_quote": set_quote, "effective_set_quote": effective_set_quote, "reply_segments": reply_segments, "send_results": send_results, }, metadata=reply_metadata, ) target_user_info = target_message.message_info.user_info target_user_name = target_user_info.user_cardname or target_user_info.user_nickname or target_user_info.user_id if tool_ctx.runtime.chat_stream.platform == CLI_PLATFORM_NAME: tool_ctx.append_guided_reply_to_chat_history(combined_reply_text) tool_ctx.runtime._record_reply_sent() reply_metadata["sent_message_ids"] = sent_message_ids reply_metadata["send_results"] = send_results track_reply_effect = getattr(tool_ctx.runtime, "track_reply_effect", None) if track_reply_effect is not None: await track_reply_effect( tool_call_id=invocation.call_id, target_message=target_message, set_quote=effective_set_quote, reply_text=combined_reply_text, reply_segments=reply_segments, planner_reasoning=latest_thought, reference_info=reference_info, tool_context={ "tool_name": invocation.tool_name, "call_id": invocation.call_id, "arguments": dict(invocation.arguments or {}), "reasoning": latest_thought, }, send_results=send_results, reply_metadata=reply_metadata, replyer_context_messages=replyer_chat_history, ) return tool_ctx.build_success_result( invocation.tool_name, "回复已生成并发送。", structured_content={ "msg_id": target_message_id, "set_quote": set_quote, "effective_set_quote": effective_set_quote, "reply_text": combined_reply_text, "reply_segments": reply_segments, "send_results": send_results, "target_user_name": target_user_name, }, metadata=reply_metadata, )