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