feat：新增sub_agent，暂时用于emoji选择；修改部分配置位置
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SengokuCola
@@ -1,16 +1,40 @@
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"""send_emoji 内置工具。"""
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from datetime import datetime
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from random import sample
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from secrets import token_hex
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from typing import Any, Dict, Optional
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import asyncio
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from pydantic import BaseModel, Field as PydanticField
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from src.chat.emoji_system.emoji_manager import emoji_manager
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from src.chat.emoji_system.maisaka_tool import send_emoji_for_maisaka
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from src.common.data_models.message_component_data_model import ImageComponent, MessageSequence, TextComponent
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from src.common.data_models.image_data_model import MaiEmoji
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from src.common.logger import get_logger
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from src.core.tooling import ToolExecutionContext, ToolExecutionResult, ToolInvocation, ToolSpec
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from src.maisaka.context_messages import LLMContextMessage
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from src.llm_models.payload_content.resp_format import RespFormat, RespFormatType
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from src.maisaka.context_messages import LLMContextMessage, ReferenceMessage, ReferenceMessageType, SessionBackedMessage
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from .context import BuiltinToolRuntimeContext
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logger = get_logger("maisaka_builtin_send_emoji")
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_EMOJI_SUB_AGENT_CONTEXT_LIMIT = 12
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_EMOJI_SUB_AGENT_MAX_TOKENS = 240
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_EMOJI_SUB_AGENT_SAMPLE_SIZE = 20
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_EMOJI_SUCCESS_MESSAGE = "???????"
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class EmojiSelectionResult(BaseModel):
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"""表情包子代理的结构化选择结果。"""
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emoji_id: str = PydanticField(default="", description="选中的候选表情包 ID。")
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matched_emotion: str = PydanticField(default="", description="本次命中的情绪标签，可为空。")
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reason: str = PydanticField(default="", description="简短选择理由。")
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def get_tool_spec() -> ToolSpec:
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"""获取 send_emoji 工具声明。"""
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@@ -33,6 +57,105 @@ def get_tool_spec() -> ToolSpec:
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)
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async def _build_emoji_candidate_message(emoji: MaiEmoji, candidate_id: str) -> SessionBackedMessage:
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"""构建供子代理挑选的图片候选消息。"""
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image_bytes = await asyncio.to_thread(emoji.full_path.read_bytes)
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raw_message = MessageSequence(
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[
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TextComponent(f"ID: {candidate_id}"),
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ImageComponent(binary_hash=str(emoji.file_hash or ""), binary_data=image_bytes),
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]
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)
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return SessionBackedMessage(
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raw_message=raw_message,
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visible_text=f"ID: {candidate_id}",
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timestamp=datetime.now(),
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source_kind="emoji_candidate",
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)
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async def _select_emoji_with_sub_agent(
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tool_ctx: BuiltinToolRuntimeContext,
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requested_emotion: str,
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reasoning: str,
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context_texts: list[str],
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sample_size: int,
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) -> tuple[MaiEmoji | None, str]:
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"""通过临时子代理从候选表情包中选出一个结果。"""
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available_emojis = list(emoji_manager.emojis)
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if not available_emojis:
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return None, ""
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effective_sample_size = min(max(sample_size, 1), _EMOJI_SUB_AGENT_SAMPLE_SIZE, len(available_emojis))
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sampled_emojis = sample(available_emojis, effective_sample_size)
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candidate_map: dict[str, MaiEmoji] = {}
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candidate_messages: list[LLMContextMessage] = []
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for emoji in sampled_emojis:
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candidate_id = token_hex(4)
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while candidate_id in candidate_map:
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candidate_id = token_hex(4)
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candidate_map[candidate_id] = emoji
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candidate_messages.append(await _build_emoji_candidate_message(emoji, candidate_id))
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context_text = "\n".join(context_texts[-5:]) if context_texts else "（暂无额外上下文）"
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system_prompt = (
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"你是 Maisaka 的临时表情包选择子代理。\n"
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"你会收到一段群聊上下文，以及若干条候选表情包消息。每条候选消息里都有一个临时 ID。\n"
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"你的任务是根据上下文、当前语气和发送意图，从候选里选出最合适的一个表情包。\n"
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"必须只从候选消息中选择，不能编造新的 ID。\n"
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"如果提供了 requested_emotion，请优先考虑与其接近的候选；如果没有完全匹配，则选择最符合上下文语气的候选。\n"
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"你必须返回一个 JSON 对象（json object），不要输出任何 JSON 之外的内容。\n"
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'返回格式固定为：{"emoji_id":"候选ID","matched_emotion":"情绪标签","reason":"简短理由"}'
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)
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prompt_message = ReferenceMessage(
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content=(
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f"[选择任务]\n"
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f"requested_emotion: {requested_emotion or '未指定'}\n"
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f"reasoning: {reasoning or '辅助表达当前语气和情绪'}\n"
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f"recent_context:\n{context_text}\n"
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'请只输出 JSON。'
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),
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timestamp=datetime.now(),
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reference_type=ReferenceMessageType.TOOL_HINT,
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remaining_uses_value=1,
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display_prefix="[表情包选择任务]",
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)
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response = await tool_ctx.runtime.run_sub_agent(
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context_message_limit=_EMOJI_SUB_AGENT_CONTEXT_LIMIT,
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system_prompt=system_prompt,
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extra_messages=[prompt_message, *candidate_messages],
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max_tokens=_EMOJI_SUB_AGENT_MAX_TOKENS,
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response_format=RespFormat(
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format_type=RespFormatType.JSON_SCHEMA,
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schema=EmojiSelectionResult,
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),
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)
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try:
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selection = EmojiSelectionResult.model_validate_json(response.content or "")
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except Exception as exc:
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logger.warning(f"{tool_ctx.runtime.log_prefix} 表情包子代理结果解析失败，将回退到候选首项: {exc}")
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fallback_emoji = sampled_emojis[0] if sampled_emojis else None
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return fallback_emoji, requested_emotion
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selected_emoji = candidate_map.get(selection.emoji_id.strip())
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if selected_emoji is None:
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logger.warning(
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f"{tool_ctx.runtime.log_prefix} 表情包子代理返回了无效 ID: {selection.emoji_id!r}，将回退到候选首项"
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)
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fallback_emoji = sampled_emojis[0] if sampled_emojis else None
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return fallback_emoji, requested_emotion
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matched_emotion = selection.matched_emotion.strip()
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if not matched_emotion:
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matched_emotion = requested_emotion.strip()
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return selected_emoji, matched_emotion
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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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@@ -64,6 +187,13 @@ async def handle_tool(
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requested_emotion=emotion,
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reasoning=tool_ctx.engine.last_reasoning_content,
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context_texts=context_texts,
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emoji_selector=lambda requested_emotion, reasoning, context_texts, sample_size: _select_emoji_with_sub_agent(
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tool_ctx,
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requested_emotion,
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reasoning,
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list(context_texts or []),
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sample_size,
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),
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)
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except Exception as exc:
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logger.exception(f"{tool_ctx.runtime.log_prefix} 发送表情包时发生异常: {exc}")
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@@ -74,28 +204,29 @@ async def handle_tool(
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structured_content=structured_result,
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)
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structured_result["description"] = send_result.description
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structured_result["emotion"] = list(send_result.emotions)
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structured_result["matched_emotion"] = send_result.matched_emotion
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structured_result["message"] = send_result.message
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if send_result.success:
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structured_result["message"] = _EMOJI_SUCCESS_MESSAGE
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logger.info(
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f"{tool_ctx.runtime.log_prefix} 表情包发送成功 "
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f"描述={send_result.description!r} 情绪标签={send_result.emotions} "
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f"请求情绪={emotion!r} 命中情绪={send_result.matched_emotion!r}"
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f"{tool_ctx.runtime.log_prefix} ??????? "
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f"??={send_result.description!r} ????={send_result.emotions} "
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f"????={emotion!r} ????={send_result.matched_emotion!r}"
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)
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tool_ctx.append_sent_emoji_to_chat_history(
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emoji_base64=send_result.emoji_base64,
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success_message=send_result.message,
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success_message=_EMOJI_SUCCESS_MESSAGE,
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)
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structured_result["success"] = True
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return tool_ctx.build_success_result(
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invocation.tool_name,
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send_result.message,
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_EMOJI_SUCCESS_MESSAGE,
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structured_content=structured_result,
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)
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structured_result["description"] = send_result.description
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structured_result["emotion"] = list(send_result.emotions)
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structured_result["matched_emotion"] = send_result.matched_emotion
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structured_result["message"] = send_result.message
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logger.warning(
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f"{tool_ctx.runtime.log_prefix} 表情包发送失败 "
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f"请求情绪={emotion!r} 错误信息={send_result.message}"
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