feat：落库麦麦文件夹，需要我帮你稳稳的接住replyer的log吗？

feat2

src/chat/replyer/maisaka_generator_multi.py

@@ -1,15 +1,20 @@
+import random
+import time
 from dataclasses import dataclass, field
 from datetime import datetime
 from typing import Dict, List, Optional, Tuple
-import random
-import time
 
+from rich.console import Group, RenderableType
+from rich.panel import Panel
+from rich.text import Text
 from sqlmodel import select
 
 from src.chat.message_receive.chat_manager import BotChatSession
+from src.chat.message_receive.message import SessionMessage
+from src.cli.console import console
 from src.common.database.database import get_db_session
-from src.common.data_models.message_component_data_model import MessageSequence, TextComponent
 from src.common.database.database_model import Expression
+from src.common.data_models.message_component_data_model import MessageSequence, TextComponent
 from src.common.data_models.reply_generation_data_models import (
     GenerationMetrics,
     LLMCompletionResult,
@@ -23,9 +28,15 @@ from src.core.types import ActionInfo
 from src.llm_models.payload_content.message import ImageMessagePart, Message, MessageBuilder, RoleType, TextMessagePart
 from src.services.llm_service import LLMServiceClient
 
-from src.chat.message_receive.message import SessionMessage
+from src.maisaka.context_messages import (
-from src.maisaka.context_messages import AssistantMessage, LLMContextMessage, ReferenceMessage, SessionBackedMessage, ToolResultMessage
+    AssistantMessage,
+    LLMContextMessage,
+    ReferenceMessage,
+    SessionBackedMessage,
+    ToolResultMessage,
+)
 from src.maisaka.message_adapter import clone_message_sequence, parse_speaker_content
+from src.maisaka.prompt_cli_renderer import PromptCLIVisualizer
 
 logger = get_logger("replyer")
 
@@ -509,9 +520,17 @@ class MaisakaReplyGenerator:
             return request_messages
 
         result.completion.request_prompt = prompt_preview
-
+        preview_chat_id = self._resolve_session_id(stream_id)
+        replyer_prompt_section: RenderableType | None = None
         if global_config.debug.show_replyer_prompt:
-            logger.info(f"\nMaisaka 回复器提示词：\n{prompt_preview}\n")
+            replyer_prompt_section = PromptCLIVisualizer.build_text_section(
+                prompt_preview,
+                category="replyer",
+                chat_id=preview_chat_id,
+                request_kind="replyer",
+                subtitle=f"会话流标识：{preview_chat_id}",
+                folded=global_config.debug.fold_maisaka_thinking,
+            )
 
         started_at = time.perf_counter()
         try:
@@ -550,5 +569,41 @@ class MaisakaReplyGenerator:
             f"总耗时毫秒={result.metrics.overall_ms} "
             f"已选表达编号={result.selected_expression_ids!r}"
         )
+        if global_config.debug.show_replyer_prompt or global_config.debug.show_replyer_reasoning:
+            summary_lines = [
+                f"会话流标识: {preview_chat_id or 'unknown'}",
+                f"总耗时: {result.metrics.overall_ms} ms",
+            ]
+            if result.selected_expression_ids:
+                summary_lines.append(f"表达习惯编号: {result.selected_expression_ids!r}")
+
+            renderables: List[RenderableType] = [Text("\n".join(summary_lines))]
+            if replyer_prompt_section is not None:
+                renderables.append(replyer_prompt_section)
+            if global_config.debug.show_replyer_reasoning and result.completion.reasoning_text:
+                renderables.append(
+                    Panel(
+                        Text(result.completion.reasoning_text),
+                        title="回复器思考",
+                        border_style="magenta",
+                        padding=(0, 1),
+                    )
+                )
+            renderables.append(
+                Panel(
+                    Text(response_text),
+                    title="回复结果",
+                    border_style="green",
+                    padding=(0, 1),
+                )
+            )
+            console.print(
+                Panel(
+                    Group(*renderables),
+                    title="MaiSaka 回复器结果",
+                    border_style="bright_yellow",
+                    padding=(0, 1),
+                )
+            )
         result.text_fragments = [response_text]
         return True, result

src/common/logger_color_and_mapping.py

@@ -31,6 +31,8 @@ MODULE_COLORS: Dict[str, Tuple[str, Optional[str], bool]] = {
     "llm_models": ("#008080", None, False),
     "remote": ("#6c6c6c", None, False),  # 深灰色，更不显眼
     "planner": ("#008080", None, False),
+    "maisaka_reasoning_engine": ("#008080", None, False),
+    "maisaka_runtime": ("#ff5fff", None, False),
     "relation": ("#af87af", None, False),  # 柔和的紫色，不刺眼
     # 聊天相关模块
     "hfc": ("#d787af", None, False),  # 柔和的粉色，不显眼但保持粉色系

src/maisaka/chat_loop_service.py

@@ -10,10 +10,8 @@ import json
 import random
 
 from pydantic import BaseModel, Field as PydanticField
-from rich.console import Group
+from rich.console import RenderableType
 from rich.panel import Panel
-
-from src.cli.console import console
 from src.common.data_models.llm_service_data_models import LLMGenerationOptions
 from src.common.logger import get_logger
 from src.common.prompt_i18n import load_prompt
@@ -53,6 +51,7 @@ class ChatResponse:
     built_message_count: int
     completion_tokens: int
     total_tokens: int
+    prompt_section: Optional[RenderableType] = None
 
 
 class ToolFilterSelection(BaseModel):
@@ -765,30 +764,17 @@ class MaisakaChatLoopService:
         if isinstance(raw_tool_definitions, list):
             all_tools = [item for item in raw_tool_definitions if isinstance(item, dict)]
 
+        prompt_section: RenderableType | None = None
         if global_config.debug.show_maisaka_thinking:
-            panel_title, panel_border_style = PromptCLIVisualizer.get_request_panel_style(request_kind)
             image_display_mode: str = "path_link" if global_config.maisaka.show_image_path else "legacy"
-            if global_config.debug.fold_maisaka_thinking:
+            prompt_section = PromptCLIVisualizer.build_prompt_section(
-                prompt_renderable = PromptCLIVisualizer.build_prompt_access_panel(
+                built_messages,
-                    built_messages,
+                category="planner" if request_kind != "timing_gate" else "timing_gate",
-                    request_kind=request_kind,
+                chat_id=self._session_id,
-                    selection_reason=selection_reason,
+                request_kind=request_kind,
-                    image_display_mode=image_display_mode,
+                selection_reason=selection_reason,
-                )
+                image_display_mode=image_display_mode,
-            else:
+                folded=global_config.debug.fold_maisaka_thinking,
-                ordered_panels = PromptCLIVisualizer.build_prompt_panels(
-                    built_messages,
-                    image_display_mode=image_display_mode,
-                )
-                prompt_renderable = Group(*ordered_panels)
-            console.print(
-                Panel(
-                    prompt_renderable,
-                    title=panel_title,
-                    subtitle=selection_reason,
-                    border_style=panel_border_style,
-                    padding=(0, 1),
-                )
             )
 
         request_started_at = perf_counter()
@@ -809,8 +795,6 @@ class MaisakaChatLoopService:
                 interrupt_flag=self._interrupt_flag,
             ),
         )
-        request_elapsed = perf_counter() - request_started_at
-        logger.info(f"规划器请求完成，耗时={request_elapsed:.3f} 秒")
 
         prompt_stats_text = PromptCLIVisualizer.build_prompt_stats_text(
             selected_history_count=len(selected_history),
@@ -865,6 +849,7 @@ class MaisakaChatLoopService:
             built_message_count=len(built_messages),
             completion_tokens=completion_tokens,
             total_tokens=total_tokens,
+            prompt_section=prompt_section,
         )
 
     @staticmethod

src/maisaka/prompt_cli_renderer.py

@@ -2,24 +2,26 @@
 
 from __future__ import annotations
 
-import hashlib
-import html
-import json
 from base64 import b64decode
 from dataclasses import dataclass
 from enum import Enum
 from pathlib import Path
-from urllib.parse import quote
 from typing import Any, Dict, List, Literal
+from urllib.parse import quote
 
+import hashlib
+import html
+import json
 import tempfile
 
 from pydantic import BaseModel, Field as PydanticField
 from rich.console import Group, RenderableType
-from rich.pretty import Pretty
 from rich.panel import Panel
+from rich.pretty import Pretty
 from rich.text import Text
 
+from .prompt_preview_logger import PromptPreviewLogger
+
 PROJECT_ROOT = Path(__file__).parent.parent.parent.absolute().resolve()
 DATA_IMAGE_DIR = PROJECT_ROOT / "data" / "images"
 
@@ -53,8 +55,6 @@ class _MessageRenderResult:
 class PromptCLIVisualizer:
     """负责构建 CLI 下 prompt 展示所需的所有可视化组件。"""
 
-    PROMPT_DUMP_DIR = Path(tempfile.gettempdir()) / "maisaka_prompt_dumps"
-
     @staticmethod
     def get_request_panel_style(request_kind: str) -> tuple[str, str]:
         """返回不同请求类型对应的标题与边框颜色。"""
@@ -62,6 +62,8 @@ class PromptCLIVisualizer:
         normalized_kind = str(request_kind or "planner").strip().lower()
         if normalized_kind == "timing_gate":
             return "MaiSaka 大模型请求 - Timing Gate 子代理", "bright_magenta"
+        if normalized_kind == "replyer":
+            return "MaiSaka 回复器 Prompt", "bright_yellow"
         if normalized_kind == "sub_agent":
             return "MaiSaka 大模型请求 - 子代理", "bright_blue"
         return "MaiSaka 大模型请求 - 对话单步", "cyan"
@@ -133,19 +135,9 @@ class PromptCLIVisualizer:
 
     @staticmethod
     def _build_file_uri(file_path: Path) -> str:
-        normalized = file_path.as_posix()
+        normalized = file_path.resolve().as_posix()
         return f"file:///{quote(normalized, safe='/:')}"
 
-    @classmethod
-    def _build_prompt_dump_base_path(cls, messages: list[Any]) -> Path:
-        cls.PROMPT_DUMP_DIR.mkdir(parents=True, exist_ok=True)
-        try:
-            payload = json.dumps(messages, ensure_ascii=False, default=str)
-        except Exception:
-            payload = repr(messages)
-        digest = hashlib.sha256(payload.encode("utf-8")).hexdigest()
-        return cls.PROMPT_DUMP_DIR / digest
-
     @staticmethod
     def _build_official_image_path(image_format: str, image_base64: str) -> Path | None:
         normalized_format = PromptCLIVisualizer._normalize_image_format(image_format)
@@ -611,15 +603,14 @@ class PromptCLIVisualizer:
         cls,
         messages: list[Any],
         *,
+        category: str,
+        chat_id: str,
         request_kind: str,
         selection_reason: str,
         image_display_mode: Literal["legacy", "path_link"],
-    ) -> Panel:
+    ) -> RenderableType:
-        """构建用于查看完整 prompt 的入口面板。"""
+        """构建用于查看完整 prompt 的折叠入口内容。"""
 
-        base_path = cls._build_prompt_dump_base_path(messages)
-        prompt_dump_path = base_path.with_suffix(".txt")
-        prompt_dump_path.write_text(cls._build_prompt_dump_text(messages), encoding="utf-8")
         viewer_messages: list[dict[str, Any]] = []
         for message in messages:
             if isinstance(message, dict):
@@ -641,15 +632,22 @@ class PromptCLIVisualizer:
                 ]
             viewer_messages.append(normalized_message)
 
-        viewer_html_path = base_path.with_suffix(".html")
+        prompt_dump_text = cls._build_prompt_dump_text(messages)
-        viewer_html_path.write_text(
+        viewer_html_text = cls._build_prompt_viewer_html(
-            cls._build_prompt_viewer_html(
+            viewer_messages,
-                viewer_messages,
+            request_kind=request_kind,
-                request_kind=request_kind,
+            selection_reason=selection_reason,
-                selection_reason=selection_reason,
-            ),
-            encoding="utf-8",
         )
+        saved_paths = PromptPreviewLogger.save_preview_files(
+            chat_id,
+            category,
+            {
+                ".html": viewer_html_text,
+                ".txt": prompt_dump_text,
+            },
+        )
+        viewer_html_path = saved_paths[".html"]
+        prompt_dump_path = saved_paths[".txt"]
         viewer_uri = cls._build_file_uri(viewer_html_path)
         dump_uri = cls._build_file_uri(prompt_dump_path)
 
@@ -659,10 +657,198 @@ class PromptCLIVisualizer:
             Text.from_markup(f"[link={viewer_uri}]点击在浏览器打开富文本 Prompt 视图[/link]", style="bold green"),
             Text.from_markup(f"[link={dump_uri}]点击直接打开 Prompt 文本[/link]", style="cyan"),
         )
+        return body
+
+    @classmethod
+    def build_prompt_section(
+        cls,
+        messages: list[Any],
+        *,
+        category: str,
+        chat_id: str,
+        request_kind: str,
+        selection_reason: str,
+        image_display_mode: Literal["legacy", "path_link"],
+        folded: bool,
+    ) -> Panel:
+        """构建用于嵌入结果面板中的 Prompt 区块。"""
+
+        panel_title, panel_border_style = cls.get_request_panel_style(request_kind)
+        if folded:
+            prompt_renderable = cls.build_prompt_access_panel(
+                messages,
+                category=category,
+                chat_id=chat_id,
+                request_kind=request_kind,
+                selection_reason=selection_reason,
+                image_display_mode=image_display_mode,
+            )
+        else:
+            ordered_panels = cls.build_prompt_panels(
+                messages,
+                image_display_mode=image_display_mode,
+            )
+            prompt_renderable = Group(*ordered_panels)
+
         return Panel(
-            body,
+            prompt_renderable,
-            title=Text(" Prompt 查看入口 ", style="bold white on blue"),
+            title=panel_title,
-            border_style="blue",
+            subtitle=selection_reason,
+            border_style=panel_border_style,
+            padding=(0, 1),
+        )
+
+    @classmethod
+    def _build_text_preview_html(
+        cls,
+        content: str,
+        *,
+        request_kind: str,
+        subtitle: str,
+    ) -> str:
+        panel_title, _ = cls.get_request_panel_style(request_kind)
+        subtitle_html = f"<div class='subtitle'>{html.escape(subtitle)}</div>" if subtitle.strip() else ""
+        return f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+  <meta charset="utf-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>{html.escape(panel_title)}</title>
+  <style>
+    :root {{
+      --bg: #f6f7fb;
+      --card: #ffffff;
+      --border: #d7dfeb;
+      --text: #18212f;
+      --muted: #5b6878;
+      --shadow: 0 18px 40px rgba(15, 23, 42, 0.08);
+    }}
+    body {{
+      margin: 0;
+      background:
+        radial-gradient(circle at top left, rgba(202, 138, 4, 0.12), transparent 24%),
+        radial-gradient(circle at top right, rgba(29, 78, 216, 0.10), transparent 24%),
+        var(--bg);
+      color: var(--text);
+      font-family: "Segoe UI", "PingFang SC", "Microsoft YaHei", sans-serif;
+    }}
+    .page {{
+      width: min(1200px, calc(100vw - 40px));
+      margin: 24px auto 40px;
+    }}
+    .hero {{
+      background: linear-gradient(135deg, #ffffff 0%, #fff8eb 100%);
+      border: 1px solid var(--border);
+      border-radius: 20px;
+      box-shadow: var(--shadow);
+      padding: 20px 24px;
+      margin-bottom: 18px;
+    }}
+    .title {{
+      font-size: 26px;
+      font-weight: 700;
+      letter-spacing: 0.02em;
+    }}
+    .subtitle {{
+      margin-top: 10px;
+      color: var(--muted);
+      white-space: pre-wrap;
+    }}
+    .content-card {{
+      background: var(--card);
+      border: 1px solid var(--border);
+      border-radius: 18px;
+      box-shadow: var(--shadow);
+      padding: 18px 20px;
+    }}
+    pre {{
+      margin: 0;
+      white-space: pre-wrap;
+      word-break: break-word;
+      font-family: "Cascadia Mono", "JetBrains Mono", "Consolas", monospace;
+      font-size: 13px;
+      line-height: 1.6;
+      color: #1e293b;
+    }}
+  </style>
+</head>
+<body>
+  <main class="page">
+    <header class="hero">
+      <div class="title">{html.escape(panel_title)}</div>
+      {subtitle_html}
+    </header>
+    <section class="content-card">
+      <pre>{html.escape(content)}</pre>
+    </section>
+  </main>
+</body>
+</html>"""
+
+    @classmethod
+    def build_text_access_panel(
+        cls,
+        content: str,
+        *,
+        category: str,
+        chat_id: str,
+        request_kind: str,
+        subtitle: str,
+    ) -> RenderableType:
+        """构建文本型 Prompt 的折叠入口内容。"""
+
+        html_content = cls._build_text_preview_html(content, request_kind=request_kind, subtitle=subtitle)
+        saved_paths = PromptPreviewLogger.save_preview_files(
+            chat_id,
+            category,
+            {
+                ".html": html_content,
+                ".txt": content,
+            },
+        )
+        viewer_html_path = saved_paths[".html"]
+        text_dump_path = saved_paths[".txt"]
+        viewer_uri = cls._build_file_uri(viewer_html_path)
+        dump_uri = cls._build_file_uri(text_dump_path)
+
+        body = Group(
+            Text(f"富文本预览：{viewer_html_path}", style="bold green"),
+            Text(f"原始文本备份：{text_dump_path}", style="magenta"),
+            Text.from_markup(f"[link={viewer_uri}]点击在浏览器打开富文本 Prompt 视图[/link]", style="bold green"),
+            Text.from_markup(f"[link={dump_uri}]点击直接打开 Prompt 文本[/link]", style="cyan"),
+        )
+        return body
+
+    @classmethod
+    def build_text_section(
+        cls,
+        content: str,
+        *,
+        category: str,
+        chat_id: str,
+        request_kind: str,
+        subtitle: str,
+        folded: bool,
+    ) -> Panel:
+        """构建文本型 Prompt 的嵌入区块。"""
+
+        panel_title, panel_border_style = cls.get_request_panel_style(request_kind)
+        if folded:
+            prompt_renderable = cls.build_text_access_panel(
+                content,
+                category=category,
+                chat_id=chat_id,
+                request_kind=request_kind,
+                subtitle=subtitle,
+            )
+        else:
+            prompt_renderable = Text(content)
+
+        return Panel(
+            prompt_renderable,
+            title=panel_title,
+            subtitle=subtitle,
+            border_style=panel_border_style,
             padding=(0, 1),
         )
 

src/maisaka/prompt_preview_logger.py

@@ -0,0 +1,83 @@
+"""Maisaka Prompt 预览落盘器。"""
+
+from __future__ import annotations
+
+import re
+import time
+from pathlib import Path
+from typing import Dict
+from uuid import uuid4
+
+from src.config.config import global_config
+
+
+class PromptPreviewLogger:
+    """负责保存 Maisaka Prompt 预览文件并控制目录容量。"""
+
+    _BASE_DIR = Path("logs") / "maisaka_prompt"
+    _TRIM_COUNT = 100
+    _SAFE_NAME_PATTERN = re.compile(r"[^A-Za-z0-9._-]+")
+
+    @classmethod
+    def _get_max_per_chat(cls) -> int:
+        """从配置中获取每个聊天流最大保存的预览数量。"""
+
+        return getattr(global_config.chat, "plan_reply_log_max_per_chat", 1000)
+
+    @classmethod
+    def _normalize_chat_id(cls, chat_id: str) -> str:
+        normalized_chat_id = cls._SAFE_NAME_PATTERN.sub("_", str(chat_id or "").strip()).strip("._")
+        if normalized_chat_id:
+            return normalized_chat_id
+        return "unknown_chat"
+
+    @classmethod
+    def save_preview_files(
+        cls,
+        chat_id: str,
+        category: str,
+        files: Dict[str, str],
+    ) -> Dict[str, Path]:
+        """保存同一份 Prompt 预览的多个文件并执行超量清理。"""
+
+        normalized_category = cls._normalize_chat_id(category)
+        chat_dir = (cls._BASE_DIR / normalized_category / cls._normalize_chat_id(chat_id)).resolve()
+        chat_dir.mkdir(parents=True, exist_ok=True)
+        stem = f"{int(time.time() * 1000)}_{uuid4().hex[:8]}"
+        saved_paths: Dict[str, Path] = {}
+        try:
+            for suffix, content in files.items():
+                normalized_suffix = suffix if suffix.startswith(".") else f".{suffix}"
+                file_path = chat_dir / f"{stem}{normalized_suffix}"
+                file_path.write_text(content, encoding="utf-8")
+                saved_paths[normalized_suffix] = file_path
+        finally:
+            cls._trim_overflow(chat_dir)
+        return saved_paths
+
+    @classmethod
+    def _trim_overflow(cls, chat_dir: Path) -> None:
+        """超过阈值时按批次删除最老的若干组预览文件。"""
+
+        grouped_files: dict[str, list[Path]] = {}
+        for file_path in chat_dir.iterdir():
+            if not file_path.is_file():
+                continue
+            grouped_files.setdefault(file_path.stem, []).append(file_path)
+
+        max_per_chat = cls._get_max_per_chat()
+        if len(grouped_files) <= max_per_chat:
+            return
+
+        sorted_groups = sorted(
+            grouped_files.items(),
+            key=lambda item: min(path.stat().st_mtime for path in item[1]),
+        )
+        overflow_count = len(grouped_files) - max_per_chat
+        trim_count = min(len(sorted_groups), max(cls._TRIM_COUNT, overflow_count))
+        for _, file_group in sorted_groups[:trim_count]:
+            for old_file in file_group:
+                try:
+                    old_file.unlink()
+                except FileNotFoundError:
+                    continue

src/maisaka/reasoning_engine.py

@@ -290,6 +290,7 @@ class MaisakaReasoningEngine:
                                 planner_response=timing_response.content or "",
                                 tool_calls=timing_response.tool_calls,
                                 tool_results=timing_tool_results,
+                                prompt_section=timing_response.prompt_section,
                             )
                             if timing_action != "continue":
                                 logger.info(
@@ -340,6 +341,7 @@ class MaisakaReasoningEngine:
                                     planner_response=response.content or "",
                                     tool_calls=response.tool_calls,
                                     tool_results=tool_result_summaries,
+                                    prompt_section=response.prompt_section,
                                 )
                                 if should_pause:
                                     break
@@ -349,6 +351,7 @@ class MaisakaReasoningEngine:
                                 selected_history_count=response.selected_history_count,
                                 prompt_tokens=response.prompt_tokens,
                                 planner_response=response.content or "",
+                                prompt_section=response.prompt_section,
                             )
                             if not response.content:
                                 break

src/maisaka/runtime.py

@@ -5,6 +5,7 @@ from typing import Any, Literal, Optional, Sequence
 import asyncio
 import time
 
+from rich.console import Group, RenderableType
 from rich.panel import Panel
 from rich.text import Text
 
@@ -493,6 +494,7 @@ class MaisakaHeartFlowChatting:
         planner_response: str = "",
         tool_calls: Optional[list[Any]] = None,
         tool_results: Optional[list[str]] = None,
+        prompt_section: Optional[RenderableType] = None,
     ) -> None:
         """在终端展示当前聊天流的上下文占用、规划结果与工具摘要。"""
         if not global_config.debug.show_maisaka_thinking:
@@ -505,21 +507,46 @@ class MaisakaHeartFlowChatting:
             f"上下文占用: {selected_history_count}条 / {self._format_token_count(prompt_tokens)}",
         ]
 
+        renderables: list[RenderableType] = [Text("\n".join(body_lines))]
+        if prompt_section is not None:
+            renderables.append(prompt_section)
+
         normalized_response = planner_response.strip()
         if normalized_response:
-            body_lines.extend(["", "Maisaka 返回:", normalized_response])
+            renderables.append(
+                Panel(
+                    Text(normalized_response),
+                    title="Maisaka 返回",
+                    border_style="green",
+                    padding=(0, 1),
+                )
+            )
 
         normalized_tool_calls = self._build_tool_call_summary_lines(tool_calls or [])
         if normalized_tool_calls:
-            body_lines.extend(["", "工具调用:", *normalized_tool_calls])
+            renderables.append(
+                Panel(
+                    Text("\n".join(normalized_tool_calls)),
+                    title="工具调用",
+                    border_style="magenta",
+                    padding=(0, 1),
+                )
+            )
 
         normalized_tool_results = [result.strip() for result in tool_results or [] if isinstance(result, str) and result.strip()]
         if normalized_tool_results:
-            body_lines.extend(["", "工具结果:", *normalized_tool_results])
+            renderables.append(
+                Panel(
+                    Text("\n".join(normalized_tool_results)),
+                    title="工具结果",
+                    border_style="yellow",
+                    padding=(0, 1),
+                )
+            )
 
         console.print(
             Panel(
-                Text("\n".join(body_lines)),
+                Group(*renderables),
                 title="MaiSaka 上下文与结果",
                 border_style="bright_blue",
                 padding=(0, 1),

src/plugin_runtime/host/message_utils.py

@@ -238,15 +238,6 @@ class PluginMessageUtils:
                         logger.info(f"解析转发节点时跳过非字典节点: {node!r}")
                         continue
                     raw_content = node.get("content", [])
-                    logger.info(
-                        "开始解析转发节点: "
-                        f"message_id={node.get('message_id')!r} "
-                        f"user_id={node.get('user_id')!r} "
-                        f"user_nickname={node.get('user_nickname')!r} "
-                        f"user_cardname={node.get('user_cardname')!r} "
-                        f"raw_content_type={type(raw_content).__name__} "
-                        f"raw_content={raw_content!r}"
-                    )
                     node_components: List[StandardMessageComponents] = []
                     if isinstance(raw_content, list):
                         node_components = [
@@ -254,12 +245,6 @@ class PluginMessageUtils:
                             for content in raw_content
                             if isinstance(content, dict)
                         ]
-                    logger.info(
-                        "转发节点解析结果: "
-                        f"message_id={node.get('message_id')!r} "
-                        f"component_types={[component.__class__.__name__ for component in node_components]!r} "
-                        f"component_values={[getattr(component, 'text', None) for component in node_components]!r}"
-                    )
                     if not node_components:
                         logger.warning(
                             "转发节点内容为空，使用占位文本回退: "