feat：给planner最终展示添加统一结果

src/chat/replyer/group_generator.py

@@ -33,7 +33,6 @@ from src.person_info.person_info import Person
 from src.core.types import ActionInfo, EventType
 from src.services import llm_service as llm_api
 
-from src.chat.logger.plan_reply_logger import PlanReplyLogger
 from src.memory_system.memory_retrieval import init_memory_retrieval_sys, build_memory_retrieval_prompt
 from src.learners.jargon_explainer_old import explain_jargon_in_context
 from src.chat.utils.common_utils import TempMethodsExpression
@@ -131,22 +130,6 @@ class DefaultReplyer:
                 llm_response.timing["overall_ms"] = round((time.perf_counter() - overall_start) * 1000, 2)
                 llm_response.timing["almost_zero"] = almost_zero_str
                 llm_response.timing["timing_logs"] = timing_logs
-                if log_reply:
-                    try:
-                        PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.session_id,
-                            prompt="",
-                            output=None,
-                            processed_output=None,
-                            model=None,
-                            timing=llm_response.timing,
-                            reasoning=None,
-                            think_level=think_level,
-                            error="build_prompt_failed",
-                            success=False,
-                        )
-                    except Exception:
-                        logger.exception("记录reply日志失败")
                 return False, llm_response
             from src.core.event_bus import event_bus
             from src.chat.event_helpers import build_event_message
@@ -201,21 +184,6 @@ class DefaultReplyer:
                 llm_response.timing_logs = timing_logs
                 llm_response.timing["timing_logs"] = timing_logs
                 llm_response.timing["almost_zero"] = almost_zero_str
-                try:
-                    if log_reply:
-                        PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.session_id,
-                            prompt=prompt,
-                            output=content,
-                            processed_output=None,
-                            model=model_name,
-                            timing=llm_response.timing,
-                            reasoning=reasoning_content,
-                            think_level=think_level,
-                            success=True,
-                        )
-                except Exception:
-                    logger.exception("记录reply日志失败")
                 _event_msg = build_event_message(
                     EventType.AFTER_LLM, llm_prompt=prompt, llm_response=llm_response, stream_id=stream_id
                 )
@@ -259,22 +227,6 @@ class DefaultReplyer:
                 llm_response.timing_logs = timing_logs
                 llm_response.timing["timing_logs"] = timing_logs
                 llm_response.timing["almost_zero"] = almost_zero_str
-                if log_reply:
-                    try:
-                        PlanReplyLogger.log_reply(
-                            chat_id=self.chat_stream.session_id,
-                            prompt=prompt or "",
-                            output=None,
-                            processed_output=None,
-                            model=model_name,
-                            timing=llm_response.timing,
-                            reasoning=None,
-                            think_level=think_level,
-                            error=str(llm_e),
-                            success=False,
-                        )
-                    except Exception:
-                        logger.exception("记录reply日志失败")
                 return False, llm_response  # LLM 调用失败则无法生成回复
 
             return True, llm_response

src/chat/replyer/maisaka_generator.py

@@ -5,8 +5,11 @@ from typing import Awaitable, Callable, Dict, List, Optional, Tuple
 import random
 import time
 
+from rich.panel import Panel
+
 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.data_models.reply_generation_data_models import (
     GenerationMetrics,
     LLMCompletionResult,
@@ -27,6 +30,7 @@ from src.maisaka.context_messages import (
     ToolResultMessage,
 )
 from src.maisaka.message_adapter import parse_speaker_content
+from src.maisaka.prompt_cli_renderer import PromptCLIVisualizer
 
 from .maisaka_expression_selector import maisaka_expression_selector
 
@@ -365,9 +369,23 @@ class MaisakaReplyGenerator:
         result.completion.request_prompt = prompt
         show_replyer_prompt = bool(getattr(global_config.debug, "show_replyer_prompt", False))
         show_replyer_reasoning = bool(getattr(global_config.debug, "show_replyer_reasoning", False))
+        preview_chat_id = self._resolve_session_id(stream_id) or "unknown"
 
         if show_replyer_prompt:
-            logger.info(f"\nMaisaka 回复器提示词:\n{prompt}\n")
+            console.print(
+                Panel(
+                    PromptCLIVisualizer.build_text_access_panel(
+                        prompt,
+                        category="replyer",
+                        chat_id=preview_chat_id,
+                        request_kind="replyer",
+                        subtitle=f"流ID: {preview_chat_id}",
+                    ),
+                    title="Maisaka 回复器 Prompt",
+                    border_style="bright_yellow",
+                    padding=(0, 1),
+                )
+            )
 
         llm_started_at = time.perf_counter()
         try:

src/chat/replyer/maisaka_generator_multi.py

@@ -444,13 +444,17 @@ class MaisakaReplyGenerator:
         preview_chat_id = self._resolve_session_id(stream_id)
         replyer_prompt_section: RenderableType | None = None
         if show_replyer_prompt:
-            replyer_prompt_section = PromptCLIVisualizer.build_text_section(
-                prompt_preview,
-                category="replyer",
-                chat_id=preview_chat_id,
-                request_kind="replyer",
-                subtitle=f"流ID: {preview_chat_id}",
-                folded=global_config.debug.fold_maisaka_thinking,
+            replyer_prompt_section = Panel(
+                PromptCLIVisualizer.build_text_access_panel(
+                    prompt_preview,
+                    category="replyer",
+                    chat_id=preview_chat_id,
+                    request_kind="replyer",
+                    subtitle=f"流ID: {preview_chat_id}",
+                ),
+                title="Reply Prompt",
+                border_style="bright_yellow",
+                padding=(0, 1),
             )
 
         llm_started_at = time.perf_counter()