refactor(eval+memoir)：精简内部评测路由与服务，composite/对话摘要与 judge 能力补强

- 访谈：新增 interview_state_hints，联动 orchestrator 与提示词
- 回忆录：story_pipeline_sync/state/memory/post_commit 与 Celery 任务调整
- 基建：开发用 celery broker、compose/development 脚本、依赖注入
- eval-web：移除数据集/实验/版本等页面与流式轮询，突出 Playground
- 文档与单测同步

api/app/agents/chat/interview_agent.py

@@ -10,6 +10,11 @@ from langchain_core.messages import HumanMessage, SystemMessage
 
 from app.agents.chat.agent_turn import AgentChatTurn
 from app.agents.chat.helpers import format_history_string, get_history_with_window
+from app.agents.chat.interview_state_hints import (
+    apply_duplicate_question_guard,
+    extract_recent_questions,
+    update_recent_questions,
+)
 from app.agents.chat.personas import normalize_interview_persona
 from app.agents.chat.prompt_context import ChatPromptContext
 from app.agents.chat.prompts_conversation import (
@@ -103,7 +108,7 @@ class InterviewAgent:
             text_for_model = self._resolve_text_for_model(
                 user_message, normalized_user_message
             )
-            empty_slots = memoir_state.empty_slots_for_current_stage()
+            empty_slots = memoir_state.prompt_empty_slots_for_current_stage()
             filled_slots = {
                 key: value.snippet
                 for key, value in memoir_state.slots.get(
@@ -120,6 +125,7 @@ class InterviewAgent:
                 max_pairs=settings.chat_history_max_pairs,
                 max_chars=settings.chat_history_max_chars,
             )
+            recent_questions = extract_recent_questions(hw.window)
             conversation_turn_total = hw.turn_total
             all_stages_coverage = memoir_state.all_stages_coverage()
             persona = normalize_interview_persona(settings.chat_interview_persona)
@@ -140,6 +146,9 @@ class InterviewAgent:
                 occupation=occupation,
                 profile_birth_year=profile_birth_year,
                 profile_era_place=profile_era_place,
+                known_facts=memoir_state.known_facts,
+                persona_threads=memoir_state.persona_threads,
+                recent_questions=recent_questions or memoir_state.recent_questions,
             )
             system_prompt = ctx.guided_system_prompt()
             messages: List[Any] = [SystemMessage(content=system_prompt)]
@@ -204,6 +213,15 @@ class InterviewAgent:
             if not out:
                 out = [response_text.strip()[:max_chars]]
             out = nonempty_segments_or_fallback(out, fallback=_FALLBACK_REPLY)
+            out, deduped = apply_duplicate_question_guard(
+                out,
+                state=memoir_state,
+                recent_questions=recent_questions or memoir_state.recent_questions,
+            )
+            updated_recent_questions = update_recent_questions(
+                recent_questions or memoir_state.recent_questions,
+                out,
+            )
             log_agent_summary(
                 logger,
                 "InterviewAgent.generate_response segments={} conversation_id={} "
@@ -212,7 +230,14 @@ class InterviewAgent:
                 conversation_id,
                 max_tokens,
             )
-            return AgentChatTurn(messages=out, skip_tts=False)
+            return AgentChatTurn(
+                messages=out,
+                skip_tts=False,
+                interview_state_meta={
+                    "recent_questions": updated_recent_questions,
+                    "duplicate_question_guard_triggered": deduped,
+                },
+            )
         except Exception as e:
             logger.error("生成回应失败: {}", e, exc_info=True)
             return AgentChatTurn(messages=[_FALLBACK_REPLY], skip_tts=True)
@@ -231,7 +256,7 @@ class InterviewAgent:
         if not self.llm:
             return ["你好呀～ 又见面了，今天有没有哪段回忆或近况想聊聊？"]
         try:
-            empty_slots = memoir_state.empty_slots_for_current_stage()
+            empty_slots = memoir_state.prompt_empty_slots_for_current_stage()
             empty_slots_readable = [SLOT_NAME_MAP.get(s, s) for s in empty_slots]
             persona = normalize_interview_persona(settings.chat_interview_persona)
             prompt = get_opening_prompt(