feat(api): 叙事 prompt、职业上下文、读路径章节、WS 解耦与错误脱敏

- 回忆录：事实边界补充允许清单；传记文体示例与 JSON 叙事要求对齐
- default 职业提示 occupation_context；cadre/military 退休语境
- GET 章节读路径零写入，prepare_chapter_read_view + markdown_for_response
- 文本归一抽到 core/text_normalize；移除弃用 reply 策略与 recompose_chapters_for_story
- ConversationService：WS 连接/用户段落/结束对话；对外错误固定文案
- 测试：HTTP 脱敏契约、章节读视图、occupation 与 background_voice

api/app/features/memoir/oral_normalize.py

@@ -8,64 +8,21 @@
 
 from __future__ import annotations
 
-import json
 from typing import Any
 
 from app.core.config import settings
-from app.core.langchain_llm import invoke_json_object
-from app.core.logging import get_logger
-from app.features.conversation.input_normalize import apply_conversation_input_rules
-from app.features.memoir.memoir_images.json_payload import extract_json_payload
-
-logger = get_logger(__name__)
-
-
-def apply_oral_normalization_rules(text: str) -> str:
-    """确定性规则；与 `apply_conversation_input_rules` 等价（memoir 历史名保留）。"""
-    return apply_conversation_input_rules(text)
+from app.core.text_normalize import apply_oral_rules, llm_normalize_text
 
 
 def _llm_normalize_oral(text: str, llm: Any) -> str | None:
     """仅修正明显错字与同音字，不增事实；失败返回 None。"""
-    if not llm or not (text or "").strip():
-        return None
-    max_in = int(settings.memoir_oral_normalize_llm_max_input_chars)
-    t = (text or "").strip()
-    if len(t) > max_in:
-        logger.debug(
-            "event=oral_normalize_llm_skip reason=input_too_long len={} max={}",
-            len(t),
-            max_in,
-        )
-        return None
-    prompt = f"""你是口述转写纠错助手。只修正明显的同音错别字、别字与标点，使句子通顺可读。
-禁止增加事实、不补充细节、不摘要、不改写句式风格；不得新增人名、地名、数字、事件。
-若原文已通顺或无法确定错误，则照抄输入。
-
-【用户口述】
-{t}
-
-**JSON 输出**：只输出一个合法 JSON 对象。
-{{"normalized_text": "纠错后的完整文本（与输入等意，仅修错字与标点）"}}
-
-只输出 JSON，不要其它文字。"""
-    try:
-        raw = invoke_json_object(
-            llm,
-            prompt,
-            max_tokens=int(settings.memoir_oral_normalize_llm_max_tokens),
-            agent="oral_normalize.llm",
-        )
-        data = json.loads(extract_json_payload(raw))
-        if not isinstance(data, dict):
-            return None
-        out = (data.get("normalized_text") or "").strip()
-        if not out:
-            return None
-        return out
-    except Exception as e:
-        logger.warning("oral_normalize LLM 失败，回退规则结果: {}", e)
-        return None
+    return llm_normalize_text(
+        text,
+        llm,
+        max_input_chars=int(settings.memoir_oral_normalize_llm_max_input_chars),
+        max_tokens=int(settings.memoir_oral_normalize_llm_max_tokens),
+        agent_name="oral_normalize.llm",
+    )
 
 
 def normalize_oral_for_memoir(text: str, *, llm: Any | None = None) -> str:
@@ -82,7 +39,7 @@ def normalize_oral_for_memoir(text: str, *, llm: Any | None = None) -> str:
     if mode == "off":
         return text or ""
 
-    base = apply_oral_normalization_rules(text or "")
+    base = apply_oral_rules(text or "")
     if mode != "llm":
         return base