feat(api): 统一 LLM JSON 调用层 llm_json_call，按域 Schema 迁移 chat/memoir agents

api/app/agents/memoir/extraction_agent.py

@@ -5,15 +5,15 @@ ExtractionAgent：从用户消息中提取 5-stage 状态与 slots。
 
 from __future__ import annotations
 
-import json
 from dataclasses import dataclass
 from typing import Any, Dict
 
 from app.agents.memoir.prompts import get_state_extraction_prompt
+from app.agents.memoir.schemas import StateExtractionOutput
 from app.agents.stage_constants import normalize_chat_stage
-from app.core.langchain_llm import invoke_json_object
+from app.core.config import settings
+from app.core.llm_call import LLMCallError, llm_json_call
 from app.core.logging import get_logger
-from app.core.json_utils import extract_json_payload
 
 logger = get_logger(__name__)
 
@@ -57,14 +57,14 @@ class ExtractionAgent:
                     for k, v in (stage_slots or {}).items()
                 },
             )
-            raw = invoke_json_object(
+            parsed = llm_json_call(
                 llm,
                 prompt,
-                max_tokens=1024,
+                StateExtractionOutput,
+                max_tokens=settings.memoir_extraction_max_tokens,
                 agent="ExtractionAgent.extract",
             )
-            parsed = json.loads(extract_json_payload(raw))
-            raw_slots = parsed.get("slots", {}) or {}
+            raw_slots = parsed.slots or {}
             extracted_slots = {
                 k: v if isinstance(v, str) else str(v) for k, v in raw_slots.items()
             }
@@ -74,12 +74,12 @@ class ExtractionAgent:
                     current_stage, fallback=current_stage
                 )
             else:
-                raw_detected = parsed.get("detected_stage", current_stage)
+                raw_detected = parsed.detected_stage or current_stage
                 detected_stage = normalize_chat_stage(
                     str(raw_detected) if raw_detected is not None else None,
                     fallback=current_stage,
                 )
-        except (json.JSONDecodeError, Exception) as e:
+        except LLMCallError as e:
             logger.warning("ExtractionAgent LLM 解析失败: {}", e)
 
         return ExtractionResult(detected_stage=detected_stage, slots=extracted_slots)