批次3-P1-3: process_h5_ai_reply管线化重构（主函数312行→76行，try/except 11对→1对，9步骤函数）+ D1止血（路由意图超时15s→8s）
This commit is contained in:
Simon
@@ -224,7 +224,7 @@ class Settings(BaseSettings):
|
||||
# Dify 审批意图识别应用 API Key
|
||||
approval_dify_api_key: str = ""
|
||||
# Dify 审批意图识别请求超时（秒）
|
||||
approval_dify_timeout: int = 15
|
||||
approval_dify_timeout: int = 8 # v4.0 批次3 D1 止血：15s→8s（路由检测与主Dify串行叠加 15+30=45s → 8+30=38s）
|
||||
# 审批意图置信度阈值（≥ 此值才触发审批卡片）
|
||||
approval_confidence_threshold: float = 0.7
|
||||
|
||||
|
||||
+209
-197
@@ -1002,77 +1002,51 @@ async def _push_asset_recommends(
|
||||
# 资产推荐失败不影响主对话流程
|
||||
|
||||
|
||||
async def process_h5_ai_reply(
|
||||
conversation_id: str,
|
||||
employee_id: str,
|
||||
content: str,
|
||||
dify_conversation_id=None,
|
||||
msg_type: str = "text",
|
||||
media_url: str = None,
|
||||
):
|
||||
"""H5 发送消息后的 AI 回复处理（asyncio.create_task 入口）。
|
||||
# =============================================================================
|
||||
# 管线步骤函数（v4.0 批次 3：process_h5_ai_reply 管线化重构）
|
||||
# =============================================================================
|
||||
# 设计：主函数从 200+ 行/11 对 try/except 收敛为 ~40 行编排代码，
|
||||
# 每步一个函数，步骤内部自管异常，主函数零嵌套。
|
||||
# 行为承诺：与原 v3.2 实现外部行为一致（仅结构调整 + v3.0 降级结果补 type 字段）。
|
||||
# =============================================================================
|
||||
|
||||
v2.0 改造（2026-07-13）：
|
||||
- AI 回复从流式 SSE 改为 blocking + JSON 结构化输出
|
||||
- Dify 返回 {text, action, options} JSON → 后端解析 → 双 WS 推送
|
||||
- 聊天气泡收到 ai_reply（text + options），侧边栏收到 dynamic_recommend（action）
|
||||
- 新增 ai_thinking 指示器，用户发送后立即看到"正在思考..."
|
||||
|
||||
v2.1 改造（2026-07-13 Phase 4）：
|
||||
- 新增图片消息处理分支（msg_type=image）
|
||||
- 图片 → VisionService.analyze_screenshot() → 视觉描述 → 融合到用户文字
|
||||
- 消息融合：查询最近 5 秒内员工的文字消息，与图片描述合并后传给 Dify
|
||||
- 降级：VisionService 失败/低置信度 → 使用原始文字或提示用户描述问题
|
||||
|
||||
流程：
|
||||
1. BYOD 关键词拦截 → byod_card 卡片
|
||||
2. 路由关键词拦截 → 名片推荐
|
||||
3. 本地快判断（打招呼/呼叫人工）→ 同步引导
|
||||
4. ★ 图片消息处理（Phase 4A）→ VisionService 分析 → 内容增强
|
||||
5. ★ 结构化 AI 回复（blocking + JSON 解析 + 双 WS 推送）
|
||||
6. 任意异常 → 推 ai_reply_failed
|
||||
|
||||
Args:
|
||||
conversation_id: 会话 ID
|
||||
employee_id: 员工企微 UserID
|
||||
content: 消息文本内容
|
||||
dify_conversation_id: Dify 会话 ID（用于多轮上下文）
|
||||
msg_type: 消息类型（text/image/file），默认 text
|
||||
media_url: 媒体文件 URL（图片消息时使用）
|
||||
"""
|
||||
ai_handler = get_shared_ai_handler()
|
||||
factory = _get_session_factory()
|
||||
async with factory() as db:
|
||||
try:
|
||||
# 防御：会话刚创建时可能事务未提交，最多重试 3 次（每次 0.5s）
|
||||
conversation = None
|
||||
async def _step_load_conversation(db, conversation_id: str):
|
||||
"""步骤1：加载会话（重试 3 次，处理事务未提交竞态）。"""
|
||||
for attempt in range(3):
|
||||
conversation = await db.get(Conversation, conversation_id)
|
||||
if conversation:
|
||||
break
|
||||
return conversation
|
||||
if attempt < 2:
|
||||
await asyncio.sleep(0.5)
|
||||
# 刷新 session 以看到已提交的数据
|
||||
await db.rollback()
|
||||
|
||||
if not conversation:
|
||||
logger.warning(f"后台 AI 任务：会话不存在（重试3次后） {conversation_id}")
|
||||
return
|
||||
return None
|
||||
|
||||
# === BYOD 关键词拦截（仅文本消息）===
|
||||
# 图片消息的 content 是占位符（如 "[图片] 截图"），跳过关键词拦截
|
||||
|
||||
async def _step_byod_intercept(db, conversation, employee_id, content, msg_type) -> bool:
|
||||
"""步骤2：BYOD 关键词拦截。命中返回 True（终止管线）。"""
|
||||
if msg_type == "text" and _byod_keyword_prefilter(content):
|
||||
await _handle_byod_query(db, conversation, employee_id, content)
|
||||
return
|
||||
return True
|
||||
return False
|
||||
|
||||
# === 业务路由检测（仅文本消息）===
|
||||
if msg_type == "text" and routing_keyword_prefilter(content):
|
||||
routed = await _handle_routing(db, conversation, employee_id, content)
|
||||
if routed:
|
||||
return
|
||||
|
||||
# === 本地快判断：打招呼 / 呼叫人工（仅文本消息）===
|
||||
if msg_type == "text" and (ai_handler.is_greeting(content) or ai_handler.is_call_human(content)):
|
||||
async def _step_routing_intercept(db, conversation, employee_id, content, msg_type) -> bool:
|
||||
"""步骤3：非IT业务路由拦截。命中并发送名片返回 True（终止管线）。"""
|
||||
if msg_type != "text" or not routing_keyword_prefilter(content):
|
||||
return False
|
||||
return await _handle_routing(db, conversation, employee_id, content)
|
||||
|
||||
|
||||
async def _step_local_quick_reply(db, conversation, employee_id, content, msg_type, dify_conversation_id) -> bool:
|
||||
"""步骤4：本地快判断（打招呼/呼叫人工）。命中返回 True（终止管线）。"""
|
||||
if msg_type != "text":
|
||||
return False
|
||||
ai_handler = get_shared_ai_handler()
|
||||
if not (ai_handler.is_greeting(content) or ai_handler.is_call_human(content)):
|
||||
return False
|
||||
result = await ai_handler.handle_message(
|
||||
content=content,
|
||||
dify_conversation_id=dify_conversation_id,
|
||||
@@ -1083,125 +1057,131 @@ async def process_h5_ai_reply(
|
||||
result.is_guidance, result.should_count,
|
||||
result.should_transfer, result.dify_conversation_id,
|
||||
)
|
||||
return
|
||||
return True
|
||||
|
||||
# === ★ v2.1 图片消息处理（Phase 4A/4B）===
|
||||
# 做什么：检测到图片消息 → 调用 VisionService 分析截图 →
|
||||
# 将视觉描述与用户文字融合 → 传给 Dify 推理
|
||||
# 为什么：Dify 文本模型无法"看"图片，需要先将图片转为文字描述
|
||||
# 降级：VisionService 失败 → 使用原始 content 继续流程
|
||||
enriched_content = content # 默认使用原始内容
|
||||
if msg_type == "image" and media_url:
|
||||
logger.info(
|
||||
f"图片消息检测: conversation={conversation_id}, "
|
||||
f"media_url={media_url}"
|
||||
)
|
||||
|
||||
async def _step_enrich_image(db, content, msg_type, media_url, conversation_id, employee_id) -> str:
|
||||
"""步骤5：图片消息增强（VisionService 分析 -> 视觉描述融合）。失败降级为原文。"""
|
||||
if msg_type != "image" or not media_url:
|
||||
return content
|
||||
logger.info(f"图片消息检测: conversation={conversation_id}, media_url={media_url}")
|
||||
try:
|
||||
enriched_content = await _enrich_image_content(
|
||||
db=db,
|
||||
media_url=media_url,
|
||||
original_content=content,
|
||||
conversation_id=conversation_id,
|
||||
employee_id=employee_id,
|
||||
enriched = await _enrich_image_content(
|
||||
db=db, media_url=media_url, original_content=content,
|
||||
conversation_id=conversation_id, employee_id=employee_id,
|
||||
)
|
||||
logger.info(
|
||||
f"图片内容增强完成: original_len={len(content)}, "
|
||||
f"enriched_len={len(enriched_content)}"
|
||||
f"图片内容增强完成: original_len={len(content)}, enriched_len={len(enriched)}"
|
||||
)
|
||||
return enriched
|
||||
except Exception as vision_err:
|
||||
logger.error(
|
||||
f"VisionService 处理失败，降级为纯文本: {vision_err}"
|
||||
)
|
||||
logger.error(f"VisionService 处理失败，降级为纯文本: {vision_err}")
|
||||
# 降级：使用原始 content，AI 会收到 "[图片] 截图" 这样的占位符
|
||||
# Dify 会回复"我收到了您的截图，请描述一下问题"
|
||||
return content
|
||||
|
||||
# === ★ v2.3 临时修复：Dify 对话历史缺失，为简短回复拼接上下文 ===
|
||||
# 问题：Dify 工作流未配置「对话历史」节点，conversation_id 传递了但 LLM 看不到历史
|
||||
# 改进：查询最近 10 条消息（用户+AI）构建完整对话摘要，含用户原始问题
|
||||
# 触发：消息短（<=50字符）、无问号、无换行 → 拼接后传给 Dify
|
||||
# 后续：Dify 工作流配置对话历史后可移除此修复
|
||||
enriched_content = await _enrich_with_last_ai_context(
|
||||
db, conversation_id, enriched_content
|
||||
)
|
||||
|
||||
# === ★ Neo4j 知识图谱查询（新增 v3.0）===
|
||||
# 做什么：在调用 Dify 之前先查询知识图谱
|
||||
# 为什么：简单问题可以直接从图谱返回解决方案，响应更快
|
||||
# 效果：简单问题响应从 3-15秒 → 毫秒级
|
||||
logger.info(f"图谱检查: msg_type={msg_type}, content_len={len(enriched_content) if enriched_content else 0}")
|
||||
if msg_type == "text" and enriched_content:
|
||||
async def _step_graph_shortcut(db, conversation, employee_id, enriched_content, msg_type) -> bool:
|
||||
"""步骤6：Neo4j 图谱短路。命中返回 True（终止管线）。异常降级继续。"""
|
||||
if msg_type != "text" or not enriched_content:
|
||||
return False
|
||||
try:
|
||||
from app.services.graph_query_service import get_graph_query_service
|
||||
from app.services.neo4j_client import get_neo4j_client
|
||||
|
||||
neo4j_client = await get_neo4j_client()
|
||||
if neo4j_client:
|
||||
if not neo4j_client:
|
||||
return False
|
||||
graph_service = await get_graph_query_service(neo4j_client)
|
||||
if graph_service:
|
||||
solution = await graph_service.find_solution_by_question(
|
||||
enriched_content
|
||||
solution = (
|
||||
await graph_service.find_solution_by_question(enriched_content)
|
||||
if graph_service else None
|
||||
)
|
||||
else:
|
||||
solution = None
|
||||
if solution:
|
||||
if not solution:
|
||||
return False
|
||||
logger.info(
|
||||
f"图谱命中: question={enriched_content[:30]}, "
|
||||
f"solution={solution.action_name}"
|
||||
f"图谱命中: question={enriched_content[:30]}, solution={solution.action_name}"
|
||||
)
|
||||
# 直接返回图谱解决方案，跳过 Dify 调用
|
||||
await _persist_and_push_solution(
|
||||
db, conversation, employee_id, solution
|
||||
)
|
||||
return
|
||||
await _persist_and_push_solution(db, conversation, employee_id, solution)
|
||||
return True
|
||||
except Exception as graph_err:
|
||||
# 图谱查询失败不阻断，继续原有 Dify 流程
|
||||
import traceback
|
||||
logger.warning(f"图谱查询异常（降级继续）: {graph_err}\n{traceback.format_exc()}")
|
||||
return False
|
||||
|
||||
# === ★ v2.0 结构化 AI 回复（替代流式）===
|
||||
# 1. 立即推送 "正在思考..." 指示器
|
||||
# 同时推给员工（气泡动画）和坐席（状态指示）
|
||||
|
||||
def _build_keyword_fallback_result(matched_card, conversation, result=None, source="keyword_fallback"):
|
||||
"""构建关键词降级结果（v3.0 超时降级 / v3.1 无action降级共用）。
|
||||
|
||||
v4.0 批次 3 合并：统一补 "type": "approval_card"（v3.0 原缺此字段，
|
||||
前端 approve-direct-card 渲染依赖它，属于缺陷修复）。
|
||||
"""
|
||||
options = matched_card.get("options") or []
|
||||
return {
|
||||
"text": f"我来帮您提交{matched_card.get('title', '审批')}，请点击下方卡片。",
|
||||
"action": {
|
||||
"type": "approval_card",
|
||||
"card_data": matched_card,
|
||||
"url": options[0].get("url", "") if options else "",
|
||||
},
|
||||
"options": None,
|
||||
"hit": True,
|
||||
"conversation_id": (result or {}).get("conversation_id") or conversation.dify_conversation_id,
|
||||
"is_structured": True,
|
||||
"diagnosis_stage": "recommending" if result else None,
|
||||
"response_time_ms": (result or {}).get("response_time_ms", 0),
|
||||
"source": source,
|
||||
}
|
||||
|
||||
|
||||
async def _step_notify_failure(conversation_id: str, employee_id: str, message: str):
|
||||
"""步骤：统一失败通知（ai_reply_failed WS 推送）。"""
|
||||
try:
|
||||
await ws_manager.broadcast_to_employees([employee_id], {
|
||||
"type": "ai_reply_failed",
|
||||
"data": {"conversation_id": conversation_id, "message": message},
|
||||
})
|
||||
except Exception:
|
||||
# 推送失败也无所谓，员工端 3 秒轮询兜底
|
||||
pass
|
||||
|
||||
|
||||
async def _step_call_dify(db, conversation, employee_id, conversation_id, content, enriched_content, dify_conversation_id):
|
||||
"""步骤7：Dify 主推理（thinking 指示器 + 30s 超时 + 关键词降级）。
|
||||
|
||||
返回结构化结果 dict；
|
||||
超时且降级失败时内部推送 ai_reply_failed 并返回 None（终止管线）；
|
||||
超时但降级成功时已推送降级卡片，返回 None（终止管线）。
|
||||
"""
|
||||
# 1. 推送 "正在思考..." 指示器（员工气泡动画 + 坐席状态指示）
|
||||
try:
|
||||
await ws_manager.broadcast_to_employees([employee_id], {
|
||||
"type": "ai_thinking",
|
||||
"data": {
|
||||
"conversation_id": conversation_id,
|
||||
},
|
||||
"data": {"conversation_id": conversation_id},
|
||||
})
|
||||
except Exception as thinking_err:
|
||||
logger.warning(f"推送 AI 思考指示器失败: {thinking_err}")
|
||||
|
||||
# 坐席端也通知：AI 正在处理此会话的消息
|
||||
try:
|
||||
await ws_manager.broadcast({
|
||||
"type": "ai_thinking",
|
||||
"data": {
|
||||
"conversation_id": conversation_id,
|
||||
"employee_id": employee_id,
|
||||
},
|
||||
"data": {"conversation_id": conversation_id, "employee_id": employee_id},
|
||||
})
|
||||
except Exception:
|
||||
pass # 坐席端通知失败不影响主流程
|
||||
|
||||
# 2. 启动延迟 "仍在思考" 后台任务（15 秒后触发）
|
||||
# 如果 Dify 在 15 秒内返回，此任务会被取消
|
||||
# 2. 启动延迟 "仍在思考" 后台任务（15 秒后触发，Dify 返回则取消）
|
||||
async def _push_still_thinking():
|
||||
"""15 秒后推送 "仍在思考" 提示，缓解用户等待焦虑。"""
|
||||
await asyncio.sleep(15)
|
||||
await ws_manager.broadcast_to_employees([employee_id], {
|
||||
"type": "ai_thinking",
|
||||
"data": {
|
||||
"conversation_id": conversation_id,
|
||||
"status": "still_thinking",
|
||||
},
|
||||
"data": {"conversation_id": conversation_id, "status": "still_thinking"},
|
||||
})
|
||||
|
||||
thinking_task = asyncio.create_task(_push_still_thinking())
|
||||
|
||||
# 3. 调用 Dify（blocking 模式 + JSON 解析 + 30 秒硬超时）
|
||||
# get_structured_reply 内部处理 HTTP 错误和 JSON 解析失败
|
||||
# asyncio.wait_for 处理 30 秒硬超时 → 建议转人工
|
||||
# 注意：图片消息使用 enriched_content（视觉描述+用户文字融合）
|
||||
# 3. 调用 Dify（blocking + 30s 硬超时）
|
||||
ai_handler = get_shared_ai_handler()
|
||||
try:
|
||||
result = await asyncio.wait_for(
|
||||
ai_handler.ai_service.get_structured_reply(
|
||||
@@ -1212,42 +1192,25 @@ async def process_h5_ai_reply(
|
||||
timeout=30,
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
# v3.0: Dify 超时 → 关键词降级匹配
|
||||
# v3.0: Dify 超时 -> 关键词降级匹配
|
||||
thinking_task.cancel()
|
||||
logger.warning(f"Dify 30 秒超时: conversation={conversation_id}，尝试关键词降级")
|
||||
|
||||
from app.services.approval_matcher import get_approval_matcher
|
||||
matcher = get_approval_matcher()
|
||||
matched_card = matcher.match_by_keywords(content)
|
||||
matched_card = get_approval_matcher().match_by_keywords(content)
|
||||
|
||||
if matched_card:
|
||||
logger.info(f"[Fallback] 关键词降级成功: {matched_card.get('title')}")
|
||||
fallback_result = {
|
||||
"text": f"我来帮您提交{matched_card.get('title', '审批')}，请点击下方卡片。",
|
||||
"action": {"card_data": matched_card, "url": matched_card.get("options", [{}])[0].get("url", "")} if matched_card.get("options") else None,
|
||||
"options": None,
|
||||
"hit": True,
|
||||
"conversation_id": conversation.dify_conversation_id,
|
||||
"is_structured": True,
|
||||
"diagnosis_stage": None,
|
||||
"response_time_ms": 0,
|
||||
"source": "keyword_fallback",
|
||||
}
|
||||
fallback_result = _build_keyword_fallback_result(matched_card, conversation)
|
||||
try:
|
||||
await _persist_and_push_structured(db, conversation, employee_id, fallback_result)
|
||||
return
|
||||
return None # 已推送降级卡片，终止管线
|
||||
except Exception as fallback_err:
|
||||
logger.error(f"[Fallback] 降级推送失败: {fallback_err}")
|
||||
|
||||
# 降级也失败 → 建议转人工
|
||||
await ws_manager.broadcast_to_employees([employee_id], {
|
||||
"type": "ai_reply_failed",
|
||||
"data": {
|
||||
"conversation_id": conversation_id,
|
||||
"message": "AI 响应时间较长，建议转人工坐席处理。",
|
||||
},
|
||||
})
|
||||
return
|
||||
# 降级也失败 -> 建议转人工
|
||||
await _step_notify_failure(conversation_id, employee_id, "AI 响应时间较长，建议转人工坐席处理。")
|
||||
return None
|
||||
|
||||
# 4. 取消 "仍在思考" 任务（Dify 已返回）
|
||||
thinking_task.cancel()
|
||||
@@ -1256,61 +1219,110 @@ async def process_h5_ai_reply(
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
# v3.1: Dify 返回但无 action（如诊断 escalate/回复"AI服务暂时不可用"）→ 关键词降级
|
||||
# 这是对 v3.0 的补充：v3.0 只在 asyncio.TimeoutError 触发降级，但 Dify LLM 自身可能误判
|
||||
# 5. v3.1: Dify 返回但无 action（如诊断 escalate）-> 关键词降级
|
||||
if not result.get("action"):
|
||||
from app.services.approval_matcher import get_approval_matcher
|
||||
matcher = get_approval_matcher()
|
||||
matched_card = matcher.match_by_keywords(content)
|
||||
matched_card = get_approval_matcher().match_by_keywords(content)
|
||||
if matched_card:
|
||||
logger.info(f"[Fallback-v3.1] Dify 无action但关键词命中: {matched_card.get('title')}")
|
||||
result = {
|
||||
"text": f"我来帮您提交{matched_card.get('title', '审批')}，请点击下方卡片。",
|
||||
"action": {
|
||||
"type": "approval_card",
|
||||
"card_data": matched_card,
|
||||
"url": matched_card.get("options", [{}])[0].get("url", "") if matched_card.get("options") else "",
|
||||
},
|
||||
"options": None,
|
||||
"hit": True,
|
||||
"conversation_id": result.get("conversation_id") or conversation.dify_conversation_id,
|
||||
"is_structured": True,
|
||||
"diagnosis_stage": "recommending",
|
||||
"response_time_ms": result.get("response_time_ms", 0),
|
||||
"source": "keyword_fallback_v3",
|
||||
}
|
||||
result = _build_keyword_fallback_result(matched_card, conversation, result, "keyword_fallback_v3")
|
||||
|
||||
# 5. 持久化 + 双 WS 推送（ai_reply + dynamic_recommend）
|
||||
# 添加单独异常处理，避免影响主流程
|
||||
return result
|
||||
|
||||
|
||||
async def _step_persist(db, conversation, employee_id, result):
|
||||
"""步骤8：持久化 + 双 WS 推送（ai_reply + dynamic_recommend）。异常不中断管线。"""
|
||||
try:
|
||||
await _persist_and_push_structured(
|
||||
db, conversation, employee_id, result,
|
||||
)
|
||||
await _persist_and_push_structured(db, conversation, employee_id, result)
|
||||
except Exception as persist_err:
|
||||
logger.error(f"[Persist] AI回复持久化失败: {persist_err}", exc_info=True)
|
||||
|
||||
# 6. v3.0 资产推荐推送（L1/L2/L3 分层）
|
||||
# 独立于对话的运维触达通道
|
||||
|
||||
async def _step_assets(db, employee_id, content, result):
|
||||
"""步骤9：资产推荐推送（L1/L2/L3 分层，独立运维触达通道）。异常不中断管线。"""
|
||||
try:
|
||||
await _push_asset_recommends(
|
||||
db, employee_id, content, result,
|
||||
)
|
||||
await _push_asset_recommends(db, employee_id, content, result)
|
||||
except Exception as asset_err:
|
||||
logger.error(f"[Asset] 资产推荐推送失败: {asset_err}", exc_info=True)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# 管线编排主函数（v4.0 批次 3 重构版）
|
||||
# =============================================================================
|
||||
|
||||
async def process_h5_ai_reply(
|
||||
conversation_id: str,
|
||||
employee_id: str,
|
||||
content: str,
|
||||
dify_conversation_id=None,
|
||||
msg_type: str = "text",
|
||||
media_url: str = None,
|
||||
):
|
||||
"""H5 发送消息后的 AI 回复处理（asyncio.create_task 入口）。
|
||||
|
||||
v4.0 批次 3 管线化重构：原 12 步/11 对 try/except 编排为 9 个步骤函数，
|
||||
主函数仅最外层 1 个 try/except，行为与 v3.2 外部表现一致。
|
||||
|
||||
流程：
|
||||
1. _step_load_conversation 加载会话（重试3次）
|
||||
2. _step_byod_intercept BYOD 关键词拦截
|
||||
3. _step_routing_intercept 非IT业务路由拦截（名片推荐）
|
||||
4. _step_local_quick_reply 本地快判断（打招呼/呼叫人工）
|
||||
5. _step_enrich_image 图片消息 VisionService 增强
|
||||
5b. _enrich_with_last_ai_context 简短回复上下文拼接（v2.3）
|
||||
6. _step_graph_shortcut Neo4j 图谱短路
|
||||
7. _step_call_dify Dify 主推理（含超时/无action关键词降级）
|
||||
8. _step_persist 持久化 + 双 WS 推送
|
||||
9. _step_assets 资产推荐推送
|
||||
|
||||
Args:
|
||||
conversation_id: 会话 ID
|
||||
employee_id: 员工企微 UserID
|
||||
content: 消息文本内容
|
||||
dify_conversation_id: Dify 会话 ID（用于多轮上下文）
|
||||
msg_type: 消息类型（text/image/file），默认 text
|
||||
media_url: 媒体文件 URL（图片消息时使用）
|
||||
"""
|
||||
factory = _get_session_factory()
|
||||
async with factory() as db:
|
||||
try:
|
||||
conversation = await _step_load_conversation(db, conversation_id)
|
||||
if not conversation:
|
||||
return
|
||||
|
||||
# 前置拦截管线（任一命中即终止）
|
||||
if await _step_byod_intercept(db, conversation, employee_id, content, msg_type):
|
||||
return
|
||||
if await _step_routing_intercept(db, conversation, employee_id, content, msg_type):
|
||||
return
|
||||
if await _step_local_quick_reply(db, conversation, employee_id, content, msg_type, dify_conversation_id):
|
||||
return
|
||||
|
||||
# 内容增强管线
|
||||
enriched_content = await _step_enrich_image(
|
||||
db, content, msg_type, media_url, conversation_id, employee_id,
|
||||
)
|
||||
enriched_content = await _enrich_with_last_ai_context(
|
||||
db, conversation_id, enriched_content,
|
||||
)
|
||||
|
||||
# 图谱短路
|
||||
if await _step_graph_shortcut(db, conversation, employee_id, enriched_content, msg_type):
|
||||
return
|
||||
|
||||
# 主推理（含 thinking 指示器 + 超时/无action 降级）
|
||||
result = await _step_call_dify(
|
||||
db, conversation, employee_id, conversation_id,
|
||||
content, enriched_content, dify_conversation_id,
|
||||
)
|
||||
if result is None:
|
||||
return # 降级路径已全部处理（超时转人工 或 已推送降级卡片）
|
||||
|
||||
# 后置处理管线
|
||||
await _step_persist(db, conversation, employee_id, result)
|
||||
await _step_assets(db, employee_id, content, result)
|
||||
|
||||
except Exception as e:
|
||||
import traceback
|
||||
# 记录完整的堆栈跟踪信息
|
||||
tb_str = traceback.format_exc()
|
||||
logger.error(f"后台 AI 任务异常: {e}\n堆栈跟踪:\n{tb_str}", exc_info=True)
|
||||
try:
|
||||
await ws_manager.broadcast_to_employees([employee_id], {
|
||||
"type": "ai_reply_failed",
|
||||
"data": {
|
||||
"conversation_id": conversation_id,
|
||||
"message": "AI 服务异常，请转人工坐席或稍后重试。",
|
||||
},
|
||||
})
|
||||
except Exception:
|
||||
# 推送失败也无所谓，员工端 3 秒轮询兜底
|
||||
pass
|
||||
logger.error(f"后台 AI 任务异常: {e}\n堆栈跟踪:\n{traceback.format_exc()}", exc_info=True)
|
||||
await _step_notify_failure(conversation_id, employee_id, "AI 服务异常，请转人工坐席或稍后重试。")
|
||||
|
||||
Reference in New Issue
Block a user