6a2632da70
将 Clover 从上层产品包旧仓库中独立出来,建立专属版本控制。 当前状态=纵切片端到端已打通(登录→选品→出文出图→审核→下载包), M1文案质量去套路化已验收。此提交作为后续按核销清单逐条修复的基线。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
"""
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app/services/flywheel_service.py — 飞轮信号写入 + 偏好上下文聚合
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preference_collector：三信号入口（选文案/选图/审核）写入 preference_events。
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preference_aggregator：查最近50条 → 最常选角度 + 打回原因近3条原文拼 prompt。
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飞轮不暴露独立埋点端点，只由业务接口内部调用（契约红线）。
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"""
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import logging
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from typing import Any
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from sqlalchemy import desc, func
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from sqlalchemy.orm import Session
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from app.constants.enums import SIGNAL_WEIGHTS, DataOwnership, SignalType
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from app.middleware.workspace_guard import CurrentUser
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from app.models.flywheel import PreferenceEvent
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from app.models.task import GenerationTask
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logger = logging.getLogger(__name__)
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# 实时聚合窗口：最近50条事件
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_AGGREGATION_WINDOW = 50
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# 冷启动阈值：不足5条信号用产品档案冷启动
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_COLD_START_THRESHOLD = 5
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def record_signal(
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db: Session,
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current_user: CurrentUser,
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task: GenerationTask,
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signal_type: str,
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candidate_id: int | None = None,
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angle_label: str | None = None,
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reason: str | None = None,
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) -> None:
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"""
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写入飞轮信号。
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workspace_id + product_id 都必须有（基石C + 按产品分开学）。
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signal_weight 用枚举默认值，北哥可校准。
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data_ownership 默认 client_data（选择行为归客户）。
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"""
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weight = SIGNAL_WEIGHTS.get(signal_type, 0)
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event = PreferenceEvent(
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workspace_id=current_user.workspace_id,
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product_id=task.product_id,
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task_id=task.id,
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user_id=current_user.user_id,
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signal_type=signal_type,
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signal_weight=weight,
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candidate_id=candidate_id,
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angle_label=angle_label,
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reason=reason,
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data_ownership=DataOwnership.CLIENT_DATA,
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)
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try:
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db.add(event)
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db.commit()
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logger.info(
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"Flywheel signal: type=%s weight=%s user=%s product=%s",
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signal_type, weight, current_user.user_id, task.product_id,
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)
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except Exception:
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db.rollback()
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logger.error(
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"Failed to write preference_event: type=%s user=%s",
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signal_type, current_user.user_id,
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)
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raise
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def get_preference_context(
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db: Session, workspace_id: int, product_id: int
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) -> dict[str, Any]:
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"""
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实时聚合偏好上下文（最近50条 events）。
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返回：recent_preference摘要 + reject_reasons近3条 + injected_count。
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不足5条 → 冷启动提示（产品档案兜底，由 AIE prompt 层读 products.custom_prompt）。
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按 workspace_id + product_id 严格过滤（不串数据，基石C）。
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"""
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recent = (
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db.query(PreferenceEvent)
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.filter(
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PreferenceEvent.workspace_id == workspace_id,
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PreferenceEvent.product_id == product_id,
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)
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.order_by(desc(PreferenceEvent.created_at))
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.limit(_AGGREGATION_WINDOW)
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.all()
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)
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if len(recent) < _COLD_START_THRESHOLD:
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return {
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"recent_preference": "信号不足，使用产品档案基线（冷启动）",
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"reject_reasons": [],
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"injected_count": len(recent),
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}
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# 统计最常被选中的角度
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angle_counts: dict[str, int] = {}
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for ev in recent:
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if ev.signal_type in (SignalType.TEXT_SELECT, SignalType.APPROVE) and ev.angle_label:
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angle_counts[ev.angle_label] = angle_counts.get(ev.angle_label, 0) + 1
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top_angles = sorted(angle_counts.items(), key=lambda x: x[1], reverse=True)[:3]
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if top_angles:
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pref_desc = "；".join(f"{a}（已选{c}次）" for a, c in top_angles)
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preference_summary = f"最近偏好：{pref_desc}"
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else:
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preference_summary = "暂无明显角度偏好"
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# 取最近3条打回原因原文（不做 AI 归纳，契约§3）
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reject_reasons = [
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ev.reason for ev in recent
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if ev.signal_type == SignalType.REJECT_WITH_REASON and ev.reason
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][:3]
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return {
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"recent_preference": preference_summary,
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"reject_reasons": reject_reasons,
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"injected_count": len(recent),
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}
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