mirror of
https://github.com/bytedance/deer-flow.git
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rayhpeng
5cb0471af5
Phase 2-C: feedback and follow-up tracking. - FeedbackRow ORM model (rating +1/-1, optional message_id, comment) - FeedbackRepository with CRUD, list_by_run/thread, aggregate stats - Feedback API endpoints: create, list, stats, delete - follow_up_to_run_id in RunCreateRequest (explicit or auto-detected from latest successful run on the thread) - Worker writes follow_up_to_run_id into human_message event metadata - Gateway deps: feedback_repo factory + getter - 17 new tests (14 FeedbackRepository + 3 follow-up association) - 109 total tests pass, zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
"""ORM model for user feedback on runs."""
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from __future__ import annotations
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from datetime import UTC, datetime
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from sqlalchemy import String, Text
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from sqlalchemy.orm import Mapped, mapped_column
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from deerflow.persistence.base import Base
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class FeedbackRow(Base):
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__tablename__ = "feedback"
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feedback_id: Mapped[str] = mapped_column(String(64), primary_key=True)
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run_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
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thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
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owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
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message_id: Mapped[str | None] = mapped_column(String(64))
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# message_id is an optional RunEventStore event identifier —
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# allows feedback to target a specific message or the entire run
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rating: Mapped[int] = mapped_column(nullable=False)
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# +1 (thumbs-up) or -1 (thumbs-down)
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comment: Mapped[str | None] = mapped_column(Text)
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# Optional text feedback from the user
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created_at: Mapped[datetime] = mapped_column(default=lambda: datetime.now(UTC))
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