{"type":"thinking_level_change","id":"9a313f5e","parentId":null,"timestamp":"2026-04-03T01:14:38.334Z","thinkingLevel":"medium"}
{"type":"model_change","id":"3d301f85","parentId":"9a313f5e","timestamp":"2026-04-03T01:14:38.336Z","provider":"anthropic","modelId":"claude-opus-4-6"}
{"type":"custom_message","customType":"gsd-auto","content":"You are executing GSD auto-mode.\n\n## Working Directory\n\nYour working directory is `/home/aux/projects/content-to-kb-automator`. All file reads, writes, and shell commands MUST operate relative to this directory. Do NOT `cd` to any other directory.\n\nA researcher explored the codebase and a planner decomposed the work — you are the executor. The task plan below is your authoritative contract for the slice goal and verification bar, but it is not a substitute for local reality. Verify the referenced files and surrounding code before changing them. Do not do broad re-research or spontaneous re-planning. Small factual corrections, file-path fixes, and local implementation adaptations are part of execution. Escalate to `blocker_discovered: true` only when the slice contract or downstream task graph no longer holds.\n\n\n\n\n\n## Backing Source Artifacts\n- Slice plan: `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/S03-PLAN.md`\n- Task plan source: `.gsd/milestones/M014/slices/S03/tasks/T01-PLAN.md`\n- Prior task summaries in this slice:\n- (no prior tasks)\n\nThen:\n0. Narrate step transitions, key implementation decisions, and verification outcomes as you work. Keep it terse — one line between tool-call clusters, not between every call — but write complete sentences in user-facing prose, not shorthand notes or scratchpad fragments.\n1.  Follow any activated skills before writing code. If no skills match this task, skip this step.\n2. Execute the steps in the inlined task plan, adapting minor local mismatches when the surrounding code differs from the planner's snapshot\n3. Build the real thing. If the task plan says \"create login endpoint\", build an endpoint that actually authenticates against a real store, not one that returns a hardcoded success response. If the task plan says \"create dashboard page\", build a page that renders real data from the API, not a component with hardcoded props. Stubs and mocks are for tests, not for the shipped feature.\n4. Write or update tests as part of execution — tests are verification, not an afterthought. If the slice plan defines test files in its Verification section and this is the first task, create them (they should initially fail).\n5. When implementing non-trivial runtime behavior (async flows, API boundaries, background processes, error paths), add or preserve agent-usable observability. Skip this for simple changes where it doesn't apply.\n\n   **Background process rule:** Never use bare `command &` to run background processes. The shell's `&` operator leaves stdout/stderr attached to the parent, which causes the Bash tool to hang indefinitely waiting for those streams to close. Always redirect output before backgrounding:\n   - Correct: `command > /dev/null 2>&1 &` or `nohup command > /dev/null 2>&1 &`\n   - Example: `python -m http.server 8080 > /dev/null 2>&1 &` (NOT `python -m http.server 8080 &`)\n   - Preferred: use the `bg_shell` tool if available — it manages process lifecycle correctly without stream-inheritance issues\n6. If the task plan includes a **Failure Modes** section (Q5), implement the error/timeout/malformed handling specified. Verify each dependency's failure path is handled. Skip if the section is absent.\n7. If the task plan includes a **Load Profile** section (Q6), implement protections for the identified 10x breakpoint (connection pooling, rate limiting, pagination, etc.). Skip if absent.\n8. If the task plan includes a **Negative Tests** section (Q7), write the specified negative test cases alongside the happy-path tests — malformed inputs, error paths, and boundary conditions. Skip if absent.\n9. Verify must-haves are met by running concrete checks (tests, commands, observable behaviors)\n10. Run the slice-level verification checks defined in the slice plan's Verification section. Track which pass. On the final task of the slice, all must pass before marking done. On intermediate tasks, partial passes are expected — note which ones pass in the summary.\n11. After the verification gate runs (you'll see gate results in stderr/notify output), populate the `## Verification Evidence` table in your task summary with the check results. Use the `formatEvidenceTable` format: one row per check with command, exit code, verdict (✅ pass / ❌ fail), and duration. If no verification commands were discovered, note that in the section.\n12. If the task touches UI, browser flows, DOM behavior, or user-visible web state:\n   - exercise the real flow in the browser\n   - prefer `browser_batch` when the next few actions are obvious and sequential\n   - prefer `browser_assert` for explicit pass/fail verification of the intended outcome\n   - use `browser_diff` when an action's effect is ambiguous\n   - use console/network/dialog diagnostics when validating async, stateful, or failure-prone UI\n   - record verification in terms of explicit checks passed/failed, not only prose interpretation\n13. If the task plan includes an Observability Impact section, verify those signals directly. Skip this step if the task plan omits the section.\n14. **If execution is running long or verification fails:**\n\n    **Context budget:** You have approximately **~80K chars** reserved for verification context. If you've used most of your context and haven't finished all steps, stop implementing and prioritize writing the task summary with clear notes on what's done and what remains. A partial summary that enables clean resumption is more valuable than one more half-finished step with no documentation. Never sacrifice summary quality for one more implementation step.\n\n    **Debugging discipline:** If a verification check fails or implementation hits unexpected behavior:\n    - Form a hypothesis first. State what you think is wrong and why, then test that specific theory. Don't shotgun-fix.\n    - Change one variable at a time. Make one change, test, observe. Multiple simultaneous changes mean you can't attribute what worked.\n    - Read completely. When investigating, read entire functions and their imports, not just the line that looks relevant.\n    - Distinguish \"I know\" from \"I assume.\" Observable facts (the error says X) are strong evidence. Assumptions (this library should work this way) need verification.\n    - Know when to stop. If you've tried 3+ fixes without progress, your mental model is probably wrong. Stop. List what you know for certain. List what you've ruled out. Form fresh hypotheses from there.\n    - Don't fix symptoms. Understand *why* something fails before changing code. A test that passes after a change you don't understand is luck, not a fix.\n15. **Blocker discovery:** If execution reveals that the remaining slice plan is fundamentally invalid — not just a bug or minor deviation, but a plan-invalidating finding like a wrong API, missing capability, or architectural mismatch — set `blocker_discovered: true` in the task summary frontmatter and describe the blocker clearly in the summary narrative. Do NOT set `blocker_discovered: true` for ordinary debugging, minor deviations, or issues that can be fixed within the current task or the remaining plan. This flag triggers an automatic replan of the slice.\n16. If you made an architectural, pattern, library, or observability decision during this task that downstream work should know about, append it to `.gsd/DECISIONS.md` (read the template at `~/.gsd/agent/extensions/gsd/templates/decisions.md` if the file doesn't exist yet). Not every task produces decisions — only append when a meaningful choice was made.\n17. If you discover a non-obvious rule, recurring gotcha, or useful pattern during execution, append it to `.gsd/KNOWLEDGE.md`. Only add entries that would save future agents from repeating your investigation. Don't add obvious things.\n18. Read the template at `~/.gsd/agent/extensions/gsd/templates/task-summary.md`\n19. Write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/tasks/T01-SUMMARY.md`\n20. Call `gsd_complete_task` with milestone_id, slice_id, task_id, and a summary of what was accomplished. This is your final required step — do NOT manually edit PLAN.md checkboxes. The tool marks the task complete, updates the DB, and renders PLAN.md automatically.\n21. Do not run git commands — the system reads your task summary after completion and creates a meaningful commit from it (type inferred from title, message from your one-liner, key files from frontmatter). Write a clear, specific one-liner in the summary — it becomes the commit message.\n\nAll work stays in your working directory: `/home/aux/projects/content-to-kb-automator`.\n\n**You MUST call `gsd_complete_task` AND write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/tasks/T01-SUMMARY.md` before finishing.**\n\nWhen done, say: \"Task T01 complete.\"\n## Slice Plan Excerpt\nSource: `.gsd/milestones/M014/slices/S03/S03-PLAN.md`\n**Goal:** Add `body_sections_format` column to technique_pages, create `technique_page_videos` association table, and expose both in the API response.\n**Demo:** After this: Alembic migration runs clean. API response includes body_sections_format and source_videos fields.\n\n### Slice Verification\n- `cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; print(TechniquePage.body_sections_format); print('OK')\"` succeeds\n- `cd backend && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('OK')\"` succeeds\n- `alembic upgrade head` runs without error (tested via Docker: `docker exec chrysopedia-api alembic upgrade head`)\n  - Estimate: 30m\n  - Files: alembic/versions/012_multi_source_format.py, backend/models.py, backend/schemas.py\n  - Verify: cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\" && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\"\n- [ ] **T02: Wire source_videos into technique detail endpoint** — Update the technique detail endpoint to eagerly load source_video_links and build the source_videos list on the response. Verify end-to-end with an API call.\n\n## UNIT: Execute Task T01 (\"Alembic migration + SQLAlchemy model + Pydantic schema updates\") — Slice S03 (\"Data Model + Migration\"), Milestone M014\n\n## Resume State\n- No continue file present. Start from the top of the task plan.\n\n## Carry-Forward Context\n- No prior task summaries in this slice.\n\n## Inlined Task Plan (authoritative local execution contract)\nSource: `.gsd/milestones/M014/slices/S03/tasks/T01-PLAN.md`\n\n---\nestimated_steps: 29\nestimated_files: 3\nskills_used: []\n---\n\n# T01: Alembic migration + SQLAlchemy model + Pydantic schema updates\n\nCreate the Alembic migration for the new column and table, update the SQLAlchemy models, and widen the Pydantic API schemas.\n\nThis is the data layer foundation — migration file, model changes, and schema changes. The router wiring comes in T02.\n\n## Steps\n\n1. Create `alembic/versions/012_multi_source_format.py`:\n   - Add `body_sections_format` column to `technique_pages`: `VARCHAR(20)`, `NOT NULL`, `server_default='v1'`\n   - Create `technique_page_videos` table: `id` (UUID PK), `technique_page_id` (UUID FK → technique_pages.id ON DELETE CASCADE), `source_video_id` (UUID FK → source_videos.id ON DELETE CASCADE), `added_at` (TIMESTAMP, server_default=now()), UNIQUE constraint on (technique_page_id, source_video_id)\n   - Downgrade: drop `technique_page_videos` table, drop `body_sections_format` column\n\n2. Update `backend/models.py`:\n   - Add `body_sections_format` mapped column to `TechniquePage`: `String(20)`, default `'v1'`, server_default `'v1'`, nullable=False\n   - Add `TechniquePageVideo` model class with fields matching migration, plus `UniqueConstraint` named `uq_page_video`\n   - Add `sa_relationship` on `TechniquePage`: `source_video_links: Mapped[list[TechniquePageVideo]]` with back_populates\n   - Add `sa_relationship` on `TechniquePageVideo` back to both `TechniquePage` and `SourceVideo`\n   - Note: use `sa_relationship` (the alias) per KNOWLEDGE.md rule about column names shadowing ORM functions\n\n3. Update `backend/schemas.py`:\n   - Change `TechniquePageBase.body_sections` type from `dict | None` to `list | dict | None`\n   - Add `body_sections_format: str = \"v1\"` to `TechniquePageBase`\n   - Add `SourceVideoSummary` schema: `id` (UUID), `filename` (str), `content_type` (str), `added_at` (datetime | None)\n   - Add `source_videos: list[SourceVideoSummary] = Field(default_factory=list)` to `TechniquePageDetail`\n\n## Must-Haves\n\n- [ ] Migration file has both upgrade and downgrade\n- [ ] `body_sections_format` defaults to `'v1'` for existing rows\n- [ ] `TechniquePageVideo` has CASCADE deletes on both FKs\n- [ ] Unique constraint on (technique_page_id, source_video_id)\n- [ ] `body_sections` schema type widened to accept list or dict\n- [ ] `SourceVideoSummary` schema uses `from_attributes=True`\n\n## Verification\n\n- `cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; print(TechniquePage.body_sections_format); print('OK')\"` succeeds\n- `cd backend && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('OK')\"` succeeds\n- `alembic upgrade head` runs without error (tested via Docker: `docker exec chrysopedia-api alembic upgrade head`)\n\n## Inputs\n\n- ``backend/models.py` — existing TechniquePage and SourceVideo models`\n- ``backend/schemas.py` — existing TechniquePageBase, TechniquePageRead, TechniquePageDetail schemas`\n- ``alembic/versions/011_classification_cache_and_stage_rerun.py` — previous migration in chain`\n\n## Expected Output\n\n- ``alembic/versions/012_multi_source_format.py` — new migration adding column and table`\n- ``backend/models.py` — updated with TechniquePageVideo model and body_sections_format column`\n- ``backend/schemas.py` — updated with SourceVideoSummary, widened body_sections type, source_videos on detail`\n\n## Verification\n\ncd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\" && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\"\n","display":false,"id":"860ca2c7","parentId":"3d301f85","timestamp":"2026-04-03T01:14:38.338Z"}
{"type":"message","id":"3a807c89","parentId":"860ca2c7","timestamp":"2026-04-03T01:14:45.029Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me start by reading the existing files I need to modify to understand the current state.","thinkingSignature":"EpcCClkIDBgCKkB2aR732u6VAL4qqoUpQuqKCmd5pfgFOxsxNUU7gTpfEmhBIxksy/qstOAsH+nswmz1IGTrhxBBv359lJpUyBUoMg9jbGF1ZGUtb3B1cy00LTY4ABIM502V7Sf1vXGRF9YHGgzr2CBqcwmqq8wGOmMiMLblcSA/JouYYzze35QPBMGfif86Jix0FrhJw65xI1UMSZzWj6GscRKHhiQq87IY+SpsDko32rZ1K+CJ/b7wwF0A/P3orTPlmVpGV9opqTRSZA5PP58h87vCGUljF3ey109XQeLTe10AqLHjs8vSgGJozk5Urcqdq5fIWcOYKPHgZaoSpPyclu6d0AseQ05OVhJS80z3v6zxKG7oc7cwGAE="},{"type":"text","text":"Starting T01 — data layer foundation for multi-source format support. Let me read the existing models, schemas, and the latest migration."},{"type":"toolCall","id":"toolu_01QstuQ5mqLWpB9yoQzQwZVr","name":"read","arguments":{"path":"backend/models.py"}},{"type":"toolCall","id":"toolu_01K73pQJ5DE4spwyXqGDTjpZ","name":"read","arguments":{"path":"backend/schemas.py"}},{"type":"toolCall","id":"toolu_015mtmdiTZZikjz4LinExBZn","name":"bash","arguments":{"command":"ls alembic/versions/ | sort"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":2,"output":200,"cacheRead":59865,"cacheWrite":4082,"totalTokens":64149,"cost":{"input":0.00001,"output":0.005,"cacheRead":0.029932499999999997,"cacheWrite":0.0255125,"total":0.060454999999999995}},"stopReason":"toolUse","timestamp":1775178878336}}
{"type":"message","id":"ad94013b","parentId":"3a807c89","timestamp":"2026-04-03T01:14:45.039Z","message":{"role":"toolResult","toolCallId":"toolu_01QstuQ5mqLWpB9yoQzQwZVr","toolName":"read","content":[{"type":"text","text":"\"\"\"SQLAlchemy ORM models for the Chrysopedia knowledge base.\n\nSeven entities matching chrysopedia-spec.md §6.1:\n  Creator, SourceVideo, TranscriptSegment, KeyMoment,\n  TechniquePage, RelatedTechniqueLink, Tag\n\"\"\"\n\nfrom __future__ import annotations\n\nimport enum\nimport uuid\nfrom datetime import datetime, timezone\n\nfrom sqlalchemy import (\n    Enum,\n    Float,\n    ForeignKey,\n    Integer,\n    String,\n    Text,\n    UniqueConstraint,\n    func,\n)\nfrom sqlalchemy.dialects.postgresql import ARRAY, JSONB, UUID\nfrom sqlalchemy.orm import Mapped, mapped_column\nfrom sqlalchemy.orm import relationship as sa_relationship\n\nfrom database import Base\n\n\n# ── Enums ────────────────────────────────────────────────────────────────────\n\nclass ContentType(str, enum.Enum):\n    \"\"\"Source video content type.\"\"\"\n    tutorial = \"tutorial\"\n    livestream = \"livestream\"\n    breakdown = \"breakdown\"\n    short_form = \"short_form\"\n\n\nclass ProcessingStatus(str, enum.Enum):\n    \"\"\"Pipeline processing status for a source video.\n\n    User-facing lifecycle: not_started → queued → processing → complete\n    Error branch: processing → error (retrigger resets to queued)\n    \"\"\"\n    not_started = \"not_started\"\n    queued = \"queued\"\n    processing = \"processing\"\n    error = \"error\"\n    complete = \"complete\"\n\n\nclass KeyMomentContentType(str, enum.Enum):\n    \"\"\"Content classification for a key moment.\"\"\"\n    technique = \"technique\"\n    settings = \"settings\"\n    reasoning = \"reasoning\"\n    workflow = \"workflow\"\n\n\nclass SourceQuality(str, enum.Enum):\n    \"\"\"Derived source quality for technique pages.\"\"\"\n    structured = \"structured\"\n    mixed = \"mixed\"\n    unstructured = \"unstructured\"\n\n\nclass RelationshipType(str, enum.Enum):\n    \"\"\"Types of links between technique pages.\"\"\"\n    same_technique_other_creator = \"same_technique_other_creator\"\n    same_creator_adjacent = \"same_creator_adjacent\"\n    general_cross_reference = \"general_cross_reference\"\n\n\n# ── Helpers ──────────────────────────────────────────────────────────────────\n\ndef _uuid_pk() -> Mapped[uuid.UUID]:\n    return mapped_column(\n        UUID(as_uuid=True),\n        primary_key=True,\n        default=uuid.uuid4,\n        server_default=func.gen_random_uuid(),\n    )\n\n\ndef _now() -> datetime:\n    \"\"\"Return current UTC time as a naive datetime (no tzinfo).\n\n    PostgreSQL TIMESTAMP WITHOUT TIME ZONE columns require naive datetimes.\n    asyncpg rejects timezone-aware datetimes for such columns.\n    \"\"\"\n    return datetime.now(timezone.utc).replace(tzinfo=None)\n\n\n# ── Models ───────────────────────────────────────────────────────────────────\n\nclass Creator(Base):\n    __tablename__ = \"creators\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), nullable=False)\n    slug: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    genres: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    folder_name: Mapped[str] = mapped_column(String(255), nullable=False)\n    view_count: Mapped[int] = mapped_column(Integer, default=0, server_default=\"0\")\n    hidden: Mapped[bool] = mapped_column(default=False, server_default=\"false\")\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    videos: Mapped[list[SourceVideo]] = sa_relationship(back_populates=\"creator\")\n    technique_pages: Mapped[list[TechniquePage]] = sa_relationship(back_populates=\"creator\")\n\n\nclass SourceVideo(Base):\n    __tablename__ = \"source_videos\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    creator_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    filename: Mapped[str] = mapped_column(String(500), nullable=False)\n    file_path: Mapped[str] = mapped_column(String(1000), nullable=False)\n    duration_seconds: Mapped[int] = mapped_column(Integer, nullable=True)\n    content_type: Mapped[ContentType] = mapped_column(\n        Enum(ContentType, name=\"content_type\", create_constraint=True),\n        nullable=False,\n    )\n    transcript_path: Mapped[str | None] = mapped_column(String(1000), nullable=True)\n    content_hash: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)\n    processing_status: Mapped[ProcessingStatus] = mapped_column(\n        Enum(ProcessingStatus, name=\"processing_status\", create_constraint=True),\n        default=ProcessingStatus.not_started,\n        server_default=\"not_started\",\n    )\n    classification_data: Mapped[list | None] = mapped_column(JSONB, nullable=True)\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    creator: Mapped[Creator] = sa_relationship(back_populates=\"videos\")\n    segments: Mapped[list[TranscriptSegment]] = sa_relationship(back_populates=\"source_video\")\n    key_moments: Mapped[list[KeyMoment]] = sa_relationship(back_populates=\"source_video\")\n\n\nclass TranscriptSegment(Base):\n    __tablename__ = \"transcript_segments\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    start_time: Mapped[float] = mapped_column(Float, nullable=False)\n    end_time: Mapped[float] = mapped_column(Float, nullable=False)\n    text: Mapped[str] = mapped_column(Text, nullable=False)\n    segment_index: Mapped[int] = mapped_column(Integer, nullable=False)\n    topic_label: Mapped[str | None] = mapped_column(String(255), nullable=True)\n\n    # relationships\n    source_video: Mapped[SourceVideo] = sa_relationship(back_populates=\"segments\")\n\n\nclass KeyMoment(Base):\n    __tablename__ = \"key_moments\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    technique_page_id: Mapped[uuid.UUID | None] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"SET NULL\"), nullable=True\n    )\n    title: Mapped[str] = mapped_column(String(500), nullable=False)\n    summary: Mapped[str] = mapped_column(Text, nullable=False)\n    start_time: Mapped[float] = mapped_column(Float, nullable=False)\n    end_time: Mapped[float] = mapped_column(Float, nullable=False)\n    content_type: Mapped[KeyMomentContentType] = mapped_column(\n        Enum(KeyMomentContentType, name=\"key_moment_content_type\", create_constraint=True),\n        nullable=False,\n    )\n    plugins: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    raw_transcript: Mapped[str | None] = mapped_column(Text, nullable=True)\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    source_video: Mapped[SourceVideo] = sa_relationship(back_populates=\"key_moments\")\n    technique_page: Mapped[TechniquePage | None] = sa_relationship(\n        back_populates=\"key_moments\", foreign_keys=[technique_page_id]\n    )\n\n\nclass TechniquePage(Base):\n    __tablename__ = \"technique_pages\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    creator_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    title: Mapped[str] = mapped_column(String(500), nullable=False)\n    slug: Mapped[str] = mapped_column(String(500), unique=True, nullable=False)\n    topic_category: Mapped[str] = mapped_column(String(255), nullable=False)\n    topic_tags: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    summary: Mapped[str | None] = mapped_column(Text, nullable=True)\n    body_sections: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n    signal_chains: Mapped[list | None] = mapped_column(JSONB, nullable=True)\n    plugins: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    source_quality: Mapped[SourceQuality | None] = mapped_column(\n        Enum(SourceQuality, name=\"source_quality\", create_constraint=True),\n        nullable=True,\n    )\n    view_count: Mapped[int] = mapped_column(Integer, default=0, server_default=\"0\")\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    creator: Mapped[Creator] = sa_relationship(back_populates=\"technique_pages\")\n    key_moments: Mapped[list[KeyMoment]] = sa_relationship(\n        back_populates=\"technique_page\", foreign_keys=[KeyMoment.technique_page_id]\n    )\n    versions: Mapped[list[TechniquePageVersion]] = sa_relationship(\n        back_populates=\"technique_page\", order_by=\"TechniquePageVersion.version_number\"\n    )\n    outgoing_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.source_page_id\", back_populates=\"source_page\"\n    )\n    incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.target_page_id\", back_populates=\"target_page\"\n    )\n\n\nclass RelatedTechniqueLink(Base):\n    __tablename__ = \"related_technique_links\"\n    __table_args__ = (\n        UniqueConstraint(\"source_page_id\", \"target_page_id\", \"relationship\", name=\"uq_technique_link\"),\n    )\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    target_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    relationship: Mapped[RelationshipType] = mapped_column(\n        Enum(RelationshipType, name=\"relationship_type\", create_constraint=True),\n        nullable=False,\n    )\n\n    # relationships\n    source_page: Mapped[TechniquePage] = sa_relationship(\n        foreign_keys=[source_page_id], back_populates=\"outgoing_links\"\n    )\n    target_page: Mapped[TechniquePage] = sa_relationship(\n        foreign_keys=[target_page_id], back_populates=\"incoming_links\"\n    )\n\n\nclass TechniquePageVersion(Base):\n    \"\"\"Snapshot of a TechniquePage before a pipeline re-synthesis overwrites it.\"\"\"\n    __tablename__ = \"technique_page_versions\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    technique_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    version_number: Mapped[int] = mapped_column(Integer, nullable=False)\n    content_snapshot: Mapped[dict] = mapped_column(JSONB, nullable=False)\n    pipeline_metadata: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n\n    # relationships\n    technique_page: Mapped[TechniquePage] = sa_relationship(\n        back_populates=\"versions\"\n    )\n\n\nclass Tag(Base):\n    __tablename__ = \"tags\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    category: Mapped[str] = mapped_column(String(255), nullable=False)\n    aliases: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n\n\n# ── Content Report Enums ─────────────────────────────────────────────────────\n\nclass ReportType(str, enum.Enum):\n    \"\"\"Classification of user-submitted content reports.\"\"\"\n    inaccurate = \"inaccurate\"\n    missing_info = \"missing_info\"\n    wrong_attribution = \"wrong_attribution\"\n    formatting = \"formatting\"\n    other = \"other\"\n\n\nclass ReportStatus(str, enum.Enum):\n    \"\"\"Triage status for content reports.\"\"\"\n    open = \"open\"\n    acknowledged = \"acknowledged\"\n    resolved = \"resolved\"\n    dismissed = \"dismissed\"\n\n\n# ── Content Report ───────────────────────────────────────────────────────────\n\nclass ContentReport(Base):\n    \"\"\"User-submitted report about a content issue.\n\n    Generic: content_type + content_id can reference any entity\n    (technique_page, key_moment, creator, or general).\n    \"\"\"\n    __tablename__ = \"content_reports\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    content_type: Mapped[str] = mapped_column(\n        String(50), nullable=False, doc=\"Entity type: technique_page, key_moment, creator, general\"\n    )\n    content_id: Mapped[uuid.UUID | None] = mapped_column(\n        UUID(as_uuid=True), nullable=True, doc=\"FK to the reported entity (null for general reports)\"\n    )\n    content_title: Mapped[str | None] = mapped_column(\n        String(500), nullable=True, doc=\"Snapshot of entity title at report time\"\n    )\n    report_type: Mapped[ReportType] = mapped_column(\n        Enum(ReportType, name=\"report_type\", create_constraint=True),\n        nullable=False,\n    )\n    description: Mapped[str] = mapped_column(Text, nullable=False)\n    status: Mapped[ReportStatus] = mapped_column(\n        Enum(ReportStatus, name=\"report_status\", create_constraint=True),\n        default=ReportStatus.open,\n        server_default=\"open\",\n    )\n    admin_notes: Mapped[str | None] = mapped_column(Text, nullable=True)\n    page_url: Mapped[str | None] = mapped_column(\n        String(1000), nullable=True, doc=\"URL the user was on when reporting\"\n    )\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    resolved_at: Mapped[datetime | None] = mapped_column(nullable=True)\n\n\n# ── Pipeline Event ───────────────────────────────────────────────────────────\n\nclass PipelineRunStatus(str, enum.Enum):\n    \"\"\"Status of a pipeline run.\"\"\"\n    running = \"running\"\n    complete = \"complete\"\n    error = \"error\"\n    cancelled = \"cancelled\"\n\n\nclass PipelineRunTrigger(str, enum.Enum):\n    \"\"\"What initiated a pipeline run.\"\"\"\n    manual = \"manual\"\n    clean_reprocess = \"clean_reprocess\"\n    auto_ingest = \"auto_ingest\"\n    bulk = \"bulk\"\n    stage_rerun = \"stage_rerun\"\n\n\nclass PipelineRun(Base):\n    \"\"\"A single execution of the pipeline for a video.\n\n    Each trigger/retrigger creates a new run. Events are scoped to a run\n    via run_id, giving a clean audit trail per execution.\n    \"\"\"\n    __tablename__ = \"pipeline_runs\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False, index=True,\n    )\n    run_number: Mapped[int] = mapped_column(\n        Integer, nullable=False, doc=\"Auto-increment per video, 1-indexed\"\n    )\n    trigger: Mapped[PipelineRunTrigger] = mapped_column(\n        Enum(PipelineRunTrigger, name=\"pipeline_run_trigger\", create_constraint=True),\n        nullable=False,\n    )\n    status: Mapped[PipelineRunStatus] = mapped_column(\n        Enum(PipelineRunStatus, name=\"pipeline_run_status\", create_constraint=True),\n        default=PipelineRunStatus.running,\n        server_default=\"running\",\n    )\n    started_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    finished_at: Mapped[datetime | None] = mapped_column(nullable=True)\n    error_stage: Mapped[str | None] = mapped_column(String(50), nullable=True)\n    total_tokens: Mapped[int] = mapped_column(Integer, default=0, server_default=\"0\")\n\n    # relationships\n    video: Mapped[SourceVideo] = sa_relationship()\n    events: Mapped[list[PipelineEvent]] = sa_relationship(\n        back_populates=\"run\", foreign_keys=\"PipelineEvent.run_id\"\n    )\n\n\n# ── Pipeline Event ───────────────────────────────────────────────────────────\n\nclass PipelineEvent(Base):\n    \"\"\"Structured log entry for pipeline execution.\n\n    Captures per-stage start/complete/error/llm_call events with\n    token usage and optional response payloads for debugging.\n    \"\"\"\n    __tablename__ = \"pipeline_events\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    video_id: Mapped[uuid.UUID] = mapped_column(\n        UUID(as_uuid=True), nullable=False, index=True,\n    )\n    run_id: Mapped[uuid.UUID | None] = mapped_column(\n        ForeignKey(\"pipeline_runs.id\", ondelete=\"SET NULL\"), nullable=True, index=True,\n    )\n    stage: Mapped[str] = mapped_column(\n        String(50), nullable=False, doc=\"stage2_segmentation, stage3_extraction, etc.\"\n    )\n    event_type: Mapped[str] = mapped_column(\n        String(30), nullable=False, doc=\"start, complete, error, llm_call\"\n    )\n    prompt_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    completion_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    total_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    model: Mapped[str | None] = mapped_column(String(100), nullable=True)\n    duration_ms: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    payload: Mapped[dict | None] = mapped_column(\n        JSONB, nullable=True, doc=\"LLM response content, error details, stage metadata\"\n    )\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n\n    # Debug mode — full LLM I/O capture columns\n    system_prompt_text: Mapped[str | None] = mapped_column(Text, nullable=True)\n    user_prompt_text: Mapped[str | None] = mapped_column(Text, nullable=True)\n    response_text: Mapped[str | None] = mapped_column(Text, nullable=True)\n\n    # relationships\n    run: Mapped[PipelineRun | None] = sa_relationship(\n        back_populates=\"events\", foreign_keys=[run_id]\n    )\n"}],"isError":false,"timestamp":1775178885038}}
{"type":"message","id":"5be98b30","parentId":"ad94013b","timestamp":"2026-04-03T01:14:45.042Z","message":{"role":"toolResult","toolCallId":"toolu_01K73pQJ5DE4spwyXqGDTjpZ","toolName":"read","content":[{"type":"text","text":"\"\"\"Pydantic schemas for the Chrysopedia API.\n\nRead-only schemas for list/detail endpoints and input schemas for creation.\nEach schema mirrors the corresponding SQLAlchemy model in models.py.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport uuid\nfrom datetime import datetime\nfrom typing import Literal\n\nfrom pydantic import BaseModel, ConfigDict, Field\n\n\n# ── Health ───────────────────────────────────────────────────────────────────\n\nclass HealthResponse(BaseModel):\n    status: str = \"ok\"\n    service: str = \"chrysopedia-api\"\n    version: str = \"0.1.0\"\n    database: str = \"unknown\"\n\n\n# ── Creator ──────────────────────────────────────────────────────────────────\n\nclass CreatorBase(BaseModel):\n    name: str\n    slug: str\n    genres: list[str] | None = None\n    folder_name: str\n\nclass CreatorCreate(CreatorBase):\n    pass\n\nclass CreatorRead(CreatorBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    view_count: int = 0\n    created_at: datetime\n    updated_at: datetime\n\n\nclass CreatorDetail(CreatorRead):\n    \"\"\"Creator with nested video count.\"\"\"\n    video_count: int = 0\n\n\n# ── SourceVideo ──────────────────────────────────────────────────────────────\n\nclass SourceVideoBase(BaseModel):\n    filename: str\n    file_path: str\n    duration_seconds: int | None = None\n    content_type: str\n    transcript_path: str | None = None\n\nclass SourceVideoCreate(SourceVideoBase):\n    creator_id: uuid.UUID\n\nclass SourceVideoRead(SourceVideoBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    creator_id: uuid.UUID\n    content_hash: str | None = None\n    processing_status: str = \"not_started\"\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── TranscriptSegment ────────────────────────────────────────────────────────\n\nclass TranscriptSegmentBase(BaseModel):\n    start_time: float\n    end_time: float\n    text: str\n    segment_index: int\n    topic_label: str | None = None\n\nclass TranscriptSegmentCreate(TranscriptSegmentBase):\n    source_video_id: uuid.UUID\n\nclass TranscriptSegmentRead(TranscriptSegmentBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    source_video_id: uuid.UUID\n\n\n# ── KeyMoment ────────────────────────────────────────────────────────────────\n\nclass KeyMomentBase(BaseModel):\n    title: str\n    summary: str\n    start_time: float\n    end_time: float\n    content_type: str\n    plugins: list[str] | None = None\n    raw_transcript: str | None = None\n\nclass KeyMomentCreate(KeyMomentBase):\n    source_video_id: uuid.UUID\n    technique_page_id: uuid.UUID | None = None\n\nclass KeyMomentRead(KeyMomentBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    source_video_id: uuid.UUID\n    technique_page_id: uuid.UUID | None = None\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── TechniquePage ────────────────────────────────────────────────────────────\n\nclass TechniquePageBase(BaseModel):\n    title: str\n    slug: str\n    topic_category: str\n    topic_tags: list[str] | None = None\n    summary: str | None = None\n    body_sections: dict | None = None\n    signal_chains: list | None = None\n    plugins: list[str] | None = None\n\nclass TechniquePageCreate(TechniquePageBase):\n    creator_id: uuid.UUID\n    source_quality: str | None = None\n\nclass TechniquePageRead(TechniquePageBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    creator_id: uuid.UUID\n    creator_name: str = \"\"\n    creator_slug: str = \"\"\n    source_quality: str | None = None\n    view_count: int = 0\n    key_moment_count: int = 0\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── RelatedTechniqueLink ─────────────────────────────────────────────────────\n\nclass RelatedTechniqueLinkBase(BaseModel):\n    source_page_id: uuid.UUID\n    target_page_id: uuid.UUID\n    relationship: str\n\nclass RelatedTechniqueLinkCreate(RelatedTechniqueLinkBase):\n    pass\n\nclass RelatedTechniqueLinkRead(RelatedTechniqueLinkBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n\n\n# ── Tag ──────────────────────────────────────────────────────────────────────\n\nclass TagBase(BaseModel):\n    name: str\n    category: str\n    aliases: list[str] | None = None\n\nclass TagCreate(TagBase):\n    pass\n\nclass TagRead(TagBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n\n\n# ── Transcript Ingestion ─────────────────────────────────────────────────────\n\nclass TranscriptIngestResponse(BaseModel):\n    \"\"\"Response returned after successfully ingesting a transcript.\"\"\"\n    video_id: uuid.UUID\n    creator_id: uuid.UUID\n    creator_name: str\n    filename: str\n    segments_stored: int\n    processing_status: str\n    is_reupload: bool\n    content_hash: str\n\n\n# ── Pagination wrapper ───────────────────────────────────────────────────────\n\nclass PaginatedResponse(BaseModel):\n    \"\"\"Generic paginated list response.\"\"\"\n    items: list = Field(default_factory=list)\n    total: int = 0\n    offset: int = 0\n    limit: int = 50\n\n\n# ── Search ───────────────────────────────────────────────────────────────────\n\nclass SearchResultItem(BaseModel):\n    \"\"\"A single search result.\"\"\"\n    title: str\n    slug: str = \"\"\n    technique_page_slug: str = \"\"\n    type: str = \"\"\n    score: float = 0.0\n    summary: str = \"\"\n    creator_name: str = \"\"\n    creator_slug: str = \"\"\n    topic_category: str = \"\"\n    topic_tags: list[str] = Field(default_factory=list)\n    match_context: str = \"\"\n\n\nclass SearchResponse(BaseModel):\n    \"\"\"Top-level search response with metadata.\"\"\"\n    items: list[SearchResultItem] = Field(default_factory=list)\n    partial_matches: list[SearchResultItem] = Field(default_factory=list)\n    total: int = 0\n    query: str = \"\"\n    fallback_used: bool = False\n\n\nclass SuggestionItem(BaseModel):\n    \"\"\"A single autocomplete suggestion.\"\"\"\n    text: str\n    type: Literal[\"topic\", \"technique\", \"creator\"]\n\n\nclass SuggestionsResponse(BaseModel):\n    \"\"\"Popular search suggestions for autocomplete.\"\"\"\n    suggestions: list[SuggestionItem] = Field(default_factory=list)\n\n\n# ── Technique Page Detail ────────────────────────────────────────────────────\n\nclass KeyMomentSummary(BaseModel):\n    \"\"\"Lightweight key moment for technique page detail.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    title: str\n    summary: str\n    start_time: float\n    end_time: float\n    content_type: str\n    plugins: list[str] | None = None\n    source_video_id: uuid.UUID | None = None\n    video_filename: str = \"\"\n\n\nclass RelatedLinkItem(BaseModel):\n    \"\"\"A related technique link with target info.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    target_title: str = \"\"\n    target_slug: str = \"\"\n    relationship: str = \"\"\n    creator_name: str = \"\"\n    topic_category: str = \"\"\n    reason: str = \"\"\n\n\nclass CreatorInfo(BaseModel):\n    \"\"\"Minimal creator info embedded in technique detail.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    name: str\n    slug: str\n    genres: list[str] | None = None\n\n\nclass TechniquePageDetail(TechniquePageRead):\n    \"\"\"Technique page with nested key moments, creator, and related links.\"\"\"\n    key_moments: list[KeyMomentSummary] = Field(default_factory=list)\n    creator_info: CreatorInfo | None = None\n    related_links: list[RelatedLinkItem] = Field(default_factory=list)\n    version_count: int = 0\n\n\n# ── Technique Page Versions ──────────────────────────────────────────────────\n\nclass TechniquePageVersionSummary(BaseModel):\n    \"\"\"Lightweight version entry for list responses.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    version_number: int\n    created_at: datetime\n    pipeline_metadata: dict | None = None\n\n\nclass TechniquePageVersionDetail(BaseModel):\n    \"\"\"Full version snapshot for detail responses.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    version_number: int\n    content_snapshot: dict\n    pipeline_metadata: dict | None = None\n    created_at: datetime\n\n\nclass TechniquePageVersionListResponse(BaseModel):\n    \"\"\"Response for version list endpoint.\"\"\"\n    items: list[TechniquePageVersionSummary] = Field(default_factory=list)\n    total: int = 0\n\n\n# ── Topics ───────────────────────────────────────────────────────────────────\n\nclass TopicSubTopic(BaseModel):\n    \"\"\"A sub-topic with aggregated counts.\"\"\"\n    name: str\n    technique_count: int = 0\n    creator_count: int = 0\n\n\nclass TopicCategory(BaseModel):\n    \"\"\"A top-level topic category with sub-topics.\"\"\"\n    name: str\n    description: str = \"\"\n    sub_topics: list[TopicSubTopic] = Field(default_factory=list)\n\n\n# ── Creator Browse ───────────────────────────────────────────────────────────\n\nclass CreatorBrowseItem(CreatorRead):\n    \"\"\"Creator with technique and video counts for browse pages.\"\"\"\n    technique_count: int = 0\n    video_count: int = 0\n\n\n# ── Content Reports ──────────────────────────────────────────────────────────\n\nclass ContentReportCreate(BaseModel):\n    \"\"\"Public submission: report a content issue.\"\"\"\n    content_type: str = Field(\n        ..., description=\"Entity type: technique_page, key_moment, creator, general\"\n    )\n    content_id: uuid.UUID | None = Field(\n        None, description=\"ID of the reported entity (null for general reports)\"\n    )\n    content_title: str | None = Field(\n        None, description=\"Title of the reported content (for display context)\"\n    )\n    report_type: str = Field(\n        ..., description=\"inaccurate, missing_info, wrong_attribution, formatting, other\"\n    )\n    description: str = Field(\n        ..., min_length=10, max_length=2000,\n        description=\"Description of the issue\"\n    )\n    page_url: str | None = Field(\n        None, description=\"URL the user was on when reporting\"\n    )\n\n\nclass ContentReportRead(BaseModel):\n    \"\"\"Full report for admin views.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    content_type: str\n    content_id: uuid.UUID | None = None\n    content_title: str | None = None\n    report_type: str\n    description: str\n    status: str = \"open\"\n    admin_notes: str | None = None\n    page_url: str | None = None\n    created_at: datetime\n    resolved_at: datetime | None = None\n\n\nclass ContentReportUpdate(BaseModel):\n    \"\"\"Admin update: change status and/or add notes.\"\"\"\n    status: str | None = Field(\n        None, description=\"open, acknowledged, resolved, dismissed\"\n    )\n    admin_notes: str | None = Field(\n        None, max_length=2000, description=\"Admin notes about resolution\"\n    )\n\n\nclass ContentReportListResponse(BaseModel):\n    \"\"\"Paginated list of content reports.\"\"\"\n    items: list[ContentReportRead] = Field(default_factory=list)\n    total: int = 0\n    offset: int = 0\n    limit: int = 50\n\n\n# ── Pipeline Debug Mode ─────────────────────────────────────────────────────\n\nclass DebugModeResponse(BaseModel):\n    \"\"\"Current debug mode status.\"\"\"\n    debug_mode: bool\n\n\nclass DebugModeUpdate(BaseModel):\n    \"\"\"Toggle debug mode on/off.\"\"\"\n    debug_mode: bool\n\n\nclass TokenStageSummary(BaseModel):\n    \"\"\"Per-stage token usage aggregation.\"\"\"\n    stage: str\n    call_count: int\n    total_prompt_tokens: int\n    total_completion_tokens: int\n    total_tokens: int\n\n\nclass TokenSummaryResponse(BaseModel):\n    \"\"\"Token usage summary for a video, broken down by stage.\"\"\"\n    video_id: str\n    stages: list[TokenStageSummary] = Field(default_factory=list)\n    grand_total_tokens: int\n"}],"isError":false,"timestamp":1775178885041}}
{"type":"message","id":"0e5ea41c","parentId":"5be98b30","timestamp":"2026-04-03T01:14:45.045Z","message":{"role":"toolResult","toolCallId":"toolu_015mtmdiTZZikjz4LinExBZn","toolName":"bash","content":[{"type":"text","text":"001_initial.py\n002_technique_page_versions.py\n003_content_reports.py\n004_pipeline_events.py\n005_content_hash.py\n006_debug_columns.py\n007_drop_review_columns.py\n008_rename_processing_status.py\n009_add_creator_hidden_flag.py\n010_add_pipeline_runs.py\n011_classification_cache_and_stage_rerun.py\n"}],"isError":false,"timestamp":1775178885041}}
{"type":"message","id":"b40da2c1","parentId":"0e5ea41c","timestamp":"2026-04-03T01:14:52.227Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Good, I have the full picture. Let me check the last migration for the revision chain.","thinkingSignature":"EpECClkIDBgCKkD7NU0slGR7sSl7XUm9wdAjmO8VLAcKGXm2Xz2eaco6mtHm2oEEICioD/bPJYbkkwaq/DbfxUuHhKEPv5XTLQJoMg9jbGF1ZGUtb3B1cy00LTY4ABIMeNS+qd/fU3TE6h9KGgxcuO3nNkuD6K3vRQgiMJHllVJQe/fmmpx15QHt09WmUBS6U1Ag+IxjGdP4735SOBVsxDguhg6FbcOm3zknFypmLIjc9cyWtifKNNzXuXMdQTBETshZq5/vw3K19zOO2YwU/k97SGm/HCVPTQn3tG6qJn3KkkrN0sNH+PSdyfsJVITkzgA0p+ii+7TEOkvyc45/2pK31vT377KsOxN4JW8/KWqemXTXGAE="},{"type":"text","text":"Let me check the last migration's revision ID to chain correctly."},{"type":"toolCall","id":"toolu_01MU8YHeu5PzUpnL78MNw2ZZ","name":"bash","arguments":{"command":"head -20 alembic/versions/011_classification_cache_and_stage_rerun.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":123,"cacheRead":63947,"cacheWrite":9183,"totalTokens":73254,"cost":{"input":0.000005,"output":0.003075,"cacheRead":0.0319735,"cacheWrite":0.05739375,"total":0.09244725000000001}},"stopReason":"toolUse","timestamp":1775178885043}}
{"type":"message","id":"728c99f0","parentId":"b40da2c1","timestamp":"2026-04-03T01:14:52.240Z","message":{"role":"toolResult","toolCallId":"toolu_01MU8YHeu5PzUpnL78MNw2ZZ","toolName":"bash","content":[{"type":"text","text":"\"\"\"Add classification_data JSONB column to source_videos and stage_rerun trigger.\n\nPersists stage 4 classification data in PostgreSQL alongside Redis cache,\neliminating the 24-hour TTL data loss risk. Also adds the 'stage_rerun'\ntrigger value for single-stage re-run support.\n\nRevision ID: 011_cls_cache_rerun\nRevises: 010_add_pipeline_runs\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\nfrom sqlalchemy.dialects.postgresql import JSONB\n\nrevision = \"011_cls_cache_rerun\"\ndown_revision = \"010_add_pipeline_runs\"\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade() -> None:\n"}],"isError":false,"timestamp":1775178892238}}
{"type":"message","id":"489ca9dc","parentId":"728c99f0","timestamp":"2026-04-03T01:15:04.368Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have everything I need. Let me create the three files.","thinkingSignature":"EvcBClkIDBgCKkCKCpxOWMJWbaGI02hu6WeImlsv3+ZOCA4h9uCkb5LQpRDaqub4jdzuBa8nvQ2CXI9cCfS7ISrduiyIJQ2xcj9qMg9jbGF1ZGUtb3B1cy00LTY4ABIM4wCuIB+lJe/WgVd5Ggxl2nAwIclJvcqm5kwiMI0GgQQKKjOV7+UE/CAFSsCu6vOB2LTaS712t6kUN4fqhI/Ybq0BLj3puXzhQzto+ypMObkcowz/mEiocgkb9upLqTchCZjFAecW7ULfhWFxw6vwQDfRsh0bbB/DHLjoDMEejSjNYo3Fbh1r+K5bzgNS+Y37sVuplLGzrBGqaRgB"},{"type":"text","text":"Good — revision chain is clear. Now I'll create the migration, update models, and update schemas.\n\n**Step 1: Create the Alembic migration.**"},{"type":"toolCall","id":"toolu_01Ly8LhzgrftV781YNzL6e7U","name":"write","arguments":{"content":"\"\"\"Add body_sections_format column and technique_page_videos association table.\n\nSupports multi-source technique pages: tracks which source videos contributed\nto a technique page, and marks the body_sections format version for future\nstructured section layouts.\n\nRevision ID: 012_multi_source_fmt\nRevises: 011_cls_cache_rerun\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\nfrom sqlalchemy.dialects.postgresql import UUID\n\nrevision = \"012_multi_source_fmt\"\ndown_revision = \"011_cls_cache_rerun\"\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade() -> None:\n    # Add body_sections_format to technique_pages with default for existing rows\n    op.add_column(\n        \"technique_pages\",\n        sa.Column(\n            \"body_sections_format\",\n            sa.String(20),\n            nullable=False,\n            server_default=\"v1\",\n        ),\n    )\n\n    # Create technique_page_videos association table\n    op.create_table(\n        \"technique_page_videos\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.func.gen_random_uuid()),\n        sa.Column(\n            \"technique_page_id\",\n            UUID(as_uuid=True),\n            sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"),\n            nullable=False,\n        ),\n        sa.Column(\n            \"source_video_id\",\n            UUID(as_uuid=True),\n            sa.ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"),\n            nullable=False,\n        ),\n        sa.Column(\"added_at\", sa.TIMESTAMP(), server_default=sa.func.now(), nullable=False),\n        sa.UniqueConstraint(\"technique_page_id\", \"source_video_id\", name=\"uq_page_video\"),\n    )\n\n\ndef downgrade() -> None:\n    op.drop_table(\"technique_page_videos\")\n    op.drop_column(\"technique_pages\", \"body_sections_format\")\n","path":"alembic/versions/012_multi_source_format.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":651,"cacheRead":73130,"cacheWrite":276,"totalTokens":74058,"cost":{"input":0.000005,"output":0.016275,"cacheRead":0.036565,"cacheWrite":0.0017250000000000002,"total":0.05457}},"stopReason":"toolUse","timestamp":1775178892239}}
{"type":"message","id":"f9291369","parentId":"489ca9dc","timestamp":"2026-04-03T01:15:04.372Z","message":{"role":"toolResult","toolCallId":"toolu_01Ly8LhzgrftV781YNzL6e7U","toolName":"write","content":[{"type":"text","text":"Successfully wrote 1764 bytes to alembic/versions/012_multi_source_format.py"}],"isError":false,"timestamp":1775178904370}}
{"type":"message","id":"c4233553","parentId":"f9291369","timestamp":"2026-04-03T01:15:10.305Z","message":{"role":"assistant","content":[{"type":"text","text":"**Step 2: Update models.py** — add `body_sections_format` to `TechniquePage` and add the `TechniquePageVideo` model."},{"type":"toolCall","id":"toolu_01EMU2m5iUqq69BhoX2pDgEb","name":"edit","arguments":{"newText":"    body_sections: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n    body_sections_format: Mapped[str] = mapped_column(\n        String(20), nullable=False, default=\"v1\", server_default=\"v1\"\n    )\n    signal_chains: Mapped[list | None] = mapped_column(JSONB, nullable=True)","oldText":"    body_sections: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n    signal_chains: Mapped[list | None] = mapped_column(JSONB, nullable=True)","path":"backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":272,"cacheRead":73406,"cacheWrite":657,"totalTokens":74336,"cost":{"input":0.000005,"output":0.0068000000000000005,"cacheRead":0.036703,"cacheWrite":0.0041062500000000005,"total":0.04761425}},"stopReason":"toolUse","timestamp":1775178904371}}
{"type":"message","id":"14f5eb0f","parentId":"c4233553","timestamp":"2026-04-03T01:15:10.315Z","message":{"role":"toolResult","toolCallId":"toolu_01EMU2m5iUqq69BhoX2pDgEb","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/models.py."}],"details":{"diff":" 215     topic_category: Mapped[str] = mapped_column(String(255), nullable=False)\n 216     topic_tags: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n 217     summary: Mapped[str | None] = mapped_column(Text, nullable=True)\n 218     body_sections: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n+219     body_sections_format: Mapped[str] = mapped_column(\n+220         String(20), nullable=False, default=\"v1\", server_default=\"v1\"\n+221     )\n 222     signal_chains: Mapped[list | None] = mapped_column(JSONB, nullable=True)\n 223     plugins: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n 224     source_quality: Mapped[SourceQuality | None] = mapped_column(\n 225         Enum(SourceQuality, name=\"source_quality\", create_constraint=True),","firstChangedLine":219},"isError":false,"timestamp":1775178910313}}
{"type":"message","id":"c4bbc911","parentId":"14f5eb0f","timestamp":"2026-04-03T01:15:17.075Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add the `source_video_links` relationship on TechniquePage — I'll add it after the `incoming_links` relationship."},{"type":"toolCall","id":"toolu_0195UgGJJHjWFUPeM3yKyyF3","name":"edit","arguments":{"newText":"    incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.target_page_id\", back_populates=\"target_page\"\n    )\n    source_video_links: Mapped[list[TechniquePageVideo]] = sa_relationship(\n        back_populates=\"technique_page\"\n    )","oldText":"    incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.target_page_id\", back_populates=\"target_page\"\n    )","path":"backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":269,"cacheRead":74063,"cacheWrite":293,"totalTokens":74626,"cost":{"input":0.000005,"output":0.006725,"cacheRead":0.037031499999999995,"cacheWrite":0.0018312500000000002,"total":0.045592749999999994}},"stopReason":"toolUse","timestamp":1775178910314}}
{"type":"message","id":"503a921f","parentId":"c4bbc911","timestamp":"2026-04-03T01:15:17.083Z","message":{"role":"toolResult","toolCallId":"toolu_0195UgGJJHjWFUPeM3yKyyF3","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/models.py."}],"details":{"diff":" 246     )\n 247     incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n 248         foreign_keys=\"RelatedTechniqueLink.target_page_id\", back_populates=\"target_page\"\n 249     )\n+250     source_video_links: Mapped[list[TechniquePageVideo]] = sa_relationship(\n+251         back_populates=\"technique_page\"\n+252     )\n 253 \n 254 \n 255 class RelatedTechniqueLink(Base):\n 256     __tablename__ = \"related_technique_links\"","firstChangedLine":250},"isError":false,"timestamp":1775178917081}}
{"type":"message","id":"bf310543","parentId":"503a921f","timestamp":"2026-04-03T01:15:25.882Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add the `TechniquePageVideo` model class. I'll insert it after the `Tag` model (before the Content Report enums section)."},{"type":"toolCall","id":"toolu_01E6HqDCCPBTbHZPKCcf3BXy","name":"edit","arguments":{"newText":"class Tag(Base):\n    __tablename__ = \"tags\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    category: Mapped[str] = mapped_column(String(255), nullable=False)\n    aliases: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n\n\nclass TechniquePageVideo(Base):\n    \"\"\"Association linking a technique page to its contributing source videos.\"\"\"\n    __tablename__ = \"technique_page_videos\"\n    __table_args__ = (\n        UniqueConstraint(\"technique_page_id\", \"source_video_id\", name=\"uq_page_video\"),\n    )\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    technique_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    source_video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    added_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n\n    # relationships\n    technique_page: Mapped[TechniquePage] = sa_relationship(\n        back_populates=\"source_video_links\"\n    )\n    source_video: Mapped[SourceVideo] = sa_relationship()","oldText":"class Tag(Base):\n    __tablename__ = \"tags\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    category: Mapped[str] = mapped_column(String(255), nullable=False)\n    aliases: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)","path":"backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":614,"cacheRead":74356,"cacheWrite":290,"totalTokens":75261,"cost":{"input":0.000005,"output":0.01535,"cacheRead":0.037177999999999996,"cacheWrite":0.0018125,"total":0.0543455}},"stopReason":"toolUse","timestamp":1775178917082}}
{"type":"message","id":"722a8aea","parentId":"bf310543","timestamp":"2026-04-03T01:15:25.896Z","message":{"role":"toolResult","toolCallId":"toolu_01E6HqDCCPBTbHZPKCcf3BXy","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/models.py."}],"details":{"diff":" 308     category: Mapped[str] = mapped_column(String(255), nullable=False)\n 309     aliases: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n 310 \n 311 \n+312 class TechniquePageVideo(Base):\n+313     \"\"\"Association linking a technique page to its contributing source videos.\"\"\"\n+314     __tablename__ = \"technique_page_videos\"\n+315     __table_args__ = (\n+316         UniqueConstraint(\"technique_page_id\", \"source_video_id\", name=\"uq_page_video\"),\n+317     )\n+318 \n+319     id: Mapped[uuid.UUID] = _uuid_pk()\n+320     technique_page_id: Mapped[uuid.UUID] = mapped_column(\n+321         ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n+322     )\n+323     source_video_id: Mapped[uuid.UUID] = mapped_column(\n+324         ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n+325     )\n+326     added_at: Mapped[datetime] = mapped_column(\n+327         default=_now, server_default=func.now()\n+328     )\n+329 \n+330     # relationships\n+331     technique_page: Mapped[TechniquePage] = sa_relationship(\n+332         back_populates=\"source_video_links\"\n+333     )\n+334     source_video: Mapped[SourceVideo] = sa_relationship()\n+335 \n+336 \n 337 # ── Content Report Enums ─────────────────────────────────────────────────────\n 338 \n 339 class ReportType(str, enum.Enum):\n 340     \"\"\"Classification of user-submitted content reports.\"\"\"","firstChangedLine":312},"isError":false,"timestamp":1775178925894}}
{"type":"message","id":"afd4aab8","parentId":"722a8aea","timestamp":"2026-04-03T01:15:31.404Z","message":{"role":"assistant","content":[{"type":"text","text":"**Step 3: Update schemas.py** — widen `body_sections`, add `body_sections_format`, add `SourceVideoSummary`, add `source_videos` to detail."},{"type":"toolCall","id":"toolu_01NmhXmwaVVuTFXgyrF3GfnX","name":"edit","arguments":{"newText":"    body_sections: list | dict | None = None\n    body_sections_format: str = \"v1\"\n    signal_chains: list | None = None","oldText":"    body_sections: dict | None = None\n    signal_chains: list | None = None","path":"backend/schemas.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":192,"cacheRead":74646,"cacheWrite":635,"totalTokens":75474,"cost":{"input":0.000005,"output":0.0048000000000000004,"cacheRead":0.037322999999999995,"cacheWrite":0.00396875,"total":0.04609675}},"stopReason":"toolUse","timestamp":1775178925895}}
{"type":"message","id":"dcb3ea6e","parentId":"afd4aab8","timestamp":"2026-04-03T01:15:31.417Z","message":{"role":"toolResult","toolCallId":"toolu_01NmhXmwaVVuTFXgyrF3GfnX","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/schemas.py."}],"details":{"diff":" 121     slug: str\n 122     topic_category: str\n 123     topic_tags: list[str] | None = None\n 124     summary: str | None = None\n-125     body_sections: dict | None = None\n+125     body_sections: list | dict | None = None\n+126     body_sections_format: str = \"v1\"\n 127     signal_chains: list | None = None\n 128     plugins: list[str] | None = None\n 129 \n 130 class TechniquePageCreate(TechniquePageBase):","firstChangedLine":125},"isError":false,"timestamp":1775178931415}}
{"type":"message","id":"b8038faa","parentId":"dcb3ea6e","timestamp":"2026-04-03T01:15:38.872Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add `SourceVideoSummary` before `TechniquePageDetail`, and add `source_videos` to `TechniquePageDetail`."},{"type":"toolCall","id":"toolu_01T3PydJQZFiPGRGqRVTzZMo","name":"edit","arguments":{"newText":"class SourceVideoSummary(BaseModel):\n    \"\"\"Lightweight source video info for technique page detail.\"\"\"\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    filename: str\n    content_type: str\n    added_at: datetime | None = None\n\n\nclass TechniquePageDetail(TechniquePageRead):\n    \"\"\"Technique page with nested key moments, creator, and related links.\"\"\"\n    key_moments: list[KeyMomentSummary] = Field(default_factory=list)\n    creator_info: CreatorInfo | None = None\n    related_links: list[RelatedLinkItem] = Field(default_factory=list)\n    version_count: int = 0\n    source_videos: list[SourceVideoSummary] = Field(default_factory=list)","oldText":"class TechniquePageDetail(TechniquePageRead):\n    \"\"\"Technique page with nested key moments, creator, and related links.\"\"\"\n    key_moments: list[KeyMomentSummary] = Field(default_factory=list)\n    creator_info: CreatorInfo | None = None\n    related_links: list[RelatedLinkItem] = Field(default_factory=list)\n    version_count: int = 0","path":"backend/schemas.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":424,"cacheRead":75281,"cacheWrite":213,"totalTokens":75919,"cost":{"input":0.000005,"output":0.0106,"cacheRead":0.0376405,"cacheWrite":0.00133125,"total":0.049576749999999996}},"stopReason":"toolUse","timestamp":1775178931416}}
{"type":"message","id":"1a46af97","parentId":"b8038faa","timestamp":"2026-04-03T01:15:38.884Z","message":{"role":"toolResult","toolCallId":"toolu_01T3PydJQZFiPGRGqRVTzZMo","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/schemas.py."}],"details":{"diff":" 275     slug: str\n 276     genres: list[str] | None = None\n 277 \n 278 \n+279 class SourceVideoSummary(BaseModel):\n+280     \"\"\"Lightweight source video info for technique page detail.\"\"\"\n+281     model_config = ConfigDict(from_attributes=True)\n+282 \n+283     id: uuid.UUID\n+284     filename: str\n+285     content_type: str\n+286     added_at: datetime | None = None\n+287 \n+288 \n 289 class TechniquePageDetail(TechniquePageRead):\n 290     \"\"\"Technique page with nested key moments, creator, and related links.\"\"\"\n 291     key_moments: list[KeyMomentSummary] = Field(default_factory=list)\n 292     creator_info: CreatorInfo | None = None\n 293     related_links: list[RelatedLinkItem] = Field(default_factory=list)\n 294     version_count: int = 0\n+295     source_videos: list[SourceVideoSummary] = Field(default_factory=list)\n 296 \n 297 \n 298 # ── Technique Page Versions ──────────────────────────────────────────────────\n 299 ","firstChangedLine":279},"isError":false,"timestamp":1775178938882}}
{"type":"message","id":"e8e5b003","parentId":"1a46af97","timestamp":"2026-04-03T01:15:44.124Z","message":{"role":"assistant","content":[{"type":"text","text":"Now run verification checks."},{"type":"toolCall","id":"toolu_013V348iUx7C2KocGHdpW7xr","name":"bash","arguments":{"command":"cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\" && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":130,"cacheRead":75494,"cacheWrite":445,"totalTokens":76070,"cost":{"input":0.000005,"output":0.0032500000000000003,"cacheRead":0.037746999999999996,"cacheWrite":0.0027812500000000003,"total":0.043783249999999996}},"stopReason":"toolUse","timestamp":1775178938883}}
{"type":"message","id":"f846b22c","parentId":"e8e5b003","timestamp":"2026-04-03T01:15:44.656Z","message":{"role":"toolResult","toolCallId":"toolu_013V348iUx7C2KocGHdpW7xr","toolName":"bash","content":[{"type":"text","text":"models OK\nschemas OK\n"}],"isError":false,"timestamp":1775178944654}}
{"type":"message","id":"0834b5e6","parentId":"f846b22c","timestamp":"2026-04-03T01:15:49.447Z","message":{"role":"assistant","content":[{"type":"text","text":"Both model and schema imports pass. Let me also verify the migration file syntax is valid Python and check the `body_sections` type widening is correct."},{"type":"toolCall","id":"toolu_01Kg8ou4NB5C4QnUeKEzAG8X","name":"bash","arguments":{"command":"python -c \"import py_compile; py_compile.compile('alembic/versions/012_multi_source_format.py', doraise=True); print('migration syntax OK')\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":127,"cacheRead":75939,"cacheWrite":148,"totalTokens":76215,"cost":{"input":0.000005,"output":0.0031750000000000003,"cacheRead":0.037969499999999996,"cacheWrite":0.000925,"total":0.0420745}},"stopReason":"toolUse","timestamp":1775178944655}}
{"type":"message","id":"019a57e0","parentId":"0834b5e6","timestamp":"2026-04-03T01:15:49.488Z","message":{"role":"toolResult","toolCallId":"toolu_01Kg8ou4NB5C4QnUeKEzAG8X","toolName":"bash","content":[{"type":"text","text":"migration syntax OK\n"}],"isError":false,"timestamp":1775178949486}}
{"type":"message","id":"7d145a87","parentId":"019a57e0","timestamp":"2026-04-03T01:15:55.010Z","message":{"role":"assistant","content":[{"type":"text","text":"All three verification checks pass locally. The Docker-side `alembic upgrade head` is for T02 or deployment — it requires the running stack on ub01.\n\nNow read the task summary template and write the summary."},{"type":"toolCall","id":"toolu_01Ha7DBUir4iCkXY5xachkdd","name":"read","arguments":{"path":"/home/aux/.gsd/agent/extensions/gsd/templates/task-summary.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":121,"cacheRead":76087,"cacheWrite":143,"totalTokens":76352,"cost":{"input":0.000005,"output":0.0030250000000000003,"cacheRead":0.0380435,"cacheWrite":0.00089375,"total":0.04196725}},"stopReason":"toolUse","timestamp":1775178949486}}
{"type":"message","id":"9d87cdb4","parentId":"7d145a87","timestamp":"2026-04-03T01:15:55.015Z","message":{"role":"toolResult","toolCallId":"toolu_01Ha7DBUir4iCkXY5xachkdd","toolName":"read","content":[{"type":"text","text":"---\nid: {{taskId}}\nparent: {{sliceId}}\nmilestone: {{milestoneId}}\nprovides:\n  - {{whatThisTaskProvides}}\nkey_files:\n  - {{filePath}}\nkey_decisions:\n  - {{decision}}\npatterns_established:\n  - {{pattern}}\nobservability_surfaces:\n  - {{status endpoint, structured log, persisted failure state, diagnostic command, or none}}\nduration: {{duration}}\nverification_result: passed\ncompleted_at: {{date}}\n# Set blocker_discovered: true only if execution revealed the remaining slice plan\n# is fundamentally invalid (wrong API, missing capability, architectural mismatch).\n# Do NOT set true for ordinary bugs, minor deviations, or fixable issues.\nblocker_discovered: false\n---\n\n# {{taskId}}: {{taskTitle}}\n\n<!-- One-liner must say what actually shipped, not just that work completed.\n     Good: \"Added retry-aware worker status logging\"\n     Bad: \"Implemented logging improvements\" -->\n\n**{{oneLiner}}**\n\n## What Happened\n\n{{narrative}}\n\n## Verification\n\n{{whatWasVerifiedAndHow — commands run, tests passed, behavior confirmed}}\n\n## Verification Evidence\n\n<!-- Populated from verification gate output. If the gate ran, fill in the table below.\n     If no gate ran (e.g., no verification commands discovered), note that. -->\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| {{row}} | {{command}} | {{exitCode}} | {{verdict}} | {{duration}} |\n\n## Diagnostics\n\n{{howToInspectWhatThisTaskBuiltLater — status surfaces, logs, error shapes, failure artifacts, or none}}\n\n## Deviations\n\n<!-- Deviations are unplanned changes to the written task plan, not ordinary debugging during implementation. -->\n\n{{deviationsFromPlan_OR_none}}\n\n## Known Issues\n\n{{issuesDiscoveredButNotFixed_OR_none}}\n\n## Files Created/Modified\n\n- `{{filePath}}` — {{description}}\n- `{{filePath}}` — {{description}}\n"}],"isError":false,"timestamp":1775178955012}}
{"type":"message","id":"91cd8dab","parentId":"9d87cdb4","timestamp":"2026-04-03T01:16:17.755Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01PTm54SgUu5WhGw3NnASaNN","name":"write","arguments":{"content":"---\nid: T01\nparent: S03\nmilestone: M014\nprovides:\n  - TechniquePageVideo model with CASCADE FKs and unique constraint\n  - body_sections_format column on TechniquePage (default 'v1')\n  - SourceVideoSummary Pydantic schema\n  - Widened body_sections type (list | dict | None)\n  - source_videos field on TechniquePageDetail\nkey_files:\n  - alembic/versions/012_multi_source_format.py\n  - backend/models.py\n  - backend/schemas.py\nkey_decisions:\n  - Used TIMESTAMP (not TIMESTAMP WITH TIME ZONE) for added_at on technique_page_videos to stay consistent with all other timestamp columns in the schema\npatterns_established:\n  - Association table pattern with dual CASCADE FKs and named unique constraint (uq_page_video)\nobservability_surfaces:\n  - none\nduration: 10m\nverification_result: passed\ncompleted_at: 2026-04-03\nblocker_discovered: false\n---\n\n# T01: Alembic migration + SQLAlchemy model + Pydantic schema updates\n\n**Added body_sections_format column, technique_page_videos association table, and SourceVideoSummary schema for multi-source technique pages**\n\n## What Happened\n\nCreated the data layer foundation for multi-source technique pages:\n\n1. **Migration** (`012_multi_source_format.py`): Adds `body_sections_format` VARCHAR(20) NOT NULL DEFAULT 'v1' to `technique_pages`, and creates the `technique_page_videos` association table with UUID PK, dual CASCADE foreign keys, timestamp, and a unique constraint on (technique_page_id, source_video_id). Both upgrade and downgrade paths implemented.\n\n2. **Models** (`models.py`): Added `body_sections_format` mapped column to `TechniquePage` with default/server_default of 'v1'. Added `TechniquePageVideo` model with relationships back to both `TechniquePage` (via `source_video_links`) and `SourceVideo`. Used `sa_relationship` alias per KNOWLEDGE.md convention.\n\n3. **Schemas** (`schemas.py`): Widened `TechniquePageBase.body_sections` from `dict | None` to `list | dict | None`. Added `body_sections_format: str = \"v1\"` to `TechniquePageBase`. Created `SourceVideoSummary` schema with `from_attributes=True`. Added `source_videos: list[SourceVideoSummary]` to `TechniquePageDetail`.\n\n## Verification\n\n- `cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\"` — passed\n- `cd backend && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\"` — passed\n- Migration file compiles cleanly (`py_compile`)\n- `alembic upgrade head` deferred to Docker execution (T02 or deployment on ub01)\n\n## Verification Evidence\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| 1 | `cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\"` | 0 | ✅ pass | <1s |\n| 2 | `cd backend && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\"` | 0 | ✅ pass | <1s |\n| 3 | `python -c \"import py_compile; py_compile.compile('alembic/versions/012_multi_source_format.py', doraise=True)\"` | 0 | ✅ pass | <1s |\n\n## Diagnostics\n\nNo runtime surfaces — this is a data layer change. Verify migration on ub01 via `docker exec chrysopedia-api alembic upgrade head`. Check column exists: `docker exec chrysopedia-db psql -U chrysopedia -c \"\\d technique_pages\"`.\n\n## Deviations\n\nNone.\n\n## Known Issues\n\nNone.\n\n## Files Created/Modified\n\n- `alembic/versions/012_multi_source_format.py` — new migration adding body_sections_format column and technique_page_videos table\n- `backend/models.py` — added TechniquePageVideo model, body_sections_format column on TechniquePage, source_video_links relationship\n- `backend/schemas.py` — widened body_sections type, added body_sections_format field, SourceVideoSummary schema, source_videos on TechniquePageDetail\n","path":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/tasks/T01-SUMMARY.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":1277,"cacheRead":76230,"cacheWrite":631,"totalTokens":78139,"cost":{"input":0.000005,"output":0.031925,"cacheRead":0.038114999999999996,"cacheWrite":0.00394375,"total":0.07398874999999999}},"stopReason":"toolUse","timestamp":1775178955013}}
{"type":"message","id":"260f3415","parentId":"91cd8dab","timestamp":"2026-04-03T01:16:17.759Z","message":{"role":"toolResult","toolCallId":"toolu_01PTm54SgUu5WhGw3NnASaNN","toolName":"write","content":[{"type":"text","text":"Successfully wrote 3888 bytes to /home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/tasks/T01-SUMMARY.md"}],"isError":false,"timestamp":1775178977757}}
{"type":"message","id":"d3079db3","parentId":"260f3415","timestamp":"2026-04-03T01:16:27.991Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_017fUX6y1dy1Tv5sUU9mg6dn","name":"gsd_task_complete","arguments":{"blockerDiscovered":false,"deviations":"None.","keyDecisions":["Used TIMESTAMP (not WITH TIME ZONE) for added_at to stay consistent with existing schema convention"],"keyFiles":["alembic/versions/012_multi_source_format.py","backend/models.py","backend/schemas.py"],"knownIssues":"None.","milestoneId":"M014","narrative":"Created Alembic migration 012 with body_sections_format VARCHAR(20) NOT NULL DEFAULT 'v1' on technique_pages and technique_page_videos association table with dual CASCADE FKs and unique constraint. Updated SQLAlchemy models with TechniquePageVideo class and body_sections_format column. Widened Pydantic body_sections type to list | dict | None, added SourceVideoSummary schema, and added source_videos field to TechniquePageDetail.","oneLiner":"Added body_sections_format column, technique_page_videos association table, and SourceVideoSummary schema for multi-source technique pages","sliceId":"S03","taskId":"T01","verification":"Model imports pass with attribute assertions. Schema imports pass. Migration file compiles cleanly. Alembic upgrade head deferred to Docker execution on ub01.","verificationEvidence":[{"command":"cd backend && python -c \"from models import TechniquePageVideo, TechniquePage; assert hasattr(TechniquePage, 'body_sections_format'); print('models OK')\"","durationMs":500,"exitCode":0,"verdict":"✅ pass"},{"command":"cd backend && python -c \"from schemas import SourceVideoSummary, TechniquePageDetail; print('schemas OK')\"","durationMs":400,"exitCode":0,"verdict":"✅ pass"},{"command":"python -c \"import py_compile; py_compile.compile('alembic/versions/012_multi_source_format.py', doraise=True)\"","durationMs":200,"exitCode":0,"verdict":"✅ pass"}]}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":692,"cacheRead":76861,"cacheWrite":1338,"totalTokens":78892,"cost":{"input":0.000005,"output":0.0173,"cacheRead":0.0384305,"cacheWrite":0.0083625,"total":0.064098}},"stopReason":"toolUse","timestamp":1775178977758}}
{"type":"message","id":"6183af50","parentId":"d3079db3","timestamp":"2026-04-03T01:16:28.040Z","message":{"role":"toolResult","toolCallId":"toolu_017fUX6y1dy1Tv5sUU9mg6dn","toolName":"gsd_task_complete","content":[{"type":"text","text":"Completed task T01 (S03/M014)"}],"details":{"operation":"complete_task","taskId":"T01","sliceId":"S03","milestoneId":"M014","summaryPath":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S03/tasks/T01-SUMMARY.md"},"isError":false,"timestamp":1775178988039}}
{"type":"message","id":"3c765a59","parentId":"6183af50","timestamp":"2026-04-03T01:16:30.754Z","message":{"role":"assistant","content":[{"type":"text","text":"Task T01 complete."}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":9,"cacheRead":78199,"cacheWrite":721,"totalTokens":78930,"cost":{"input":0.000005,"output":0.00022500000000000002,"cacheRead":0.039099499999999995,"cacheWrite":0.00450625,"total":0.04383574999999999}},"stopReason":"stop","timestamp":1775178988039}}
