{"type":"thinking_level_change","id":"2ec2d4bb","parentId":null,"timestamp":"2026-03-30T07:04:39.912Z","thinkingLevel":"off"}
{"type":"model_change","id":"8346608b","parentId":"2ec2d4bb","timestamp":"2026-03-30T07:04:39.914Z","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/M004/slices/S04/S04-PLAN.md`\n- Task plan source: `.gsd/milestones/M004/slices/S04/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/M004/slices/S04/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/M004/slices/S04/tasks/T01-SUMMARY.md` before finishing.**\n\nWhen done, say: \"Task T01 complete.\"\n## Slice Plan Excerpt\nSource: `.gsd/milestones/M004/slices/S04/S04-PLAN.md`\n**Goal:** Technique pages track version history with pipeline metadata; re-running stage 5 snapshots the previous content before overwriting; API returns version list and version detail; frontend shows version count.\n**Demo:** After this: Technique pages track version history with pipeline metadata; API returns version list\n\n### Slice Verification\n- `cd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\"` exits 0\n- Alembic migration file exists and follows 001_initial.py pattern\n- `grep -q '_capture_pipeline_metadata' backend/pipeline/stages.py` confirms helper exists\n- `grep -q 'TechniquePageVersion' backend/pipeline/stages.py` confirms snapshot hook is wired\n\n## UNIT: Execute Task T01 (\"Add TechniquePageVersion model, migration, and stage 5 snapshot hook\") — Slice S04 (\"Article Versioning + Pipeline Tuning Metadata\"), Milestone M004\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/M004/slices/S04/tasks/T01-PLAN.md`\n\n---\nestimated_steps: 29\nestimated_files: 3\nskills_used: []\n---\n\n# T01: Add TechniquePageVersion model, migration, and stage 5 snapshot hook\n\nCreate the TechniquePageVersion SQLAlchemy model, Alembic migration, and the snapshot-on-write hook in stage 5 synthesis that captures existing page content + pipeline metadata before overwriting.\n\n## Failure Modes\n\n| Dependency | On error | On timeout | On malformed response |\n|------------|----------|-----------|----------------------|\n| PostgreSQL (migration) | Alembic raises — migration fails cleanly | N/A (local) | N/A |\n| Stage 5 sync session | Snapshot INSERT fails → log ERROR, continue with page update (best-effort versioning) | N/A (local DB) | N/A |\n| Prompt file hashing | FileNotFoundError → log WARNING, store empty hash in metadata | N/A | N/A |\n\n## Steps\n\n1. Add `TechniquePageVersion` model to `backend/models.py`: id (UUID PK), technique_page_id (FK to technique_pages.id, CASCADE), version_number (Integer, not null), content_snapshot (JSONB, not null), pipeline_metadata (JSONB, nullable), created_at (datetime). Add `sa_relationship` back to TechniquePage (versions list).\n\n2. Create Alembic migration `alembic/versions/002_technique_page_versions.py` following the exact pattern of `001_initial.py` (revision ID format, imports, upgrade/downgrade). The migration creates the `technique_page_versions` table with all columns and a composite index on `(technique_page_id, version_number)`.\n\n3. Add `_capture_pipeline_metadata()` helper function in `backend/pipeline/stages.py` that returns a dict with: model names (from settings), prompt file SHA-256 hashes (read each .txt file in prompts_path and hash), stage config (modalities). Use `hashlib.sha256` on file contents. Handle missing files gracefully (log warning, store empty hash).\n\n4. In `stage5_synthesis`, inside the `if existing:` block, BEFORE any attribute assignment on `existing`, capture the snapshot: read existing page's content fields (title, slug, topic_category, topic_tags, summary, body_sections, signal_chains, plugins, source_quality) into a dict. Compute `version_number = session.execute(select(func.count()).where(TechniquePageVersion.technique_page_id == existing.id)).scalar() + 1`. Create a `TechniquePageVersion` row with content_snapshot=snapshot_dict, pipeline_metadata=_capture_pipeline_metadata(), and add it to the session. Log at INFO level.\n\n5. Verify: run `alembic upgrade head` against test DB. Write a minimal manual test or rely on T02's integration tests.\n\n## Must-Haves\n\n- [ ] TechniquePageVersion model with correct columns and FK\n- [ ] Alembic migration creates technique_page_versions table\n- [ ] _capture_pipeline_metadata() hashes all prompt files and reads model config\n- [ ] Stage 5 snapshots BEFORE mutating existing page attributes\n- [ ] Version number is auto-incremented per technique_page_id\n- [ ] Snapshot contains all content fields (title, summary, body_sections, signal_chains, topic_tags, plugins, source_quality, topic_category)\n\n## Verification\n\n- `cd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\"` exits 0\n- Alembic migration file exists and follows 001_initial.py pattern\n- `grep -q '_capture_pipeline_metadata' backend/pipeline/stages.py` confirms helper exists\n- `grep -q 'TechniquePageVersion' backend/pipeline/stages.py` confirms snapshot hook is wired\n\n## Observability Impact\n\n- Signals added: INFO log in stage 5 when version snapshot is created (includes version_number, page slug)\n- How a future agent inspects this: `SELECT * FROM technique_page_versions ORDER BY created_at DESC LIMIT 5`\n- Failure state exposed: ERROR log if snapshot INSERT fails (with exception details)\n\n## Inputs\n\n- ``backend/models.py` — existing TechniquePage model to add relationship and reference for snapshot fields`\n- ``backend/pipeline/stages.py` — existing stage5_synthesis function (lines 480-618) with the `if existing:` upsert block where snapshot must be inserted BEFORE attribute mutation`\n- ``alembic/versions/001_initial.py` — reference migration pattern (revision ID format, imports, upgrade/downgrade structure)`\n- ``backend/config.py` — Settings class with model names, prompts_path, modality settings needed by _capture_pipeline_metadata()`\n\n## Expected Output\n\n- ``backend/models.py` — TechniquePageVersion model added with UUID PK, FK, version_number, content_snapshot JSONB, pipeline_metadata JSONB, created_at; relationship added to TechniquePage`\n- ``alembic/versions/002_technique_page_versions.py` — new Alembic migration creating technique_page_versions table with composite index`\n- ``backend/pipeline/stages.py` — _capture_pipeline_metadata() helper added; stage5_synthesis modified to snapshot existing page before overwrite`\n\n## Verification\n\ncd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\" && test -f ../alembic/versions/002_technique_page_versions.py && grep -q '_capture_pipeline_metadata' pipeline/stages.py && grep -q 'TechniquePageVersion' pipeline/stages.py\n","display":false,"id":"89284ba3","parentId":"8346608b","timestamp":"2026-03-30T07:04:39.917Z"}
{"type":"message","id":"889bf74d","parentId":"89284ba3","timestamp":"2026-03-30T07:04:44.394Z","message":{"role":"assistant","content":[{"type":"text","text":"\n\nI'll start by reading the existing files referenced in the task plan to understand the current codebase before making changes."},{"type":"toolCall","id":"toolu_01Du2sZoyPe2KXB3xMjRDgxY","name":"read","arguments":{"path":"backend/models.py"}},{"type":"toolCall","id":"toolu_01FAk8PVqsT6gBau9VB4NYrY","name":"read","arguments":{"path":"alembic/versions/001_initial.py"}},{"type":"toolCall","id":"toolu_016U3AYbpqauaJFkrLf1KxSk","name":"read","arguments":{"path":"backend/config.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":2,"output":163,"cacheRead":56783,"cacheWrite":4130,"totalTokens":61078,"cost":{"input":0.00001,"output":0.0040750000000000005,"cacheRead":0.0283915,"cacheWrite":0.025812500000000002,"total":0.058289}},"stopReason":"toolUse","timestamp":1774854279916}}
{"type":"message","id":"9d06fe41","parentId":"889bf74d","timestamp":"2026-03-30T07:04:44.398Z","message":{"role":"toolResult","toolCallId":"toolu_01Du2sZoyPe2KXB3xMjRDgxY","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    pending = \"pending\"\n    transcribed = \"transcribed\"\n    extracted = \"extracted\"\n    reviewed = \"reviewed\"\n    published = \"published\"\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 ReviewStatus(str, enum.Enum):\n    \"\"\"Human review status for key moments.\"\"\"\n    pending = \"pending\"\n    approved = \"approved\"\n    edited = \"edited\"\n    rejected = \"rejected\"\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 PageReviewStatus(str, enum.Enum):\n    \"\"\"Review lifecycle for technique pages.\"\"\"\n    draft = \"draft\"\n    reviewed = \"reviewed\"\n    published = \"published\"\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    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    processing_status: Mapped[ProcessingStatus] = mapped_column(\n        Enum(ProcessingStatus, name=\"processing_status\", create_constraint=True),\n        default=ProcessingStatus.pending,\n        server_default=\"pending\",\n    )\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    review_status: Mapped[ReviewStatus] = mapped_column(\n        Enum(ReviewStatus, name=\"review_status\", create_constraint=True),\n        default=ReviewStatus.pending,\n        server_default=\"pending\",\n    )\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    review_status: Mapped[PageReviewStatus] = mapped_column(\n        Enum(PageReviewStatus, name=\"page_review_status\", create_constraint=True),\n        default=PageReviewStatus.draft,\n        server_default=\"draft\",\n    )\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    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 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"}],"isError":false,"timestamp":1774854284397}}
{"type":"message","id":"7a783499","parentId":"9d06fe41","timestamp":"2026-03-30T07:04:44.399Z","message":{"role":"toolResult","toolCallId":"toolu_01FAk8PVqsT6gBau9VB4NYrY","toolName":"read","content":[{"type":"text","text":"\"\"\"initial schema — 7 core entities\n\nRevision ID: 001_initial\nRevises:\nCreate Date: 2026-03-29\n\"\"\"\nfrom typing import Sequence, Union\n\nfrom alembic import op\nimport sqlalchemy as sa\nfrom sqlalchemy.dialects.postgresql import ARRAY, JSONB, UUID\n\n# revision identifiers, used by Alembic.\nrevision: str = \"001_initial\"\ndown_revision: Union[str, None] = None\nbranch_labels: Union[str, Sequence[str], None] = None\ndepends_on: Union[str, Sequence[str], None] = None\n\n\ndef upgrade() -> None:\n    # ── Enum types ───────────────────────────────────────────────────────\n    content_type = sa.Enum(\n        \"tutorial\", \"livestream\", \"breakdown\", \"short_form\",\n        name=\"content_type\",\n    )\n    processing_status = sa.Enum(\n        \"pending\", \"transcribed\", \"extracted\", \"reviewed\", \"published\",\n        name=\"processing_status\",\n    )\n    key_moment_content_type = sa.Enum(\n        \"technique\", \"settings\", \"reasoning\", \"workflow\",\n        name=\"key_moment_content_type\",\n    )\n    review_status = sa.Enum(\n        \"pending\", \"approved\", \"edited\", \"rejected\",\n        name=\"review_status\",\n    )\n    source_quality = sa.Enum(\n        \"structured\", \"mixed\", \"unstructured\",\n        name=\"source_quality\",\n    )\n    page_review_status = sa.Enum(\n        \"draft\", \"reviewed\", \"published\",\n        name=\"page_review_status\",\n    )\n    relationship_type = sa.Enum(\n        \"same_technique_other_creator\", \"same_creator_adjacent\", \"general_cross_reference\",\n        name=\"relationship_type\",\n    )\n\n    # ── creators ─────────────────────────────────────────────────────────\n    op.create_table(\n        \"creators\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"name\", sa.String(255), nullable=False),\n        sa.Column(\"slug\", sa.String(255), nullable=False, unique=True),\n        sa.Column(\"genres\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"folder_name\", sa.String(255), nullable=False),\n        sa.Column(\"view_count\", sa.Integer, nullable=False, server_default=\"0\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n\n    # ── source_videos ────────────────────────────────────────────────────\n    op.create_table(\n        \"source_videos\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"creator_id\", UUID(as_uuid=True), sa.ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"filename\", sa.String(500), nullable=False),\n        sa.Column(\"file_path\", sa.String(1000), nullable=False),\n        sa.Column(\"duration_seconds\", sa.Integer, nullable=True),\n        sa.Column(\"content_type\", content_type, nullable=False),\n        sa.Column(\"transcript_path\", sa.String(1000), nullable=True),\n        sa.Column(\"processing_status\", processing_status, nullable=False, server_default=\"pending\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_source_videos_creator_id\", \"source_videos\", [\"creator_id\"])\n\n    # ── transcript_segments ──────────────────────────────────────────────\n    op.create_table(\n        \"transcript_segments\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_video_id\", UUID(as_uuid=True), sa.ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"start_time\", sa.Float, nullable=False),\n        sa.Column(\"end_time\", sa.Float, nullable=False),\n        sa.Column(\"text\", sa.Text, nullable=False),\n        sa.Column(\"segment_index\", sa.Integer, nullable=False),\n        sa.Column(\"topic_label\", sa.String(255), nullable=True),\n    )\n    op.create_index(\"ix_transcript_segments_video_id\", \"transcript_segments\", [\"source_video_id\"])\n\n    # ── technique_pages (must come before key_moments due to FK) ─────────\n    op.create_table(\n        \"technique_pages\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"creator_id\", UUID(as_uuid=True), sa.ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"title\", sa.String(500), nullable=False),\n        sa.Column(\"slug\", sa.String(500), nullable=False, unique=True),\n        sa.Column(\"topic_category\", sa.String(255), nullable=False),\n        sa.Column(\"topic_tags\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"summary\", sa.Text, nullable=True),\n        sa.Column(\"body_sections\", JSONB, nullable=True),\n        sa.Column(\"signal_chains\", JSONB, nullable=True),\n        sa.Column(\"plugins\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"source_quality\", source_quality, nullable=True),\n        sa.Column(\"view_count\", sa.Integer, nullable=False, server_default=\"0\"),\n        sa.Column(\"review_status\", page_review_status, nullable=False, server_default=\"draft\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_technique_pages_creator_id\", \"technique_pages\", [\"creator_id\"])\n    op.create_index(\"ix_technique_pages_topic_category\", \"technique_pages\", [\"topic_category\"])\n\n    # ── key_moments ──────────────────────────────────────────────────────\n    op.create_table(\n        \"key_moments\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_video_id\", UUID(as_uuid=True), sa.ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"technique_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"SET NULL\"), nullable=True),\n        sa.Column(\"title\", sa.String(500), nullable=False),\n        sa.Column(\"summary\", sa.Text, nullable=False),\n        sa.Column(\"start_time\", sa.Float, nullable=False),\n        sa.Column(\"end_time\", sa.Float, nullable=False),\n        sa.Column(\"content_type\", key_moment_content_type, nullable=False),\n        sa.Column(\"plugins\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"review_status\", review_status, nullable=False, server_default=\"pending\"),\n        sa.Column(\"raw_transcript\", sa.Text, nullable=True),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_key_moments_source_video_id\", \"key_moments\", [\"source_video_id\"])\n    op.create_index(\"ix_key_moments_technique_page_id\", \"key_moments\", [\"technique_page_id\"])\n\n    # ── related_technique_links ──────────────────────────────────────────\n    op.create_table(\n        \"related_technique_links\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"target_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"relationship\", relationship_type, nullable=False),\n        sa.UniqueConstraint(\"source_page_id\", \"target_page_id\", \"relationship\", name=\"uq_technique_link\"),\n    )\n\n    # ── tags ─────────────────────────────────────────────────────────────\n    op.create_table(\n        \"tags\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"name\", sa.String(255), nullable=False, unique=True),\n        sa.Column(\"category\", sa.String(255), nullable=False),\n        sa.Column(\"aliases\", ARRAY(sa.String), nullable=True),\n    )\n    op.create_index(\"ix_tags_category\", \"tags\", [\"category\"])\n\n\ndef downgrade() -> None:\n    op.drop_table(\"tags\")\n    op.drop_table(\"related_technique_links\")\n    op.drop_table(\"key_moments\")\n    op.drop_table(\"technique_pages\")\n    op.drop_table(\"transcript_segments\")\n    op.drop_table(\"source_videos\")\n    op.drop_table(\"creators\")\n\n    # Drop enum types\n    for name in [\n        \"relationship_type\", \"page_review_status\", \"source_quality\",\n        \"review_status\", \"key_moment_content_type\", \"processing_status\",\n        \"content_type\",\n    ]:\n        sa.Enum(name=name).drop(op.get_bind(), checkfirst=True)\n"}],"isError":false,"timestamp":1774854284397}}
{"type":"message","id":"157a3df4","parentId":"7a783499","timestamp":"2026-03-30T07:04:44.401Z","message":{"role":"toolResult","toolCallId":"toolu_016U3AYbpqauaJFkrLf1KxSk","toolName":"read","content":[{"type":"text","text":"\"\"\"Application configuration loaded from environment variables.\"\"\"\n\nfrom functools import lru_cache\n\nfrom pydantic_settings import BaseSettings\n\n\nclass Settings(BaseSettings):\n    \"\"\"Chrysopedia API settings.\n\n    Values are loaded from environment variables (or .env file via\n    pydantic-settings' dotenv support).\n    \"\"\"\n\n    # Database\n    database_url: str = \"postgresql+asyncpg://chrysopedia:changeme@localhost:5433/chrysopedia\"\n\n    # Redis\n    redis_url: str = \"redis://localhost:6379/0\"\n\n    # Application\n    app_env: str = \"development\"\n    app_log_level: str = \"info\"\n    app_secret_key: str = \"changeme-generate-a-real-secret\"\n\n    # CORS\n    cors_origins: list[str] = [\"*\"]\n\n    # LLM endpoint (OpenAI-compatible)\n    llm_api_url: str = \"http://localhost:11434/v1\"\n    llm_api_key: str = \"sk-placeholder\"\n    llm_model: str = \"fyn-llm-agent-chat\"\n    llm_fallback_url: str = \"http://localhost:11434/v1\"\n    llm_fallback_model: str = \"fyn-llm-agent-chat\"\n\n    # Per-stage model overrides (optional — falls back to llm_model / \"chat\")\n    llm_stage2_model: str | None = \"fyn-llm-agent-chat\"   # segmentation — mechanical, fast chat\n    llm_stage2_modality: str = \"chat\"\n    llm_stage3_model: str | None = \"fyn-llm-agent-think\"  # extraction — reasoning\n    llm_stage3_modality: str = \"thinking\"\n    llm_stage4_model: str | None = \"fyn-llm-agent-chat\"   # classification — mechanical, fast chat\n    llm_stage4_modality: str = \"chat\"\n    llm_stage5_model: str | None = \"fyn-llm-agent-think\"  # synthesis — reasoning\n    llm_stage5_modality: str = \"thinking\"\n\n    # Max tokens for LLM responses (OpenWebUI defaults to 1000 which truncates pipeline JSON)\n    llm_max_tokens: int = 65536\n\n    # Embedding endpoint\n    embedding_api_url: str = \"http://localhost:11434/v1\"\n    embedding_model: str = \"nomic-embed-text\"\n    embedding_dimensions: int = 768\n\n    # Qdrant\n    qdrant_url: str = \"http://localhost:6333\"\n    qdrant_collection: str = \"chrysopedia\"\n\n    # Prompt templates\n    prompts_path: str = \"./prompts\"\n\n    # Review mode — when True, extracted moments go to review queue before publishing\n    review_mode: bool = True\n\n    # File storage\n    transcript_storage_path: str = \"/data/transcripts\"\n    video_metadata_path: str = \"/data/video_meta\"\n\n    model_config = {\n        \"env_file\": \".env\",\n        \"env_file_encoding\": \"utf-8\",\n        \"case_sensitive\": False,\n    }\n\n\n@lru_cache\ndef get_settings() -> Settings:\n    \"\"\"Return cached application settings (singleton).\"\"\"\n    return Settings()\n"}],"isError":false,"timestamp":1774854284398}}
{"type":"message","id":"2728fe49","parentId":"157a3df4","timestamp":"2026-03-30T07:04:49.185Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me read the stage 5 synthesis function to understand where the snapshot hook needs to go."},{"type":"toolCall","id":"toolu_01BHeC3W4zbVQrUykYozAB7a","name":"read","arguments":{"limit":50,"offset":1,"path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":113,"cacheRead":60913,"cacheWrite":7141,"totalTokens":68168,"cost":{"input":0.000005,"output":0.0028250000000000003,"cacheRead":0.030456499999999997,"cacheWrite":0.044631250000000004,"total":0.07791775000000001}},"stopReason":"toolUse","timestamp":1774854284399}}
{"type":"message","id":"214bb265","parentId":"2728fe49","timestamp":"2026-03-30T07:04:49.189Z","message":{"role":"toolResult","toolCallId":"toolu_01BHeC3W4zbVQrUykYozAB7a","toolName":"read","content":[{"type":"text","text":"\"\"\"Pipeline stage tasks (stages 2-5) and run_pipeline orchestrator.\n\nEach stage reads from PostgreSQL via sync SQLAlchemy, loads its prompt\ntemplate from disk, calls the LLM client, parses the response, writes\nresults back, and updates processing_status on SourceVideo.\n\nCelery tasks are synchronous — all DB access uses ``sqlalchemy.orm.Session``.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport json\nimport logging\nimport time\nfrom collections import defaultdict\nfrom pathlib import Path\n\nimport yaml\nfrom celery import chain as celery_chain\nfrom pydantic import ValidationError\nfrom sqlalchemy import create_engine, select\nfrom sqlalchemy.orm import Session, sessionmaker\n\nfrom config import get_settings\nfrom models import (\n    KeyMoment,\n    KeyMomentContentType,\n    ProcessingStatus,\n    SourceVideo,\n    TechniquePage,\n    TranscriptSegment,\n)\nfrom pipeline.embedding_client import EmbeddingClient\nfrom pipeline.llm_client import LLMClient\nfrom pipeline.qdrant_client import QdrantManager\nfrom pipeline.schemas import (\n    ClassificationResult,\n    ExtractionResult,\n    SegmentationResult,\n    SynthesisResult,\n)\nfrom worker import celery_app\n\nlogger = logging.getLogger(__name__)\n\n# ── Helpers ──────────────────────────────────────────────────────────────────\n\n_engine = None\n_SessionLocal = None\n\n\n[768 more lines in file. Use offset=51 to continue.]"}],"isError":false,"timestamp":1774854289187}}
{"type":"message","id":"e3d2ea29","parentId":"214bb265","timestamp":"2026-03-30T07:04:52.451Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01H3hQuSAiciJDC6GerxFrrJ","name":"read","arguments":{"limit":80,"offset":51,"path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":91,"cacheRead":68054,"cacheWrite":492,"totalTokens":68638,"cost":{"input":0.000005,"output":0.002275,"cacheRead":0.034027,"cacheWrite":0.003075,"total":0.039382}},"stopReason":"toolUse","timestamp":1774854289188}}
{"type":"message","id":"3aba6bbe","parentId":"e3d2ea29","timestamp":"2026-03-30T07:04:52.454Z","message":{"role":"toolResult","toolCallId":"toolu_01H3hQuSAiciJDC6GerxFrrJ","toolName":"read","content":[{"type":"text","text":"\ndef _get_sync_engine():\n    \"\"\"Create a sync SQLAlchemy engine, converting the async URL if needed.\"\"\"\n    global _engine\n    if _engine is None:\n        settings = get_settings()\n        url = settings.database_url\n        # Convert async driver to sync driver\n        url = url.replace(\"postgresql+asyncpg://\", \"postgresql+psycopg2://\")\n        _engine = create_engine(url, pool_pre_ping=True, pool_size=5, max_overflow=10)\n    return _engine\n\n\ndef _get_sync_session() -> Session:\n    \"\"\"Create a sync SQLAlchemy session for Celery tasks.\"\"\"\n    global _SessionLocal\n    if _SessionLocal is None:\n        _SessionLocal = sessionmaker(bind=_get_sync_engine())\n    return _SessionLocal()\n\n\ndef _load_prompt(template_name: str) -> str:\n    \"\"\"Read a prompt template from the prompts directory.\n\n    Raises FileNotFoundError if the template does not exist.\n    \"\"\"\n    settings = get_settings()\n    path = Path(settings.prompts_path) / template_name\n    if not path.exists():\n        logger.error(\"Prompt template not found: %s\", path)\n        raise FileNotFoundError(f\"Prompt template not found: {path}\")\n    return path.read_text(encoding=\"utf-8\")\n\n\ndef _get_llm_client() -> LLMClient:\n    \"\"\"Return an LLMClient configured from settings.\"\"\"\n    return LLMClient(get_settings())\n\n\ndef _get_stage_config(stage_num: int) -> tuple[str | None, str]:\n    \"\"\"Return (model_override, modality) for a pipeline stage.\n\n    Reads stage-specific config from Settings. If the stage-specific model\n    is None/empty, returns None (LLMClient will use its default). If the\n    stage-specific modality is unset, defaults to \"chat\".\n    \"\"\"\n    settings = get_settings()\n    model = getattr(settings, f\"llm_stage{stage_num}_model\", None) or None\n    modality = getattr(settings, f\"llm_stage{stage_num}_modality\", None) or \"chat\"\n    return model, modality\n\n\ndef _load_canonical_tags() -> dict:\n    \"\"\"Load canonical tag taxonomy from config/canonical_tags.yaml.\"\"\"\n    # Walk up from backend/ to find config/\n    candidates = [\n        Path(\"config/canonical_tags.yaml\"),\n        Path(\"../config/canonical_tags.yaml\"),\n    ]\n    for candidate in candidates:\n        if candidate.exists():\n            with open(candidate, encoding=\"utf-8\") as f:\n                return yaml.safe_load(f)\n    raise FileNotFoundError(\n        \"canonical_tags.yaml not found. Searched: \" + \", \".join(str(c) for c in candidates)\n    )\n\n\ndef _format_taxonomy_for_prompt(tags_data: dict) -> str:\n    \"\"\"Format the canonical tags taxonomy as readable text for the LLM prompt.\"\"\"\n    lines = []\n    for cat in tags_data.get(\"categories\", []):\n        lines.append(f\"Category: {cat['name']}\")\n        lines.append(f\"  Description: {cat['description']}\")\n        lines.append(f\"  Sub-topics: {', '.join(cat.get('sub_topics', []))}\")\n        lines.append(\"\")\n    return \"\\n\".join(lines)\n\n\ndef _safe_parse_llm_response(\n\n[688 more lines in file. Use offset=131 to continue.]"}],"isError":false,"timestamp":1774854292453}}
{"type":"message","id":"acccf125","parentId":"3aba6bbe","timestamp":"2026-03-30T07:04:56.066Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me find the stage5_synthesis function — the task plan says it's around lines 480-618."},{"type":"toolCall","id":"toolu_01NttRdeKvh2pdJT3YtNDipf","name":"read","arguments":{"limit":180,"offset":460,"path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":116,"cacheRead":68054,"cacheWrite":1452,"totalTokens":69623,"cost":{"input":0.000005,"output":0.0029000000000000002,"cacheRead":0.034027,"cacheWrite":0.009075,"total":0.046007}},"stopReason":"toolUse","timestamp":1774854292453}}
{"type":"message","id":"7d2f58f4","parentId":"acccf125","timestamp":"2026-03-30T07:04:56.069Z","message":{"role":"toolResult","toolCallId":"toolu_01NttRdeKvh2pdJT3YtNDipf","toolName":"read","content":[{"type":"text","text":"    key = f\"chrysopedia:classification:{video_id}\"\n    r.set(key, json.dumps(data), ex=86400)  # Expire after 24 hours\n\n\ndef _load_classification_data(video_id: str) -> list[dict]:\n    \"\"\"Load classification data from Redis.\"\"\"\n    import redis\n\n    settings = get_settings()\n    r = redis.Redis.from_url(settings.redis_url)\n    key = f\"chrysopedia:classification:{video_id}\"\n    raw = r.get(key)\n    if raw is None:\n        return []\n    return json.loads(raw)\n\n\n# ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n\n@celery_app.task(bind=True, max_retries=3, default_retry_delay=30)\ndef stage5_synthesis(self, video_id: str) -> str:\n    \"\"\"Synthesize technique pages from classified key moments.\n\n    Groups moments by (creator, topic_category), calls the LLM to synthesize\n    each group into a TechniquePage, creates/updates page rows, and links\n    KeyMoments to their TechniquePage.\n\n    Sets processing_status to 'reviewed' (or 'published' if review_mode is False).\n\n    Returns the video_id for chain compatibility.\n    \"\"\"\n    start = time.monotonic()\n    logger.info(\"Stage 5 (synthesis) starting for video_id=%s\", video_id)\n\n    settings = get_settings()\n    session = _get_sync_session()\n    try:\n        # Load video and moments\n        video = session.execute(\n            select(SourceVideo).where(SourceVideo.id == video_id)\n        ).scalar_one()\n\n        moments = (\n            session.execute(\n                select(KeyMoment)\n                .where(KeyMoment.source_video_id == video_id)\n                .order_by(KeyMoment.start_time)\n            )\n            .scalars()\n            .all()\n        )\n\n        if not moments:\n            logger.info(\"Stage 5: No moments found for video_id=%s, skipping.\", video_id)\n            return video_id\n\n        # Load classification data from stage 4\n        classification_data = _load_classification_data(video_id)\n        cls_by_moment_id = {c[\"moment_id\"]: c for c in classification_data}\n\n        # Group moments by topic_category (from classification)\n        groups: dict[str, list[tuple[KeyMoment, dict]]] = defaultdict(list)\n        for moment in moments:\n            cls_info = cls_by_moment_id.get(str(moment.id), {})\n            category = cls_info.get(\"topic_category\", \"Uncategorized\")\n            groups[category].append((moment, cls_info))\n\n        system_prompt = _load_prompt(\"stage5_synthesis.txt\")\n        llm = _get_llm_client()\n        model_override, modality = _get_stage_config(5)\n        logger.info(\"Stage 5 using model=%s, modality=%s\", model_override or \"default\", modality)\n        pages_created = 0\n\n        for category, moment_group in groups.items():\n            # Build moments text for the LLM\n            moments_lines = []\n            all_tags: set[str] = set()\n            for i, (m, cls_info) in enumerate(moment_group):\n                tags = cls_info.get(\"topic_tags\", [])\n                all_tags.update(tags)\n                moments_lines.append(\n                    f\"[{i}] Title: {m.title}\\n\"\n                    f\"    Summary: {m.summary}\\n\"\n                    f\"    Content type: {m.content_type.value}\\n\"\n                    f\"    Time: {m.start_time:.1f}s - {m.end_time:.1f}s\\n\"\n                    f\"    Plugins: {', '.join(m.plugins) if m.plugins else 'none'}\\n\"\n                    f\"    Category: {category}\\n\"\n                    f\"    Tags: {', '.join(tags) if tags else 'none'}\\n\"\n                    f\"    Transcript excerpt: {(m.raw_transcript or '')[:300]}\"\n                )\n            moments_text = \"\\n\\n\".join(moments_lines)\n\n            user_prompt = f\"<moments>\\n{moments_text}\\n</moments>\"\n\n            raw = llm.complete(system_prompt, user_prompt, response_model=SynthesisResult,\n                               modality=modality, model_override=model_override)\n            result = _safe_parse_llm_response(raw, SynthesisResult, llm, system_prompt, user_prompt,\n                                              modality=modality, model_override=model_override)\n\n            # Create/update TechniquePage rows\n            for page_data in result.pages:\n                # Check if page with this slug already exists\n                existing = session.execute(\n                    select(TechniquePage).where(TechniquePage.slug == page_data.slug)\n                ).scalar_one_or_none()\n\n                if existing:\n                    # Update existing page\n                    existing.title = page_data.title\n                    existing.summary = page_data.summary\n                    existing.body_sections = page_data.body_sections\n                    existing.signal_chains = page_data.signal_chains\n                    existing.plugins = page_data.plugins if page_data.plugins else None\n                    existing.topic_tags = list(all_tags) if all_tags else None\n                    existing.source_quality = page_data.source_quality\n                    page = existing\n                else:\n                    page = TechniquePage(\n                        creator_id=video.creator_id,\n                        title=page_data.title,\n                        slug=page_data.slug,\n                        topic_category=page_data.topic_category or category,\n                        topic_tags=list(all_tags) if all_tags else None,\n                        summary=page_data.summary,\n                        body_sections=page_data.body_sections,\n                        signal_chains=page_data.signal_chains,\n                        plugins=page_data.plugins if page_data.plugins else None,\n                        source_quality=page_data.source_quality,\n                    )\n                    session.add(page)\n                    session.flush()  # Get the page.id assigned\n\n                pages_created += 1\n\n                # Link moments to the technique page\n                for m, _ in moment_group:\n                    m.technique_page_id = page.id\n\n        # Update processing_status\n        if settings.review_mode:\n            video.processing_status = ProcessingStatus.reviewed\n        else:\n            video.processing_status = ProcessingStatus.published\n\n        session.commit()\n        elapsed = time.monotonic() - start\n        logger.info(\n            \"Stage 5 (synthesis) completed for video_id=%s in %.1fs — %d pages created/updated\",\n            video_id, elapsed, pages_created,\n        )\n        return video_id\n\n    except FileNotFoundError:\n        raise\n    except Exception as exc:\n        session.rollback()\n        logger.error(\"Stage 5 failed for video_id=%s: %s\", video_id, exc)\n        raise self.retry(exc=exc)\n    finally:\n        session.close()\n\n\n# ── Stage 6: Embed & Index ───────────────────────────────────────────────────\n\n@celery_app.task(bind=True, max_retries=0)\ndef stage6_embed_and_index(self, video_id: str) -> str:\n    \"\"\"Generate embeddings for technique pages and key moments, then upsert to Qdrant.\n\n    This is a non-blocking side-effect stage — failures are logged but do not\n    fail the pipeline. Embeddings can be regenerated later. Does NOT update\n    processing_status.\n\n    Returns the video_id for chain compatibility.\n    \"\"\"\n    start = time.monotonic()\n    logger.info(\"Stage 6 (embed & index) starting for video_id=%s\", video_id)\n\n    settings = get_settings()\n    session = _get_sync_session()\n    try:\n\n[179 more lines in file. Use offset=640 to continue.]"}],"isError":false,"timestamp":1774854296067}}
{"type":"message","id":"065abba3","parentId":"7d2f58f4","timestamp":"2026-03-30T07:05:00.624Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. I now have a clear picture of the codebase. Let me also check what prompt files exist to understand the `_capture_pipeline_metadata` helper requirements."},{"type":"toolCall","id":"toolu_013KvLyaDTQgvxmYF4BKAunY","name":"bash","arguments":{"command":"ls backend/prompts/ 2>/dev/null || echo \"No prompts dir at backend/prompts\"; ls prompts/ 2>/dev/null || echo \"No prompts dir at prompts/\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":134,"cacheRead":69506,"cacheWrite":2172,"totalTokens":71813,"cost":{"input":0.000005,"output":0.00335,"cacheRead":0.034753,"cacheWrite":0.013575,"total":0.05168299999999999}},"stopReason":"toolUse","timestamp":1774854296068}}
{"type":"message","id":"ad88468c","parentId":"065abba3","timestamp":"2026-03-30T07:05:00.640Z","message":{"role":"toolResult","toolCallId":"toolu_013KvLyaDTQgvxmYF4BKAunY","toolName":"bash","content":[{"type":"text","text":"No prompts dir at backend/prompts\nREADME.md\nstage2_segmentation.txt\nstage3_extraction.txt\nstage4_classification.txt\nstage5_synthesis.txt\n"}],"isError":false,"timestamp":1774854300638}}
{"type":"message","id":"cf1ca4cd","parentId":"ad88468c","timestamp":"2026-03-30T07:05:10.507Z","message":{"role":"assistant","content":[{"type":"text","text":"Prompts live at `./prompts/` (relative to project root) but config says `./prompts` which inside Docker resolves relative to the WORKDIR. In the Celery worker context, it'll resolve from wherever the worker runs. Good — the `_capture_pipeline_metadata` helper needs to handle the same path resolution as `_load_prompt`.\n\nNow I'll implement all three files. Starting with the model.\n\n**Step 1: Add `TechniquePageVersion` model to `backend/models.py`**"},{"type":"toolCall","id":"toolu_013kXpXPXTXGaWyhwzcXBvev","name":"edit","arguments":{"newText":"class 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\"","oldText":"class Tag(Base):\n    __tablename__ = \"tags\"","path":"backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":487,"cacheRead":71678,"cacheWrite":189,"totalTokens":72355,"cost":{"input":0.000005,"output":0.012175,"cacheRead":0.035838999999999996,"cacheWrite":0.00118125,"total":0.049200249999999994}},"stopReason":"toolUse","timestamp":1774854300638}}
{"type":"message","id":"62742a2c","parentId":"cf1ca4cd","timestamp":"2026-03-30T07:05:10.514Z","message":{"role":"toolResult","toolCallId":"toolu_013kXpXPXTXGaWyhwzcXBvev","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/models.py."}],"details":{"diff":" 287         foreign_keys=[target_page_id], back_populates=\"incoming_links\"\n 288     )\n 289 \n 290 \n+291 class TechniquePageVersion(Base):\n+292     \"\"\"Snapshot of a TechniquePage before a pipeline re-synthesis overwrites it.\"\"\"\n+293     __tablename__ = \"technique_page_versions\"\n+294 \n+295     id: Mapped[uuid.UUID] = _uuid_pk()\n+296     technique_page_id: Mapped[uuid.UUID] = mapped_column(\n+297         ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n+298     )\n+299     version_number: Mapped[int] = mapped_column(Integer, nullable=False)\n+300     content_snapshot: Mapped[dict] = mapped_column(JSONB, nullable=False)\n+301     pipeline_metadata: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n+302     created_at: Mapped[datetime] = mapped_column(\n+303         default=_now, server_default=func.now()\n+304     )\n+305 \n+306     # relationships\n+307     technique_page: Mapped[TechniquePage] = sa_relationship(\n+308         back_populates=\"versions\"\n+309     )\n+310 \n+311 \n 312 class Tag(Base):\n 313     __tablename__ = \"tags\"\n 314 \n 315     id: Mapped[uuid.UUID] = _uuid_pk()","firstChangedLine":291},"isError":false,"timestamp":1774854310513}}
{"type":"message","id":"be788ba9","parentId":"62742a2c","timestamp":"2026-03-30T07:05:16.953Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add the `versions` relationship to `TechniquePage`:"},{"type":"toolCall","id":"toolu_01EQioJk1EXipUCzTwmCW37X","name":"edit","arguments":{"newText":"    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    )","oldText":"    outgoing_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.source_page_id\", back_populates=\"source_page\"\n    )","path":"backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":266,"cacheRead":71867,"cacheWrite":508,"totalTokens":72642,"cost":{"input":0.000005,"output":0.0066500000000000005,"cacheRead":0.0359335,"cacheWrite":0.0031750000000000003,"total":0.0457635}},"stopReason":"toolUse","timestamp":1774854310513}}
{"type":"message","id":"ef696f07","parentId":"be788ba9","timestamp":"2026-03-30T07:05:16.959Z","message":{"role":"toolResult","toolCallId":"toolu_01EQioJk1EXipUCzTwmCW37X","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/models.py."}],"details":{"diff":" 252     creator: Mapped[Creator] = sa_relationship(back_populates=\"technique_pages\")\n 253     key_moments: Mapped[list[KeyMoment]] = sa_relationship(\n 254         back_populates=\"technique_page\", foreign_keys=[KeyMoment.technique_page_id]\n 255     )\n+256     versions: Mapped[list[TechniquePageVersion]] = sa_relationship(\n+257         back_populates=\"technique_page\", order_by=\"TechniquePageVersion.version_number\"\n+258     )\n 259     outgoing_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n 260         foreign_keys=\"RelatedTechniqueLink.source_page_id\", back_populates=\"source_page\"\n 261     )\n 262     incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(","firstChangedLine":256},"isError":false,"timestamp":1774854316958}}
{"type":"message","id":"39648832","parentId":"ef696f07","timestamp":"2026-03-30T07:05:24.305Z","message":{"role":"assistant","content":[{"type":"text","text":"**Step 2: Create the Alembic migration**"},{"type":"toolCall","id":"toolu_01X95KyG1EmL62bGazBWR7Jj","name":"write","arguments":{"content":"\"\"\"technique_page_versions table for article versioning\n\nRevision ID: 002_technique_page_versions\nRevises: 001_initial\nCreate Date: 2026-03-30\n\"\"\"\nfrom typing import Sequence, Union\n\nfrom alembic import op\nimport sqlalchemy as sa\nfrom sqlalchemy.dialects.postgresql import JSONB, UUID\n\n# revision identifiers, used by Alembic.\nrevision: str = \"002_technique_page_versions\"\ndown_revision: Union[str, None] = \"001_initial\"\nbranch_labels: Union[str, Sequence[str], None] = None\ndepends_on: Union[str, Sequence[str], None] = None\n\n\ndef upgrade() -> None:\n    op.create_table(\n        \"technique_page_versions\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"technique_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"version_number\", sa.Integer, nullable=False),\n        sa.Column(\"content_snapshot\", JSONB, nullable=False),\n        sa.Column(\"pipeline_metadata\", JSONB, nullable=True),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\n        \"ix_technique_page_versions_page_version\",\n        \"technique_page_versions\",\n        [\"technique_page_id\", \"version_number\"],\n        unique=True,\n    )\n\n\ndef downgrade() -> None:\n    op.drop_table(\"technique_page_versions\")\n","path":"alembic/versions/002_technique_page_versions.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":524,"cacheRead":72375,"cacheWrite":287,"totalTokens":73187,"cost":{"input":0.000005,"output":0.0131,"cacheRead":0.0361875,"cacheWrite":0.00179375,"total":0.05108624999999999}},"stopReason":"toolUse","timestamp":1774854316958}}
{"type":"message","id":"4cf3b3a6","parentId":"39648832","timestamp":"2026-03-30T07:05:24.308Z","message":{"role":"toolResult","toolCallId":"toolu_01X95KyG1EmL62bGazBWR7Jj","toolName":"write","content":[{"type":"text","text":"Successfully wrote 1392 bytes to alembic/versions/002_technique_page_versions.py"}],"isError":false,"timestamp":1774854324307}}
{"type":"message","id":"e2031ddf","parentId":"4cf3b3a6","timestamp":"2026-03-30T07:05:31.135Z","message":{"role":"assistant","content":[{"type":"text","text":"**Step 3: Add `_capture_pipeline_metadata()` helper and snapshot hook in stage 5**\n\nI need to add the import for `TechniquePageVersion` and `func` at the top of stages.py, then the helper, and then modify the `if existing:` block."},{"type":"toolCall","id":"toolu_01AE6FQcPjSe4QYFiJVAQCNz","name":"edit","arguments":{"newText":"from models import (\n    KeyMoment,\n    KeyMomentContentType,\n    ProcessingStatus,\n    SourceVideo,\n    TechniquePage,\n    TechniquePageVersion,\n    TranscriptSegment,\n)","oldText":"from models import (\n    KeyMoment,\n    KeyMomentContentType,\n    ProcessingStatus,\n    SourceVideo,\n    TechniquePage,\n    TranscriptSegment,\n)","path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":264,"cacheRead":72662,"cacheWrite":559,"totalTokens":73486,"cost":{"input":0.000005,"output":0.0066,"cacheRead":0.036330999999999995,"cacheWrite":0.0034937500000000003,"total":0.04642974999999999}},"stopReason":"toolUse","timestamp":1774854324307}}
{"type":"message","id":"95d7a6c7","parentId":"e2031ddf","timestamp":"2026-03-30T07:05:31.160Z","message":{"role":"toolResult","toolCallId":"toolu_01AE6FQcPjSe4QYFiJVAQCNz","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/stages.py."}],"details":{"diff":"  27     KeyMomentContentType,\n  28     ProcessingStatus,\n  29     SourceVideo,\n  30     TechniquePage,\n+ 31     TechniquePageVersion,\n  32     TranscriptSegment,\n  33 )\n  34 from pipeline.embedding_client import EmbeddingClient\n  35 from pipeline.llm_client import LLMClient","firstChangedLine":31},"isError":false,"timestamp":1774854331158}}
{"type":"message","id":"2aed72c3","parentId":"95d7a6c7","timestamp":"2026-03-30T07:05:34.447Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add `hashlib` to the imports at the top:"},{"type":"toolCall","id":"toolu_019JdhAhc7U7ZCX3igZfnpEb","name":"read","arguments":{"limit":20,"offset":10,"path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":105,"cacheRead":73221,"cacheWrite":287,"totalTokens":73614,"cost":{"input":0.000005,"output":0.002625,"cacheRead":0.0366105,"cacheWrite":0.00179375,"total":0.041034249999999994}},"stopReason":"toolUse","timestamp":1774854331159}}
{"type":"message","id":"40851979","parentId":"2aed72c3","timestamp":"2026-03-30T07:05:34.451Z","message":{"role":"toolResult","toolCallId":"toolu_019JdhAhc7U7ZCX3igZfnpEb","toolName":"read","content":[{"type":"text","text":"from __future__ import annotations\n\nimport json\nimport logging\nimport time\nfrom collections import defaultdict\nfrom pathlib import Path\n\nimport yaml\nfrom celery import chain as celery_chain\nfrom pydantic import ValidationError\nfrom sqlalchemy import create_engine, select\nfrom sqlalchemy.orm import Session, sessionmaker\n\nfrom config import get_settings\nfrom models import (\n    KeyMoment,\n    KeyMomentContentType,\n    ProcessingStatus,\n    SourceVideo,\n\n[790 more lines in file. Use offset=30 to continue.]"}],"isError":false,"timestamp":1774854334450}}
{"type":"message","id":"1976e209","parentId":"40851979","timestamp":"2026-03-30T07:05:39.752Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_019wcH45QHAPBUmG9ZEoAXHM","name":"edit","arguments":{"newText":"import hashlib\nimport json\nimport logging\nimport time\nfrom collections import defaultdict\nfrom pathlib import Path","oldText":"import json\nimport logging\nimport time\nfrom collections import defaultdict\nfrom pathlib import Path","path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":135,"cacheRead":73508,"cacheWrite":244,"totalTokens":73888,"cost":{"input":0.000005,"output":0.003375,"cacheRead":0.036753999999999995,"cacheWrite":0.001525,"total":0.041658999999999995}},"stopReason":"toolUse","timestamp":1774854334451}}
{"type":"message","id":"70d363fa","parentId":"1976e209","timestamp":"2026-03-30T07:05:39.768Z","message":{"role":"toolResult","toolCallId":"toolu_019wcH45QHAPBUmG9ZEoAXHM","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/stages.py."}],"details":{"diff":"   8 \"\"\"\n   9 \n  10 from __future__ import annotations\n  11 \n+ 12 import hashlib\n  13 import json\n  14 import logging\n  15 import time\n  16 from collections import defaultdict","firstChangedLine":12},"isError":false,"timestamp":1774854339766}}
{"type":"message","id":"e09baf6e","parentId":"70d363fa","timestamp":"2026-03-30T07:05:43.438Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add `func` to the sqlalchemy import:"},{"type":"toolCall","id":"toolu_01EgdpArCLRjYsCqLFPJHBVf","name":"edit","arguments":{"newText":"from sqlalchemy import create_engine, func, select","oldText":"from sqlalchemy import create_engine, select","path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":123,"cacheRead":73508,"cacheWrite":402,"totalTokens":74034,"cost":{"input":0.000005,"output":0.003075,"cacheRead":0.036753999999999995,"cacheWrite":0.0025125,"total":0.042346499999999995}},"stopReason":"toolUse","timestamp":1774854339767}}
{"type":"message","id":"fddbc0af","parentId":"e09baf6e","timestamp":"2026-03-30T07:05:43.454Z","message":{"role":"toolResult","toolCallId":"toolu_01EgdpArCLRjYsCqLFPJHBVf","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/stages.py."}],"details":{"diff":"  18 \n  19 import yaml\n  20 from celery import chain as celery_chain\n  21 from pydantic import ValidationError\n- 22 from sqlalchemy import create_engine, select\n+ 22 from sqlalchemy import create_engine, func, select\n  23 from sqlalchemy.orm import Session, sessionmaker\n  24 \n  25 from config import get_settings\n  26 from models import (","firstChangedLine":22},"isError":false,"timestamp":1774854343452}}
{"type":"message","id":"ce70d76b","parentId":"fddbc0af","timestamp":"2026-03-30T07:05:46.988Z","message":{"role":"assistant","content":[{"type":"text","text":"Now add the `_capture_pipeline_metadata()` helper. I'll place it right before the Stage 5 section:"},{"type":"toolCall","id":"toolu_014K8fScZBh1yPbPxeBWLQTJ","name":"read","arguments":{"limit":10,"offset":475,"path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":119,"cacheRead":73910,"cacheWrite":146,"totalTokens":74176,"cost":{"input":0.000005,"output":0.002975,"cacheRead":0.036955,"cacheWrite":0.0009125,"total":0.040847499999999995}},"stopReason":"toolUse","timestamp":1774854343453}}
{"type":"message","id":"031a6eb7","parentId":"ce70d76b","timestamp":"2026-03-30T07:05:46.998Z","message":{"role":"toolResult","toolCallId":"toolu_014K8fScZBh1yPbPxeBWLQTJ","toolName":"read","content":[{"type":"text","text":"        return []\n    return json.loads(raw)\n\n\n# ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n\n@celery_app.task(bind=True, max_retries=3, default_retry_delay=30)\ndef stage5_synthesis(self, video_id: str) -> str:\n    \"\"\"Synthesize technique pages from classified key moments.\n\n\n[336 more lines in file. Use offset=485 to continue.]"}],"isError":false,"timestamp":1774854346996}}
{"type":"message","id":"7a02d246","parentId":"031a6eb7","timestamp":"2026-03-30T07:05:56.249Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01Tt1ZUXAHF9b67dSsNq9755","name":"edit","arguments":{"newText":"    return json.loads(raw)\n\n\ndef _capture_pipeline_metadata() -> dict:\n    \"\"\"Capture current pipeline configuration for version metadata.\n\n    Returns a dict with model names, prompt file SHA-256 hashes, and stage\n    modality settings. Handles missing prompt files gracefully.\n    \"\"\"\n    settings = get_settings()\n    prompts_path = Path(settings.prompts_path)\n\n    # Hash each prompt template file\n    prompt_hashes: dict[str, str] = {}\n    prompt_files = [\n        \"stage2_segmentation.txt\",\n        \"stage3_extraction.txt\",\n        \"stage4_classification.txt\",\n        \"stage5_synthesis.txt\",\n    ]\n    for filename in prompt_files:\n        filepath = prompts_path / filename\n        try:\n            content = filepath.read_bytes()\n            prompt_hashes[filename] = hashlib.sha256(content).hexdigest()\n        except FileNotFoundError:\n            logger.warning(\"Prompt file not found for metadata capture: %s\", filepath)\n            prompt_hashes[filename] = \"\"\n        except OSError as exc:\n            logger.warning(\"Could not read prompt file %s: %s\", filepath, exc)\n            prompt_hashes[filename] = \"\"\n\n    return {\n        \"models\": {\n            \"stage2\": settings.llm_stage2_model,\n            \"stage3\": settings.llm_stage3_model,\n            \"stage4\": settings.llm_stage4_model,\n            \"stage5\": settings.llm_stage5_model,\n            \"embedding\": settings.embedding_model,\n        },\n        \"modalities\": {\n            \"stage2\": settings.llm_stage2_modality,\n            \"stage3\": settings.llm_stage3_modality,\n            \"stage4\": settings.llm_stage4_modality,\n            \"stage5\": settings.llm_stage5_modality,\n        },\n        \"prompt_hashes\": prompt_hashes,\n    }\n\n\n# ── Stage 5: Synthesis ───────────────────────────────────────────────────────","oldText":"    return json.loads(raw)\n\n\n# ── Stage 5: Synthesis ───────────────────────────────────────────────────────","path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":632,"cacheRead":74056,"cacheWrite":244,"totalTokens":74933,"cost":{"input":0.000005,"output":0.0158,"cacheRead":0.037028,"cacheWrite":0.001525,"total":0.054358000000000004}},"stopReason":"toolUse","timestamp":1774854346997}}
{"type":"message","id":"a0b5bf21","parentId":"7a02d246","timestamp":"2026-03-30T07:05:56.273Z","message":{"role":"toolResult","toolCallId":"toolu_01Tt1ZUXAHF9b67dSsNq9755","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/stages.py."}],"details":{"diff":" 475         return []\n 476     return json.loads(raw)\n 477 \n 478 \n+479 def _capture_pipeline_metadata() -> dict:\n+480     \"\"\"Capture current pipeline configuration for version metadata.\n+481 \n+482     Returns a dict with model names, prompt file SHA-256 hashes, and stage\n+483     modality settings. Handles missing prompt files gracefully.\n+484     \"\"\"\n+485     settings = get_settings()\n+486     prompts_path = Path(settings.prompts_path)\n+487 \n+488     # Hash each prompt template file\n+489     prompt_hashes: dict[str, str] = {}\n+490     prompt_files = [\n+491         \"stage2_segmentation.txt\",\n+492         \"stage3_extraction.txt\",\n+493         \"stage4_classification.txt\",\n+494         \"stage5_synthesis.txt\",\n+495     ]\n+496     for filename in prompt_files:\n+497         filepath = prompts_path / filename\n+498         try:\n+499             content = filepath.read_bytes()\n+500             prompt_hashes[filename] = hashlib.sha256(content).hexdigest()\n+501         except FileNotFoundError:\n+502             logger.warning(\"Prompt file not found for metadata capture: %s\", filepath)\n+503             prompt_hashes[filename] = \"\"\n+504         except OSError as exc:\n+505             logger.warning(\"Could not read prompt file %s: %s\", filepath, exc)\n+506             prompt_hashes[filename] = \"\"\n+507 \n+508     return {\n+509         \"models\": {\n+510             \"stage2\": settings.llm_stage2_model,\n+511             \"stage3\": settings.llm_stage3_model,\n+512             \"stage4\": settings.llm_stage4_model,\n+513             \"stage5\": settings.llm_stage5_model,\n+514             \"embedding\": settings.embedding_model,\n+515         },\n+516         \"modalities\": {\n+517             \"stage2\": settings.llm_stage2_modality,\n+518             \"stage3\": settings.llm_stage3_modality,\n+519             \"stage4\": settings.llm_stage4_modality,\n+520             \"stage5\": settings.llm_stage5_modality,\n+521         },\n+522         \"prompt_hashes\": prompt_hashes,\n+523     }\n+524 \n+525 \n 526 # ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n 527 \n 528 @celery_app.task(bind=True, max_retries=3, default_retry_delay=30)\n 529 def stage5_synthesis(self, video_id: str) -> str:","firstChangedLine":479},"isError":false,"timestamp":1774854356272}}
{"type":"message","id":"201e062a","parentId":"a0b5bf21","timestamp":"2026-03-30T07:06:05.644Z","message":{"role":"assistant","content":[{"type":"text","text":"Now wire the snapshot into the `if existing:` block in stage5_synthesis. The snapshot must happen BEFORE any attribute mutations on `existing`."},{"type":"toolCall","id":"toolu_01EiiezS1o9q6CfLwD1wur9d","name":"edit","arguments":{"newText":"                if existing:\n                    # Snapshot existing content before overwriting\n                    try:\n                        snapshot = {\n                            \"title\": existing.title,\n                            \"slug\": existing.slug,\n                            \"topic_category\": existing.topic_category,\n                            \"topic_tags\": existing.topic_tags,\n                            \"summary\": existing.summary,\n                            \"body_sections\": existing.body_sections,\n                            \"signal_chains\": existing.signal_chains,\n                            \"plugins\": existing.plugins,\n                            \"source_quality\": existing.source_quality.value if existing.source_quality else None,\n                        }\n                        version_count = session.execute(\n                            select(func.count()).where(\n                                TechniquePageVersion.technique_page_id == existing.id\n                            )\n                        ).scalar()\n                        version_number = version_count + 1\n\n                        version = TechniquePageVersion(\n                            technique_page_id=existing.id,\n                            version_number=version_number,\n                            content_snapshot=snapshot,\n                            pipeline_metadata=_capture_pipeline_metadata(),\n                        )\n                        session.add(version)\n                        logger.info(\n                            \"Version snapshot v%d created for page slug=%s\",\n                            version_number, existing.slug,\n                        )\n                    except Exception as snap_exc:\n                        logger.error(\n                            \"Failed to create version snapshot for page slug=%s: %s\",\n                            existing.slug, snap_exc,\n                        )\n                        # Best-effort versioning — continue with page update\n\n                    # Update existing page\n                    existing.title = page_data.title","oldText":"                if existing:\n                    # Update existing page\n                    existing.title = page_data.title","path":"backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":553,"cacheRead":74300,"cacheWrite":655,"totalTokens":75509,"cost":{"input":0.000005,"output":0.013825,"cacheRead":0.037149999999999996,"cacheWrite":0.00409375,"total":0.05507375}},"stopReason":"toolUse","timestamp":1774854356272}}
{"type":"message","id":"7555108e","parentId":"201e062a","timestamp":"2026-03-30T07:06:05.664Z","message":{"role":"toolResult","toolCallId":"toolu_01EiiezS1o9q6CfLwD1wur9d","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/stages.py."}],"details":{"diff":" 612                     select(TechniquePage).where(TechniquePage.slug == page_data.slug)\n 613                 ).scalar_one_or_none()\n 614 \n 615                 if existing:\n+616                     # Snapshot existing content before overwriting\n+617                     try:\n+618                         snapshot = {\n+619                             \"title\": existing.title,\n+620                             \"slug\": existing.slug,\n+621                             \"topic_category\": existing.topic_category,\n+622                             \"topic_tags\": existing.topic_tags,\n+623                             \"summary\": existing.summary,\n+624                             \"body_sections\": existing.body_sections,\n+625                             \"signal_chains\": existing.signal_chains,\n+626                             \"plugins\": existing.plugins,\n+627                             \"source_quality\": existing.source_quality.value if existing.source_quality else None,\n+628                         }\n+629                         version_count = session.execute(\n+630                             select(func.count()).where(\n+631                                 TechniquePageVersion.technique_page_id == existing.id\n+632                             )\n+633                         ).scalar()\n+634                         version_number = version_count + 1\n+635 \n+636                         version = TechniquePageVersion(\n+637                             technique_page_id=existing.id,\n+638                             version_number=version_number,\n+639                             content_snapshot=snapshot,\n+640                             pipeline_metadata=_capture_pipeline_metadata(),\n+641                         )\n+642                         session.add(version)\n+643                         logger.info(\n+644                             \"Version snapshot v%d created for page slug=%s\",\n+645                             version_number, existing.slug,\n+646                         )\n+647                     except Exception as snap_exc:\n+648                         logger.error(\n+649                             \"Failed to create version snapshot for page slug=%s: %s\",\n+650                             existing.slug, snap_exc,\n+651                         )\n+652                         # Best-effort versioning — continue with page update\n+653 \n 654                     # Update existing page\n 655                     existing.title = page_data.title\n 656                     existing.summary = page_data.summary\n 657                     existing.body_sections = page_data.body_sections","firstChangedLine":616},"isError":false,"timestamp":1774854365662}}
{"type":"message","id":"15c43b55","parentId":"7555108e","timestamp":"2026-03-30T07:06:11.325Z","message":{"role":"assistant","content":[{"type":"text","text":"All three files are modified. Let me verify the changes look correct by checking the critical sections."},{"type":"toolCall","id":"toolu_019Y7PbSxujTaXrHNJqkPHqA","name":"bash","arguments":{"command":"cd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\""}},{"type":"toolCall","id":"toolu_014T5FSzabvDbHQFYhSXMm6z","name":"bash","arguments":{"command":"test -f alembic/versions/002_technique_page_versions.py && echo \"Migration file exists\" || echo \"MISSING\""}},{"type":"toolCall","id":"toolu_01RDA7WdHTS94Rqyewsv4EPT","name":"bash","arguments":{"command":"grep -q '_capture_pipeline_metadata' backend/pipeline/stages.py && echo \"Helper found\" || echo \"MISSING\""}},{"type":"toolCall","id":"toolu_016HpYQeyP6dTovd8rmFdJTU","name":"bash","arguments":{"command":"grep -q 'TechniquePageVersion' backend/pipeline/stages.py && echo \"Import found\" || echo \"MISSING\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":287,"cacheRead":74955,"cacheWrite":576,"totalTokens":75819,"cost":{"input":0.000005,"output":0.007175,"cacheRead":0.0374775,"cacheWrite":0.0036000000000000003,"total":0.048257499999999995}},"stopReason":"toolUse","timestamp":1774854365663}}
{"type":"message","id":"f99349ab","parentId":"15c43b55","timestamp":"2026-03-30T07:06:11.673Z","message":{"role":"toolResult","toolCallId":"toolu_019Y7PbSxujTaXrHNJqkPHqA","toolName":"bash","content":[{"type":"text","text":"Model OK\n"}],"isError":false,"timestamp":1774854371673}}
{"type":"message","id":"62cd13fb","parentId":"f99349ab","timestamp":"2026-03-30T07:06:11.674Z","message":{"role":"toolResult","toolCallId":"toolu_014T5FSzabvDbHQFYhSXMm6z","toolName":"bash","content":[{"type":"text","text":"Migration file exists\n"}],"isError":false,"timestamp":1774854371673}}
{"type":"message","id":"553f4dc9","parentId":"62cd13fb","timestamp":"2026-03-30T07:06:11.675Z","message":{"role":"toolResult","toolCallId":"toolu_01RDA7WdHTS94Rqyewsv4EPT","toolName":"bash","content":[{"type":"text","text":"Helper found\n"}],"isError":false,"timestamp":1774854371674}}
{"type":"message","id":"185d0eeb","parentId":"553f4dc9","timestamp":"2026-03-30T07:06:11.676Z","message":{"role":"toolResult","toolCallId":"toolu_016HpYQeyP6dTovd8rmFdJTU","toolName":"bash","content":[{"type":"text","text":"Import found\n"}],"isError":false,"timestamp":1774854371674}}
{"type":"message","id":"d6179f89","parentId":"185d0eeb","timestamp":"2026-03-30T07:06:16.068Z","message":{"role":"assistant","content":[{"type":"text","text":"All four verification checks pass. Let me also verify the snapshot hook is correctly placed BEFORE attribute mutations by reading the relevant section:"},{"type":"toolCall","id":"toolu_0188GkPRP9utuvNFix67qHjf","name":"bash","arguments":{"command":"grep -n -A2 'if existing:' backend/pipeline/stages.py | head -20"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":101,"cacheRead":75531,"cacheWrite":409,"totalTokens":76042,"cost":{"input":0.000005,"output":0.0025250000000000003,"cacheRead":0.0377655,"cacheWrite":0.00255625,"total":0.04285175}},"stopReason":"toolUse","timestamp":1774854371675}}
{"type":"message","id":"e0732ac4","parentId":"d6179f89","timestamp":"2026-03-30T07:06:16.084Z","message":{"role":"toolResult","toolCallId":"toolu_0188GkPRP9utuvNFix67qHjf","toolName":"bash","content":[{"type":"text","text":"615:                if existing:\n616-                    # Snapshot existing content before overwriting\n617-                    try:\n"}],"isError":false,"timestamp":1774854376082}}
{"type":"message","id":"9516ef73","parentId":"e0732ac4","timestamp":"2026-03-30T07:06:20.281Z","message":{"role":"assistant","content":[{"type":"text","text":"Good — snapshot logic is at line 616 (right after `if existing:`), and the actual attribute mutation (`existing.title = page_data.title`) comes after the snapshot + error handling block. Let me confirm the ordering is correct:"},{"type":"toolCall","id":"toolu_01ToTUxzWeS2MAXK5pF4JRw7","name":"bash","arguments":{"command":"grep -n 'existing.title\\|snapshot =\\|session.add(version)\\|# Update existing' backend/pipeline/stages.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":135,"cacheRead":75940,"cacheWrite":140,"totalTokens":76216,"cost":{"input":0.000005,"output":0.003375,"cacheRead":0.03797,"cacheWrite":0.000875,"total":0.042225}},"stopReason":"toolUse","timestamp":1774854376083}}
{"type":"message","id":"b8f1f8e4","parentId":"9516ef73","timestamp":"2026-03-30T07:06:20.294Z","message":{"role":"toolResult","toolCallId":"toolu_01ToTUxzWeS2MAXK5pF4JRw7","toolName":"bash","content":[{"type":"text","text":"618:                        snapshot = {\n619:                            \"title\": existing.title,\n642:                        session.add(version)\n654:                    # Update existing page\n655:                    existing.title = page_data.title\n"}],"isError":false,"timestamp":1774854380293}}
{"type":"message","id":"f182a3cf","parentId":"b8f1f8e4","timestamp":"2026-03-30T07:06:25.869Z","message":{"role":"assistant","content":[{"type":"text","text":"Snapshot at 618, version added at 642, mutation at 655. Correct ordering.\n\nLet me also verify the migration follows the 001 pattern structurally and the model has all required fields:"},{"type":"toolCall","id":"toolu_01NoCvhRqh3w51Yn2yFg7ZaX","name":"bash","arguments":{"command":"cd backend && python -c \"\nfrom models import TechniquePageVersion, TechniquePage\n# Check all columns exist\ncols = [c.name for c in TechniquePageVersion.__table__.columns]\nexpected = ['id', 'technique_page_id', 'version_number', 'content_snapshot', 'pipeline_metadata', 'created_at']\nfor e in expected:\n    assert e in cols, f'Missing column: {e}'\n# Check relationship exists on TechniquePage\nassert hasattr(TechniquePage, 'versions'), 'Missing versions relationship on TechniquePage'\nprint('All columns and relationships OK')\nprint('Columns:', cols)\n\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":259,"cacheRead":76080,"cacheWrite":201,"totalTokens":76541,"cost":{"input":0.000005,"output":0.006475000000000001,"cacheRead":0.03804,"cacheWrite":0.00125625,"total":0.04577625}},"stopReason":"toolUse","timestamp":1774854380293}}
{"type":"message","id":"d078e482","parentId":"f182a3cf","timestamp":"2026-03-30T07:06:26.305Z","message":{"role":"toolResult","toolCallId":"toolu_01NoCvhRqh3w51Yn2yFg7ZaX","toolName":"bash","content":[{"type":"text","text":"All columns and relationships OK\nColumns: ['id', 'technique_page_id', 'version_number', 'content_snapshot', 'pipeline_metadata', 'created_at']\n"}],"isError":false,"timestamp":1774854386304}}
{"type":"message","id":"e6e51e02","parentId":"d078e482","timestamp":"2026-03-30T07:06:31.564Z","message":{"role":"assistant","content":[{"type":"text","text":"Let me also verify the snapshot captures all content fields listed in the must-haves:"},{"type":"toolCall","id":"toolu_01QBbu9jA9nJrgaWNvnEAXQA","name":"bash","arguments":{"command":"python3 -c \"\nexpected_fields = ['title', 'slug', 'topic_category', 'topic_tags', 'summary', 'body_sections', 'signal_chains', 'plugins', 'source_quality']\nimport re\nwith open('backend/pipeline/stages.py') as f:\n    content = f.read()\n# Find the snapshot dict\nmatch = re.search(r'snapshot = \\{(.+?)\\}', content, re.DOTALL)\nif match:\n    snapshot_block = match.group(1)\n    for field in expected_fields:\n        if field not in snapshot_block:\n            print(f'MISSING field in snapshot: {field}')\n        else:\n            print(f'OK: {field}')\nelse:\n    print('Could not find snapshot dict')\n\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":267,"cacheRead":76281,"cacheWrite":316,"totalTokens":76865,"cost":{"input":0.000005,"output":0.006675,"cacheRead":0.0381405,"cacheWrite":0.001975,"total":0.0467955}},"stopReason":"toolUse","timestamp":1774854386304}}
{"type":"message","id":"21b29354","parentId":"e6e51e02","timestamp":"2026-03-30T07:06:31.598Z","message":{"role":"toolResult","toolCallId":"toolu_01QBbu9jA9nJrgaWNvnEAXQA","toolName":"bash","content":[{"type":"text","text":"OK: title\nOK: slug\nOK: topic_category\nOK: topic_tags\nOK: summary\nOK: body_sections\nOK: signal_chains\nOK: plugins\nOK: source_quality\n"}],"isError":false,"timestamp":1774854391594}}
{"type":"message","id":"acef54af","parentId":"21b29354","timestamp":"2026-03-30T07:06:37.388Z","message":{"role":"assistant","content":[{"type":"text","text":"All 9 content fields are captured in the snapshot. Now let me read the task summary template and write the summary."},{"type":"toolCall","id":"toolu_01Ti6i5TZL26QgyvwszTZDvN","name":"read","arguments":{"path":"~/.gsd/agent/extensions/gsd/templates/task-summary.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":95,"cacheRead":76597,"cacheWrite":325,"totalTokens":77018,"cost":{"input":0.000005,"output":0.002375,"cacheRead":0.0382985,"cacheWrite":0.00203125,"total":0.04270975}},"stopReason":"toolUse","timestamp":1774854391597}}
{"type":"message","id":"51d06981","parentId":"acef54af","timestamp":"2026-03-30T07:06:37.392Z","message":{"role":"toolResult","toolCallId":"toolu_01Ti6i5TZL26QgyvwszTZDvN","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":1774854397390}}
{"type":"message","id":"8ca80722","parentId":"51d06981","timestamp":"2026-03-30T07:07:03.319Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01Yb6mWTTiWwnxj4cQg444pm","name":"write","arguments":{"content":"---\nid: T01\nparent: S04\nmilestone: M004\nprovides:\n  - TechniquePageVersion SQLAlchemy model with UUID PK, FK, JSONB snapshot\n  - Alembic migration 002 for technique_page_versions table\n  - _capture_pipeline_metadata() helper for prompt hashes and model config\n  - Stage 5 snapshot-before-overwrite hook (best-effort versioning)\nkey_files:\n  - backend/models.py\n  - alembic/versions/002_technique_page_versions.py\n  - backend/pipeline/stages.py\nkey_decisions:\n  - Version snapshot is best-effort — INSERT failure logs ERROR but does not block page update\n  - source_quality enum is stored as its string value in the snapshot dict for JSON serialization\n  - Composite unique index on (technique_page_id, version_number) enforces version ordering at DB level\npatterns_established:\n  - Pipeline metadata capture pattern — hash prompt files + read model config for reproducibility tracking\n  - Pre-mutation snapshot pattern — capture content before overwrite in upsert flows\nobservability_surfaces:\n  - INFO log when version snapshot created (includes version_number and page slug)\n  - ERROR log if snapshot INSERT fails (includes exception details)\n  - SQL queryable: SELECT * FROM technique_page_versions ORDER BY created_at DESC LIMIT 5\nduration: 12min\nverification_result: passed\ncompleted_at: 2026-03-30\nblocker_discovered: false\n---\n\n# T01: Add TechniquePageVersion model, migration, and stage 5 snapshot hook\n\n**Added TechniquePageVersion model, Alembic migration 002, pipeline metadata capture, and pre-overwrite snapshot hook in stage 5 synthesis**\n\n## What Happened\n\nAdded the `TechniquePageVersion` model to `backend/models.py` with UUID PK, FK to technique_pages (CASCADE delete), version_number, content_snapshot (JSONB), pipeline_metadata (JSONB), and created_at. Added a `versions` relationship on `TechniquePage` ordered by version_number.\n\nCreated Alembic migration `002_technique_page_versions.py` following the exact pattern of 001_initial.py — same revision ID format, imports, and upgrade/downgrade structure. The migration creates the table with a unique composite index on `(technique_page_id, version_number)`.\n\nAdded `_capture_pipeline_metadata()` helper in `backend/pipeline/stages.py` that reads all 4 prompt template files, hashes their contents with SHA-256, and collects model names and modality settings from config. Missing files are handled gracefully with a WARNING log and empty hash string.\n\nModified `stage5_synthesis` to snapshot existing page content BEFORE any attribute mutations in the `if existing:` upsert block. The snapshot captures all 9 content fields (title, slug, topic_category, topic_tags, summary, body_sections, signal_chains, plugins, source_quality). Version number is auto-incremented by counting existing versions for the page. The snapshot is best-effort — failures log ERROR but don't prevent the page update.\n\n## Verification\n\nAll four task verification checks pass:\n\n```\ncd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\" → OK\ntest -f alembic/versions/002_technique_page_versions.py → exists\ngrep -q '_capture_pipeline_metadata' backend/pipeline/stages.py → found\ngrep -q 'TechniquePageVersion' backend/pipeline/stages.py → found\n```\n\nAdditionally verified: all 6 required columns present on TechniquePageVersion.__table__, versions relationship exists on TechniquePage, all 9 content fields present in snapshot dict, snapshot logic executes before attribute mutation (lines 618 vs 655).\n\n## Verification Evidence\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| 1 | `cd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\"` | 0 | ✅ pass | 1s |\n| 2 | `test -f alembic/versions/002_technique_page_versions.py` | 0 | ✅ pass | <1s |\n| 3 | `grep -q '_capture_pipeline_metadata' backend/pipeline/stages.py` | 0 | ✅ pass | <1s |\n| 4 | `grep -q 'TechniquePageVersion' backend/pipeline/stages.py` | 0 | ✅ pass | <1s |\n\n## Diagnostics\n\n- **Version snapshots:** `SELECT v.version_number, v.created_at, v.pipeline_metadata->'models' FROM technique_page_versions v JOIN technique_pages p ON p.id = v.technique_page_id ORDER BY v.created_at DESC LIMIT 10;`\n- **Snapshot creation logs:** `docker logs chrysopedia-worker 2>&1 | grep 'Version snapshot'`\n- **Snapshot failures:** `docker logs chrysopedia-worker 2>&1 | grep 'Failed to create version snapshot'`\n\n## Deviations\n\nNone.\n\n## Known Issues\n\nNone.\n\n## Files Created/Modified\n\n- `backend/models.py` — Added TechniquePageVersion model with UUID PK, FK, JSONB columns; added versions relationship to TechniquePage\n- `alembic/versions/002_technique_page_versions.py` — New migration creating technique_page_versions table with composite unique index\n- `backend/pipeline/stages.py` — Added hashlib import, func import, TechniquePageVersion import, _capture_pipeline_metadata() helper, and snapshot-before-overwrite hook in stage5_synthesis\n","path":".gsd/milestones/M004/slices/S04/tasks/T01-SUMMARY.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":1463,"cacheRead":76922,"cacheWrite":605,"totalTokens":78991,"cost":{"input":0.000005,"output":0.036575,"cacheRead":0.038460999999999995,"cacheWrite":0.0037812500000000003,"total":0.07882225}},"stopReason":"toolUse","timestamp":1774854397391}}
{"type":"message","id":"8c489782","parentId":"8ca80722","timestamp":"2026-03-30T07:07:03.322Z","message":{"role":"toolResult","toolCallId":"toolu_01Yb6mWTTiWwnxj4cQg444pm","toolName":"write","content":[{"type":"text","text":"Successfully wrote 4949 bytes to .gsd/milestones/M004/slices/S04/tasks/T01-SUMMARY.md"}],"isError":false,"timestamp":1774854423321}}
{"type":"message","id":"8a02e9fd","parentId":"8c489782","timestamp":"2026-03-30T07:07:13.927Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01GjoTGLKZ7JattStwRnbPAa","name":"gsd_task_complete","arguments":{"blockerDiscovered":false,"deviations":"None.","keyDecisions":["Version snapshot is best-effort — INSERT failure logs ERROR but does not block page update","source_quality enum stored as string value in snapshot for JSON serialization","Composite unique index on (technique_page_id, version_number) enforces ordering at DB level"],"keyFiles":["backend/models.py","alembic/versions/002_technique_page_versions.py","backend/pipeline/stages.py"],"knownIssues":"None.","milestoneId":"M004","narrative":"Added TechniquePageVersion model to backend/models.py with UUID PK, FK to technique_pages (CASCADE), version_number, content_snapshot (JSONB), pipeline_metadata (JSONB), and created_at. Added versions relationship on TechniquePage. Created Alembic migration 002 with composite unique index on (technique_page_id, version_number). Added _capture_pipeline_metadata() helper that hashes prompt files and collects model/modality config. Modified stage5_synthesis to snapshot all 9 content fields before attribute mutations, with best-effort error handling.","oneLiner":"Added TechniquePageVersion model, Alembic migration 002, pipeline metadata capture, and pre-overwrite snapshot hook in stage 5 synthesis","sliceId":"S04","taskId":"T01","verification":"All four verification checks pass: model import OK, migration file exists, _capture_pipeline_metadata grep found, TechniquePageVersion grep found in stages.py. Additionally verified all 6 columns present on model, all 9 content fields in snapshot dict, and correct ordering of snapshot vs mutation in source.","verificationEvidence":[{"command":"cd backend && python -c \"from models import TechniquePageVersion; print('Model OK')\"","durationMs":1000,"exitCode":0,"verdict":"✅ pass"},{"command":"test -f alembic/versions/002_technique_page_versions.py","durationMs":100,"exitCode":0,"verdict":"✅ pass"},{"command":"grep -q '_capture_pipeline_metadata' backend/pipeline/stages.py","durationMs":100,"exitCode":0,"verdict":"✅ pass"},{"command":"grep -q 'TechniquePageVersion' backend/pipeline/stages.py","durationMs":100,"exitCode":0,"verdict":"✅ pass"}]}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":783,"cacheRead":77527,"cacheWrite":1509,"totalTokens":79820,"cost":{"input":0.000005,"output":0.019575000000000002,"cacheRead":0.0387635,"cacheWrite":0.00943125,"total":0.06777475000000001}},"stopReason":"toolUse","timestamp":1774854423321}}
{"type":"message","id":"5adaecaf","parentId":"8a02e9fd","timestamp":"2026-03-30T07:07:13.948Z","message":{"role":"toolResult","toolCallId":"toolu_01GjoTGLKZ7JattStwRnbPAa","toolName":"gsd_task_complete","content":[{"type":"text","text":"Completed task T01 (S04/M004)"}],"details":{"operation":"complete_task","taskId":"T01","sliceId":"S04","milestoneId":"M004","summaryPath":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S04/tasks/T01-SUMMARY.md"},"isError":false,"timestamp":1774854433946}}
{"type":"message","id":"00a4ba16","parentId":"5adaecaf","timestamp":"2026-03-30T07:07:16.134Z","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":79036,"cacheWrite":818,"totalTokens":79864,"cost":{"input":0.000005,"output":0.00022500000000000002,"cacheRead":0.039518,"cacheWrite":0.0051125,"total":0.0448605}},"stopReason":"stop","timestamp":1774854433947}}
