e26236fdc1
* Extract session pipeline framework, refactor verification, add UsageProcessor skeleton Pluggable framework under services/session_pipeline/ (contract + lib + per-processor runner) so multiple processors can read /data/user_sessions/<key>/*.jsonl on their own cadence with full failure isolation. Verification flow becomes the first plugin; a no-op UsageProcessor reserves the second slot pending a separate brainstorm on extraction logic + storage shape. Schema v28→v29: rename session_extraction_state → session_processor_state with composite PK (processor_name, session_file). Existing rows copied over with processor_name='verification'; legacy table dropped. Migration is idempotent and no-ops the copy step on fresh installs that came up at the new schema. Endpoint: /api/admin/run-verification-detector replaced by parametrized /api/admin/run-session-processor?processor=<name>. Audit action format follows. Scheduler JOBS: verification-detector entry split into session-processor:verification + session-processor:usage. SCHEDULER_VERIFICATION_DETECTOR_INTERVAL retained for operator compatibility (drives both cadence and health-check grace window); SCHEDULER_USAGE_PROCESSOR_INTERVAL added. * Address PR #232 review: scan dead branch + per-processor lock - `SessionProcessorStateRepository.scan_unprocessed_for` dead else: both branches surfaced every jsonl, the SELECT was unused, runner MD5-rehashed every stable session per tick. Replaced with an mtime precheck — stable sessions (mtime <= processed_at) are filtered at scan; modified files still surface for the runner's authoritative `file_hash` invalidation. Naive-local comparison matches the existing health-check idiom (DuckDB TIMESTAMP strips tz on storage). - Per-processor advisory lock around `_run_processor` in `/api/admin/run-session-processor`. Scheduler tick + manual admin POST could otherwise both run, both call create_evidence on overlapping detections, and accumulate duplicate verification_evidence rows (the dedup short-circuit only covers create+contradiction, not evidence per ADR Decision 3). Non-blocking acquire → 409 Conflict on concurrent invocation; release in finally so a runner exception doesn't wedge the processor. Tests: two new scan unit tests (mtime filter + post-mark mtime bump), 409 endpoint test, lock-released-on-exception test. Two existing tests updated for the new "filtered at scan" stat shape (previously asserted skipped == 1, now scanned == 0). * Address PR #232 review #2: parallel scheduler tick + last_run on terminal state Two pre-existing scaffold bugs in services/scheduler/__main__.py amplified by adding more session-pipeline jobs: 1. Serial for-loop over jobs with synchronous httpx.post(timeout=900) — a 10-minute verification run blocked every other job (data-refresh, health-check, usage, corporate-memory) for the whole window. The PR's stated isolation guarantee held inside the runner but broke at the scheduler dispatch layer. 2. last_run advanced only when _call_api returned True. Permanent-failure jobs hot-looped on every tick (30s) instead of cadence (15min). Fix: ThreadPoolExecutor.submit per due job + per-job in_flight set so a long-running job can't be re-launched on subsequent ticks. last_run advances unconditionally in finally; errors still surface via _call_api logging + audit_log on the receiving side. _run_job extracted to module-level for unit testing. New tests: - TestRunJobBookkeeping: advances on success / failure / unhandled raise - TestRunLoopParallelism: in_flight protection prevents duplicate launches across ticks for a single slow job --------- Co-authored-by: Minas Arustamyan <arustamyan.minas@gmail.com>
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
"""UsageProcessor — extracts skill / agent invocation events from Claude Code
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session jsonls.
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NOTE: extraction logic is intentionally not implemented yet. Storage shape
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(DuckDB events table vs. append-only parquet event log), granularity
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(per-invocation row vs. per-session aggregate), and signal sources
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(tool_use blocks only vs. also slash-command markers in user messages) are
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pending a separate brainstorm — see plan
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~/.claude/plans/abundant-leaping-charm.md "Out of scope" section.
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The class exists at this stage so that:
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- The session-pipeline framework can be exercised end-to-end with two
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registered processors, not one (catches single-processor assumptions).
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- The scheduler entry + admin endpoint routing are wired now and won't
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need a follow-up PR to add the second processor's plumbing.
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process_session is a no-op that always reports 0 items extracted. The
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runner still calls mark_processed so the same session isn't scanned again.
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"""
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from __future__ import annotations
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from pathlib import Path
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import duckdb
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from services.session_pipeline.contract import ProcessorResult
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class UsageProcessor:
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name: str = "usage"
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cadence_minutes: int = 10
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def process_session(
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self,
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session_path: Path,
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username: str,
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session_key: str,
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conn: duckdb.DuckDBPyConnection,
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) -> ProcessorResult:
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# TODO: extraction logic — pending brainstorm on signal sources
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# (tool_use.name in {"Skill", "Task"}? slash-command markers?
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# subagent invocations?) and storage (events table? parquet log?
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# aggregates?). For now, return zero so the runner marks the
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# session processed and we don't re-scan it every tick.
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return ProcessorResult(items_count=0)
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