mirror of
https://github.com/Sea-Haven-Industries/open-swe.git
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Plan step C4 (docs/upstream-sync/domain-reorg/reorg-build-plan.md, approved
decisions 1-2): split the 2,590-line agent/webapp.py monolith into
agent/webhooks/common.py (shared verify/dispatch helpers), agent/api/app.py
(composition), agent/api/health.py (/health + /webhooks/run-complete), and
per-source {github,linear,slack,jira,confluence}_routes.py. Atlassian
Connect lifecycle + descriptor routes (/connect/*) fold into
confluence_routes.py; webapp.py becomes the upstream-shaped compatibility
shim (from .api.app import app). langgraph.json http.app stays
agent.webapp:app via the shim.
Fork content, upstream layout: linear/slack route files verified
content-identical to upstream 8356eb34 and taken verbatim; github_routes is
upstream + the fork's CI auto-fix trigger wiring; jira/confluence routes are
fork-only, transformed to the same common.X / service.X module-attribute
style. All signature verification (GitHub HMAC, Slack, Linear
timestamp-freshness, verify_jira_secret + opt-in HMAC/timestamp/IP
allowlist, Connect JWT/qsh), token-attribution gating, TID-COLLIDE-01 repo
binding, _is_repo_auto_review_enabled gates, and public-repo org gate move
unchanged.
Handlers rewired from webapp.X to common.X; test monkeypatch sites across
26 files + conftest.py + e2e/harness.py retargeted to
webhook_common/handler/route modules per upstream's pattern. Residual
agent.webapp importers: only the shim, langgraph.json http.app, Makefile
uvicorn target, and docs (doc-path updates land in C7).
Gates: ruff check + format, pytest --co, full unit (1637 passed), full
Playwright E2E vs real langgraph dev (9/9), residual-importer sweep.
246 lines
8.7 KiB
Python
246 lines
8.7 KiB
Python
"""Kick off and sync per-repo review style analysis runs."""
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from __future__ import annotations
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import logging
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import os
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from typing import Any
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from langgraph_sdk import get_client
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from ..review.style_collector import (
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collect_review_samples,
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format_samples_for_analyzer,
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generate_review_style_thread_id,
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)
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from ..utils.analyzer_skills import build_skill_files
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from .review_styles import (
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get_review_style,
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has_saved_prompt,
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mark_analysis_failed,
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mark_analysis_running,
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reconcile_running_status,
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update_review_style,
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)
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logger = logging.getLogger(__name__)
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_ASSISTANT_ID = "analyzer"
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def _client():
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"""LangGraph SDK client for the current deployment (same resolution as webhook common)."""
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url = os.environ.get("LANGGRAPH_URL") or os.environ.get("LANGGRAPH_URL_PROD")
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if url:
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return get_client(url=url)
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return get_client()
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def build_continual_run_input(full_name: str) -> dict[str, Any]:
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"""Run input for a continual-learning analyzer run (shared with the cron)."""
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return {
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"messages": [
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{
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"role": "user",
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"content": (
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f"Refine the review-style prompt for `{full_name}` using this "
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"reviewer's recorded finding outcomes. Follow the continual-learning "
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"skill, then save the refined prompt."
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),
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}
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],
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"files": build_skill_files(),
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}
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def build_continual_run_configurable(full_name: str) -> dict[str, Any]:
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"""Configurable for a continual-learning analyzer run (shared with the cron).
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Includes an explicit ``thread_id`` so the run is anchored to the repo's
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deterministic analyzer thread. The nightly cron is threadless, so without
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this ``get_analyzer`` would early-return an empty agent (no thread_id) and
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the run would no-op. Reusing the deterministic id keys the sandbox + thread
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metadata to the repo; the threadless run carries no message history, so it
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does not accumulate across nights.
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"""
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owner, repo = full_name.split("/", 1)
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return {
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"thread_id": generate_review_style_thread_id(owner, repo),
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"review_style_full_name": full_name,
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"analyzer_mode": "continual",
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}
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async def start_bootstrap_analysis(
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full_name: str,
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*,
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github_token: str,
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created_by: str,
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) -> dict[str, Any]:
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"""Collect samples, persist metadata, and start a bootstrap analyzer run."""
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owner, repo = full_name.split("/", 1)
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try:
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samples = await collect_review_samples(github_token, owner, repo)
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except Exception:
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logger.exception("Failed to collect review samples for %s", full_name)
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await mark_analysis_failed(full_name, "sample collection failed")
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record = await get_review_style(full_name)
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return record or {
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"full_name": full_name,
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"status": "failed",
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"error": "Sample collection failed. Please retry later.",
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}
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samples_text = format_samples_for_analyzer(samples)
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thread_id = generate_review_style_thread_id(owner, repo)
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client = _client()
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configurable: dict[str, Any] = {
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"thread_id": thread_id,
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"review_style_full_name": full_name,
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"review_style_github_token": github_token,
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"review_style_samples_text": samples_text,
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"review_style_top_reviewers": samples.top_reviewers,
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"review_style_prs_sampled": samples.prs_scanned,
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"review_style_reviews_sampled": samples.reviews_scanned,
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"analyzer_mode": "bootstrap",
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}
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if not samples.samples:
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logger.info(
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"No pre-collected samples for %s (%s merged PRs scanned); analyzer will fetch via API",
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full_name,
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samples.prs_scanned,
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)
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await mark_analysis_running(
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full_name,
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thread_id=thread_id,
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run_id=None,
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top_reviewers=samples.top_reviewers,
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prs_sampled=samples.prs_scanned,
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reviews_sampled=samples.reviews_scanned,
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)
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try:
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run = await client.runs.create(
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thread_id,
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_ASSISTANT_ID,
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input={
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"messages": [
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{
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"role": "user",
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"content": (
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f"Analyze review style for `{full_name}`. Follow the "
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"bootstrap-repo-analysis skill: browse merged PR review feedback "
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"with `GH_TOKEN=dummy gh` until you have enough human examples, "
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"then save the repository-specific prompt."
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),
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}
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],
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"files": build_skill_files(),
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},
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config={"configurable": configurable},
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if_not_exists="create",
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)
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run_id = run.get("run_id") if isinstance(run, dict) else getattr(run, "run_id", None)
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record = await update_review_style(
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full_name,
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{"analysis_run_id": run_id, "created_by": created_by},
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)
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return record
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except Exception:
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logger.exception("Failed to start review style analyzer for %s", full_name)
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await mark_analysis_failed(full_name, "run start failed")
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record = await get_review_style(full_name)
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return record or {
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"full_name": full_name,
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"status": "failed",
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"error": "Failed to start analysis. Please retry later.",
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}
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async def start_continual_run(
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full_name: str,
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*,
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created_by: str = "manual",
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) -> dict[str, Any]:
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"""Start an immediate continual-learning run (outcome-driven refinement)."""
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configurable = build_continual_run_configurable(full_name)
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thread_id = configurable["thread_id"]
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try:
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run = await _client().runs.create(
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thread_id,
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_ASSISTANT_ID,
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input=build_continual_run_input(full_name),
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config={"configurable": configurable},
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if_not_exists="create",
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)
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run_id = run.get("run_id") if isinstance(run, dict) else getattr(run, "run_id", None)
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return await update_review_style(
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full_name,
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{"analysis_run_id": run_id, "created_by": created_by},
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)
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except Exception:
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logger.exception("Failed to start continual analyzer run for %s", full_name)
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record = await get_review_style(full_name)
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return record or {"full_name": full_name, "status": "failed", "error": "run start failed"}
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async def sync_review_style_run_status(full_name: str) -> dict[str, Any]:
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"""Refresh store status from the latest analyzer run when still running."""
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record = await get_review_style(full_name)
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if not record or record.get("status") != "running":
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return record or {}
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thread_id = record.get("analysis_thread_id")
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run_id = record.get("analysis_run_id")
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if not isinstance(thread_id, str) or not thread_id:
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return record
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client = _client()
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run_status: str | None = None
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run_missing = False
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try:
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if isinstance(run_id, str) and run_id:
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run = await client.runs.get(thread_id, run_id)
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else:
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runs = await client.runs.list(thread_id, limit=1)
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items = runs if isinstance(runs, list) else (runs.get("runs") or [])
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run = items[0] if items else None
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if not run:
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run_missing = True
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else:
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raw = run.get("status") if isinstance(run, dict) else getattr(run, "status", None)
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run_status = raw.lower() if isinstance(raw, str) else None
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except Exception:
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logger.debug("Could not sync run status for %s", full_name, exc_info=True)
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return record
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return await reconcile_running_status(
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full_name, record, run_status=run_status, run_missing=run_missing
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)
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async def cancel_review_style_analysis(full_name: str) -> dict[str, Any]:
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"""Stop an in-flight analyzer run and clear stale ``running`` status."""
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record = await get_review_style(full_name)
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if not record:
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return {}
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if record.get("status") != "running":
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return record
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thread_id = record.get("analysis_thread_id")
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run_id = record.get("analysis_run_id")
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if isinstance(thread_id, str) and isinstance(run_id, str) and thread_id and run_id:
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try:
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await _client().runs.cancel(thread_id, run_id, wait=False)
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except Exception:
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logger.debug("Could not cancel review style run for %s", full_name, exc_info=True)
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if has_saved_prompt(record):
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return await update_review_style(full_name, {"status": "completed", "error": None})
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return await update_review_style(
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full_name,
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{"status": "idle", "error": None, "analysis_run_id": None},
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)
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