Correlation has only ever been measured through live AI windows: days of wall time per change, and the 09-20→22 window was invalidated outright by unfunded AI accounts (#169). Recordings are kept regardless of AI, so the traffic to measure against already exists. - internal/replay.py: runs a time range of real calls through the live pipeline code in original order, clock pinned per call, into replay_runs/{run_id}/calls|incidents. Modes: audio (re-transcribe), transcripts (re-extract), reuse (correlation only from a prior run's scenes). Simulates the idle-resolve and orphan-recorrelation sweeps on virtual time. No alerts, summaries, vocab, AI-health alerts or pending terms. One run at a time, <=5000 calls, <=7 days. - firestore.py: ContextVar sandbox redirect for calls/incidents. - clock.py: ContextVar-pinnable now(), used on the correlation path. - feature_flags.py: ContextVar flag override so replay runs with live AI off. - upload.py: scene loop extracted to _extract_and_correlate, shared by the live pipeline and replay so replay measures the code that runs live. - resolved_via on every incident resolve, so a real clear can be told from the idle timeout — live and in replay. - routers/replay.py + /admin Replay tab: estimate, start, compare runs, drill into incidents with audio. Reviewed by drb-correlation-review; its leak and fidelity findings are fixed and covered by tests. c2-core: 456 pass. Frontend typecheck not run (no Node on the authoring box). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
178 lines
7.2 KiB
Python
178 lines
7.2 KiB
Python
import asyncio
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import time as _time
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from contextvars import ContextVar
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from typing import Optional, Any
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import firebase_admin
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from firebase_admin import credentials, firestore as fs
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from google.cloud.firestore_v1.base_query import FieldFilter
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from app.config import settings
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from app.internal.logger import logger
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# Re-exported so callers never need their own `firebase_admin.firestore` import
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# just to delete a field. server-26#96/#114 review: `doc_set(..., merge=True)`
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# merges nested maps by key but can never REMOVE one — writing `{"scenes": {}}`
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# to clear a map is a no-op, not a delete. Use `doc_update(coll, id, {"field":
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# fstore.DELETE_FIELD})` (or doc_set + merge, DELETE_FIELD works under both)
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# whenever a re-extraction/reprocess path needs a stale nested field gone
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# rather than merged over.
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DELETE_FIELD = fs.DELETE_FIELD
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# ---------------------------------------------------------------------------
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# In-memory TTL cache for rarely-changing documents (systems, nodes config)
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# ---------------------------------------------------------------------------
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# Key: "collection/doc_id" → (expires_at_monotonic, data_or_None)
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_doc_cache: dict[str, tuple[float, Optional[dict]]] = {}
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def _init_firebase():
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if firebase_admin._apps:
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return firestore.client()
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if settings.gcp_credentials_path:
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cred = credentials.Certificate(settings.gcp_credentials_path)
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else:
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cred = credentials.ApplicationDefault()
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firebase_admin.initialize_app(cred)
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logger.info("Firebase initialised.")
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_init_firebase()
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db = fs.client(database_id=settings.firestore_database)
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# ---------------------------------------------------------------------------
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# Replay sandbox (app/internal/replay.py)
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# ---------------------------------------------------------------------------
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# While a replay run is executing, every read and write the pipeline makes to
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# `calls` or `incidents` is redirected to that run's own subcollections under
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# replay_runs/{run_id}/, so re-running the pipeline over past traffic can never
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# touch a live call or incident. A subcollection keeps the same collection ID
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# ("calls"/"incidents"), so the composite indexes prod queries depend on apply
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# to it unchanged. Everything else (systems, nodes, config) is read from prod
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# as-is. ContextVar for the same reason as app/internal/clock.py: the redirect
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# follows the replay task and never a concurrent live upload.
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SANDBOXED_COLLECTIONS = frozenset({"calls", "incidents"})
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_sandbox_root: ContextVar[Optional[str]] = ContextVar("drb_fstore_sandbox", default=None)
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def enter_sandbox(root: Optional[str]):
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"""Redirect calls/incidents under `root` (e.g. "replay_runs/<id>") for this context."""
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return _sandbox_root.set(root)
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def exit_sandbox(token) -> None:
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_sandbox_root.reset(token)
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def in_sandbox() -> bool:
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"""True inside a replay run. Anything that writes live state OTHER than
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calls/incidents (AI health alerts, pending-term queues) checks this and
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stands down — the redirect below only covers the two sandboxed collections."""
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return _sandbox_root.get() is not None
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def _path(collection: str) -> str:
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root = _sandbox_root.get()
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if root and collection in SANDBOXED_COLLECTIONS:
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return f"{root}/{collection}"
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return collection
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# ---------------------------------------------------------------------------
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# Thin async wrappers — firebase-admin is synchronous, run in thread executor
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# ---------------------------------------------------------------------------
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async def doc_set(collection: str, doc_id: str, data: dict, merge: bool = True) -> None:
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ref = db.collection(_path(collection)).document(doc_id)
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await asyncio.to_thread(ref.set, data, merge=merge)
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async def doc_get(collection: str, doc_id: str) -> Optional[dict]:
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ref = db.collection(_path(collection)).document(doc_id)
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snap = await asyncio.to_thread(ref.get)
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return snap.to_dict() if snap.exists else None
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async def doc_update(collection: str, doc_id: str, data: dict) -> None:
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ref = db.collection(_path(collection)).document(doc_id)
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await asyncio.to_thread(ref.update, data)
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async def collection_list(collection: str, **filters) -> list[dict]:
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"""
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List all documents in a collection.
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Optional keyword filters: field=value pairs passed as equality where-clauses.
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"""
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def _query():
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ref = db.collection(_path(collection))
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for field, value in filters.items():
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ref = ref.where(filter=FieldFilter(field, "==", value))
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return [doc.to_dict() for doc in ref.stream()]
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return await asyncio.to_thread(_query)
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async def collection_where(
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collection: str,
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conditions: list[tuple[str, str, Any]],
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order_by: Optional[list[tuple[str, str]]] = None,
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limit_to: Optional[int] = None,
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start_after: Optional[dict] = None,
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) -> list[dict]:
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"""
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Query a collection with arbitrary where-clauses.
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conditions: list of (field, op, value) — e.g. [("ended_at", ">=", cutoff_dt)]
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Supports any Firestore operator, including "array_contains" — it's just
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forwarded straight to FieldFilter, so a condition like
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("incident_ids", "array_contains", incident_id) already worked before this
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function grew explicit order_by/limit/cursor params below.
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order_by: list of (field, direction) — direction is "ASCENDING" or
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"DESCENDING" (Firestore's own constants; passed straight through as
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strings so this module doesn't need a google.cloud.firestore_v1.Query
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import). Applied in list order, so multi-field sorts work.
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limit_to: cap the number of documents returned.
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start_after: cursor — a dict of the same field values as the *last*
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document from a previous page's order_by fields (Firestore's
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`Query.start_after()` takes a field-value mapping, not a document
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snapshot, when you're not holding one).
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Added for org_id-scoped queries that also need to be ordered/paginated —
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unscoped equality-only lookups can keep using collection_list().
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"""
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def _query():
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ref = db.collection(_path(collection))
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for field, op, value in conditions:
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ref = ref.where(filter=FieldFilter(field, op, value))
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for field, direction in (order_by or []):
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ref = ref.order_by(field, direction=direction)
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if start_after is not None:
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ref = ref.start_after(start_after)
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if limit_to is not None:
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ref = ref.limit(limit_to)
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return [doc.to_dict() for doc in ref.stream()]
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return await asyncio.to_thread(_query)
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async def doc_delete(collection: str, doc_id: str) -> None:
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ref = db.collection(_path(collection)).document(doc_id)
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await asyncio.to_thread(ref.delete)
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async def doc_get_cached(collection: str, doc_id: str, ttl: float = 300.0) -> Optional[dict]:
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"""
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Like doc_get but backed by a short-lived in-memory TTL cache.
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Use for documents that change rarely (systems config, node assignments).
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Default TTL is 5 minutes — a write will be visible within that window.
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"""
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key = f"{_path(collection)}/{doc_id}"
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now = _time.monotonic()
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entry = _doc_cache.get(key)
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if entry and now < entry[0]:
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return entry[1]
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data = await doc_get(collection, doc_id)
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_doc_cache[key] = (now + ttl, data)
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return data
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