Compare commits
7
Commits
| Author | SHA1 | Date | |
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3c642e2946 | ||
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f0a88d401c | ||
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8eac32caf5 | ||
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6e82ee8579 | ||
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cdc61dcc9d | ||
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032e9bd653 | ||
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8dadbdd977 |
@@ -45,7 +45,10 @@ class Settings(BaseSettings):
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# while correlation behaviour was being tuned against rules-only output.
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# Verify against https://ai.google.dev/gemini-api/docs/models before changing.
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corr_cheap_model: str = "gemini-3.6-flash" # was gemini-2.0-flash (shut down)
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corr_smart_model: str = "gemini-2.5-pro" # was gemini-1.5-pro (shut down)
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# gemini-2.5-pro was closed to new projects by 2026-09 (every tiebreak 404'd
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# in the first replay run, server-26#170); Google lists no stable Pro model,
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# so the smart tier is the newest stable Flash instead.
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corr_smart_model: str = "gemini-3.8-flash" # was gemini-2.5-pro, gemini-1.5-pro
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# Transcript correction (server-26#36). Runs inside transcription, once per
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# transcribed call above MIN_WORDS_FOR_CORRECTION, so it is priced like STT
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# rather than like the correlation tier — cheap model on purpose.
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@@ -224,6 +224,28 @@ def _normalize_unit(unit: str) -> str:
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return key or unit.strip().lower()
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def _is_trackable_unit(unit: str) -> bool:
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"""
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Whether a unit is concrete enough to hold an incident open until it clears.
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Extraction lists everything that sounds like a unit — "Desk", "Central",
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"Division", "sergeant", "unknown", and plate phonetics ("John Henry
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Zebra"). None of those ever transmit a 10-8, so while they sat in
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units_active the all-clear gate below could never pass: in the first
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replay (server-26#170, 09-22 10:00-12:00) 0 of 19 incidents resolved on
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a clear and every one had such a name in units_active. A real radio unit
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ID carries a number ("45-9", "11-Adam 2", "Whitestone 1", "E-14"), so
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only those gate resolution. The others are still kept in `units` and
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still match for correlation.
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"""
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if _TEN_CODE_RE.match((unit or "").strip()):
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return False # "10-8" read back as a unit ID is the status, not a unit
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return any(ch.isdigit() for ch in unit or "")
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_TEN_CODE_RE = re.compile(r"^10[\s-]?\d{1,2}$")
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def _unit_keys(units: Optional[list[str]]) -> set[str]:
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"""Comparison keys for a unit list, empties dropped."""
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return {k for k in (_normalize_unit(u) for u in (units or [])) if k}
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@@ -1910,11 +1932,19 @@ def _apply_unit_clearance(inc: dict, cleared: list[str]) -> tuple[list[str], lis
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"""
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units_active = list(inc.get("units_active") or [])
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units_cleared = list(inc.get("units_cleared") or [])
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for u in cleared:
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if u in units_active:
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units_active.remove(u)
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if u not in units_cleared:
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# Compared by normalised key: the unit that cleared as "11-Adam" is the
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# one that went active as "11 Adam", and exact equality left it active.
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# Only a unit that was actually active here can clear here — a clear from
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# a unit never on this incident says nothing about whether it is over, and
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# counting it let one stray 10-8 close an incident still being worked.
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cleared_keys = _unit_keys(cleared)
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releasing = [u for u in units_active if _normalize_unit(u) in cleared_keys]
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units_active = [u for u in units_active if _normalize_unit(u) not in cleared_keys]
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known_cleared = _unit_keys(units_cleared)
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for u in releasing:
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if _normalize_unit(u) not in known_cleared:
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units_cleared.append(u)
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known_cleared.add(_normalize_unit(u))
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auto_resolved = bool(units_cleared) and not units_active
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return units_active, units_cleared, auto_resolved
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@@ -2009,9 +2039,11 @@ async def _update_incident(
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# units_active = units currently on scene; units_cleared = units back in service
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units_active = list(inc.get("units_active") or [])
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units_cleared = list(inc.get("units_cleared") or [])
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tracked = _unit_keys(units_active) | _unit_keys(units_cleared)
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for u in call_units:
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if u not in units_cleared and u not in units_active:
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if _is_trackable_unit(u) and _normalize_unit(u) not in tracked:
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units_active.append(u)
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tracked.add(_normalize_unit(u))
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inc_with_active_update = {**inc, "units_active": units_active, "units_cleared": units_cleared}
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units_active, units_cleared, _ = _apply_unit_clearance(inc_with_active_update, cleared_units or [])
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@@ -2143,7 +2175,7 @@ async def _create_incident(
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"system_ids": [system_id] if system_id else [],
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"tags": tags + ["auto-generated"],
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"units": call_units,
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"units_active": list(call_units),
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"units_active": [u for u in call_units if _is_trackable_unit(u)],
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"units_cleared": [],
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"vehicles": call_vehicles,
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"srcaddrs": [call_srcaddr] if call_srcaddr else [],
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@@ -247,18 +247,26 @@ async def extract_scenes(
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f"Intelligence: call {call_id} — transcript too short for extraction "
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f"({len(transcript.split())} words), skipping"
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)
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cleared_unit = _short_clearance_unit(transcript)
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try:
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# Severity is still recorded: a five-word acknowledgement is genuinely
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# routine traffic, and downstream code treats a missing severity as
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# "not yet processed" rather than "nothing happened".
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await fstore.doc_set("calls", call_id, {
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updates = {
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"skip_reason": "transcript_too_short",
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"severity": "routine",
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"chatter_classifier_verdict": chatter_is_chatter,
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"chatter_classifier_reason": chatter_reason,
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})
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}
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if cleared_unit:
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updates["units"] = [cleared_unit]
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updates["cleared_units"] = [cleared_unit]
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await fstore.doc_set("calls", call_id, updates)
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except Exception:
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pass
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if cleared_unit:
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logger.info(f"Intelligence: call {call_id} — short clearance from {cleared_unit!r}")
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return [_clearance_scene(transcript, cleared_unit)]
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return []
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try:
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@@ -469,6 +477,72 @@ async def extract_scenes(
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return processed
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# "45-9, I'm clear." / "Vehicle 1, clear." / "Car 12 10-8" — a unit reporting
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# itself back in service is the one signal that ends an incident, and it is
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# almost always five words or fewer, which is exactly the population the
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# too-short skip above keeps away from GPT. In the first replay
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# (server-26#170, 09-22 10:00-12:00 ET) 25 transmissions said 10-8/clear and
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# 2 reached cleared_units. Rule-based on purpose: no model call, and only a
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# unit named BEFORE the status word counts, so "10-8, 10-8." or "CMT clear."
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# (no number) clears nobody rather than guessing.
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_CLEAR_WORD_RE = re.compile(
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r"\b(clear|10-?8|10-?98|back in service|in service|available)\b", re.IGNORECASE
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)
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_TEN_CODE_TOKEN_RE = re.compile(r"^10-?\d{1,2}$")
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_UNIT_PREFIX_WORDS = {"unit", "car", "vehicle", "engine", "ladder", "medic", "rescue", "post", "truck", "squad"}
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# A number after one of these is a place or a time, not a radio unit.
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_NOT_UNIT_PREFIX_WORDS = {"room", "route", "rt", "exit", "pole", "apartment", "apt", "floor",
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"building", "hours", "hour", "block", "lane", "highway", "interstate"}
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# The status word has to END the transmission: "clear the scene", "clear to
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# transport", "available for" are orders or plans, not a unit back in service.
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_TRAILING_OK = {"10-4", "thanks", "thank", "you", "k", "over", "now", "again", "from", "headquarters", "hq",
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"central", "dispatch"}
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def _short_clearance_unit(transcript: str) -> Optional[str]:
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text = (transcript or "").strip()
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if not text or "?" in text:
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return None # "45-9, are you clear?" asks; it doesn't report
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m = _CLEAR_WORD_RE.search(text)
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if not m:
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return None
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before = [t.strip(".,;:!") for t in text[: m.start()].split()]
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before = [t for t in before if t]
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after = [t.strip(".,;:!").lower() for t in text[m.end():].split()]
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if any(t and t not in _TRAILING_OK for t in after):
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return None
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if any(t.lower() in {"not", "is", "are", "negative", "you"} for t in before):
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return None # "not clear yet", "Is 45-9 clear", "you clear"
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for i, tok in enumerate(before[:4]):
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if not any(ch.isdigit() for ch in tok) or _TEN_CODE_TOKEN_RE.match(tok):
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continue
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prev = before[i - 1].lower() if i else ""
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if prev in _NOT_UNIT_PREFIX_WORDS:
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return None
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nxt = before[i + 1] if i + 1 < len(before) else ""
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if nxt.lower() in _NOT_UNIT_PREFIX_WORDS:
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return None # "1400 hours, clear"
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if nxt.isdigit():
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tok = f"{tok}-{nxt}" # "45 9 clear" is unit 45-9, not unit 45
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elif nxt.isalpha() and nxt[0].isupper() and nxt.lower() not in {"i'm", "im", "we're", "copy"}:
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tok = f"{tok} {nxt}" # "11 Adam, clear"
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if prev in _UNIT_PREFIX_WORDS:
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return f"{before[i - 1]} {tok}"
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return tok
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return None
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def _clearance_scene(transcript: str, unit: str) -> dict:
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"""A minimal scene for a rule-parsed clearance: the unit, and nothing that
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could make the incident-creation gate open a new incident for it."""
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return {
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"tags": [], "incident_type": None, "location": None, "location_coords": None,
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"resolved": False, "severity": "routine", "vehicles": [], "units": [unit],
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"cleared_units": [unit], "reassignment": False, "transcript": transcript,
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"transcript_corrected": None, "segment_indices": [], "embedding": None,
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}
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def _geo_dist_km(lat1: float, lon1: float, lat2: float, lon2: float) -> float:
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"""Haversine distance in km between two lat/lon points."""
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R = 6371.0
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@@ -275,6 +275,12 @@ async def decide(call_id: str, ctx: dict) -> Optional[dict]:
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if ctx["is_thin_call"]:
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return None # thin calls have no transcript/units/coords to reason about
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if _is_clearance_only(ctx):
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# "45-9, I'm clear." carries one fact: which unit is done. Only the
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# rules engine's unit match can say which incident that is; an LLM
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# link here would apply the clear to whatever incident it picked.
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return None
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if not ctx["recent"]:
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return None # no incidents to correlate against — rules handles new-only
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@@ -295,6 +301,14 @@ async def decide(call_id: str, ctx: dict) -> Optional[dict]:
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return None
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def _is_clearance_only(ctx: dict) -> bool:
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units = ctx.get("call_units") or []
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cleared = ctx.get("call_cleared") or []
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return bool(cleared) and set(units) <= set(cleared) and not (
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ctx.get("tags") or ctx.get("location") or ctx.get("call_vehicles") or ctx.get("incident_type")
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)
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_dead_models: set[str] = set()
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@@ -140,6 +140,7 @@ def _call_row(c: dict) -> dict:
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"cleared_units": c.get("cleared_units"),
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"location": c.get("location"),
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"skip_reason": c.get("skip_reason"),
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"srcaddr": c.get("srcaddr"),
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"corr_path": [p for p in paths if p] or ([c["corr_path"]] if c.get("corr_path") else []),
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"incident_ids": c.get("incident_ids") or [],
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}
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@@ -174,6 +175,7 @@ async def run_incidents(run_id: str, decoded: dict = Depends(require_admin_token
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"units_active": inc.get("units_active"),
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"units_cleared": inc.get("units_cleared"),
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"talkgroup_ids": inc.get("talkgroup_ids"),
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"srcaddrs": inc.get("srcaddrs"),
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"calls": rows,
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})
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orphans = sorted((r for r in by_id.values() if not r["incident_ids"]),
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@@ -0,0 +1,68 @@
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"""
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Dispatch→10-8 lifecycle, as measured by the first replay (server-26#170):
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0 of 19 incidents resolved on a clear although 25 transmissions said one.
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Three independent breaks, each pinned here.
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"""
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from app.internal import incident_correlator as ic
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from app.internal.intelligence import _clearance_scene, _short_clearance_unit
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def test_short_clearance_names_the_unit_that_cleared():
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assert _short_clearance_unit("45-9, I'm clear.") == "45-9"
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assert _short_clearance_unit("Vehicle 1, clear.") == "Vehicle 1"
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assert _short_clearance_unit("11 Adam, clear") == "11 Adam"
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assert _short_clearance_unit("Car 12 10-8") == "Car 12"
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assert _short_clearance_unit("45 9 clear") == "45-9"
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assert _short_clearance_unit("Warrant 4, clear from the jail") is None or True # >5 words: GPT's job
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assert _short_clearance_unit("45-9 clear, thank you") == "45-9"
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def test_short_clearance_never_guesses():
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for t in ("10-8, 10-8.", "CMT clear.", "10-8, I'm back now. Clear.",
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"10-8, thank you.", "Show us 10-8, post 4.", "7, Charlie Central.", "10-4.",
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# review findings: questions, negations, orders, places, times
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"45-9, are you clear?", "Is 45-9 clear", "45-9, not clear yet.",
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"Engine 5 not available.", "45-9, clear the scene.", "Medic 3, clear to transport.",
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"Room 2 clear.", "Route 9 is clear.", "1400 hours, clear.", "you clear 45-9"):
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assert _short_clearance_unit(t) is None, t
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def test_clearance_scene_cannot_open_an_incident():
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scene = _clearance_scene("45-9, I'm clear.", "45-9")
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ctx = {"call_vehicles": scene["vehicles"], "coords": scene["location_coords"], "tags": scene["tags"]}
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assert not ic.has_event_substance(ctx)
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assert scene["severity"] == "routine" and scene["incident_type"] is None
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def test_clearance_matches_a_differently_spoken_unit():
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inc = {"units_active": ["11 Adam", "45-9"], "units_cleared": []}
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active, cleared, resolved = ic._apply_unit_clearance(inc, ["11-Adam"])
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assert active == ["45-9"]
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active, cleared, resolved = ic._apply_unit_clearance(
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{"units_active": active, "units_cleared": cleared}, ["45 9"])
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assert active == [] and resolved
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def test_a_unit_never_on_the_incident_cannot_close_it():
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inc = {"units_active": ["45-9"], "units_cleared": []}
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active, cleared, resolved = ic._apply_unit_clearance(inc, ["22-1"])
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assert active == ["45-9"] and cleared == [] and not resolved
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# an incident with no numbered unit ever active never resolves on a clear
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active, cleared, resolved = ic._apply_unit_clearance({"units_active": [], "units_cleared": []}, ["22-1"])
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assert not resolved
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def test_clearance_only_call_skips_the_llm():
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from app.internal import llm_correlator
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ctx = {"call_units": ["45-9"], "call_cleared": ["45-9"], "tags": [], "location": None,
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"call_vehicles": [], "incident_type": None}
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assert llm_correlator._is_clearance_only(ctx)
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assert not llm_correlator._is_clearance_only({**ctx, "tags": ["mva"]})
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assert not llm_correlator._is_clearance_only({**ctx, "call_cleared": []})
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def test_only_numbered_units_hold_an_incident_open():
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for junk in ("Desk", "Central", "Division", "sergeant", "unknown", "John", "Zebra", "10-8", "10 4"):
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assert not ic._is_trackable_unit(junk), junk
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for real in ("45-9", "11-Adam", "Whitestone 1", "E-14", "Highway 3-4", "7"):
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assert ic._is_trackable_unit(real), real
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@@ -67,7 +67,10 @@ def test_clearing_a_unit_not_tracked_as_active_is_a_noop_for_active_list():
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inc = _incident(units_active=["6-7"], units_cleared=[])
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active, cleared, resolved = _apply_unit_clearance(inc, ["ghost-unit"])
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assert active == ["6-7"]
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assert cleared == ["ghost-unit"]
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# A unit never active on this incident is not recorded as cleared here
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# either (server-26#170 replay review): its 10-8 says nothing about this
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# incident, and recording it let the all-clear gate pass on a stray clear.
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assert cleared == []
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assert resolved is False
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Reference in New Issue
Block a user