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Converts ObservationModel (Pydantic) → flat numpy float32 vector.
All downstream RL code depends on OBS_DIM being stable.
Feature layout (total = OBS_DIM = 84):
[0 : 63) — per-service block (7 services × 9 features each)
[63 : 84) — global block (21 scalar features)
"""
from __future__ import annotations
import numpy as np
from typing import List
from app.models import (
ObservationModel,
ServiceType,
StageType,
PriorityMode,
ActionType,
)
# ── Canonical orderings (must never change across the codebase) ──────────────
SERVICES: List[ServiceType] = [
ServiceType.PASSPORT,
ServiceType.DRIVING_LICENSE,
ServiceType.GST_REGISTRATION,
ServiceType.INCOME_CERTIFICATE,
ServiceType.CASTE_CERTIFICATE,
ServiceType.BIRTH_CERTIFICATE,
ServiceType.LAND_REGISTRATION,
] # 7 legacy RL services for checkpoint compatibility
STAGES: List[StageType] = list(StageType) # 5 stages
PRIORITY_MODES: List[PriorityMode] = list(PriorityMode) # 4 modes
ACTION_TYPES: List[ActionType] = list(ActionType) # 6 types
SERVICE_IDX = {s: i for i, s in enumerate(SERVICES)}
STAGE_IDX = {s: i for i, s in enumerate(STAGES)}
PM_IDX = {m: i for i, m in enumerate(PRIORITY_MODES)}
AT_IDX = {a: i for i, a in enumerate(ACTION_TYPES)}
# ── Dimension constants ───────────────────────────────────────────────────────
N_SERVICES = len(SERVICES) # 7
N_STAGES = len(STAGES) # 5
N_PRIORITY_MODES = len(PRIORITY_MODES) # 4
N_ACTION_TYPES = len(ACTION_TYPES) # 6
PER_SERVICE_DIM = 4 + N_STAGES # queue_len, avg_wait, urgent, missing + 5 stage fracs = 9
GLOBAL_DIM = (
1 # day_ratio
+ 1 # total_backlog_normalized
+ 1 # total_completed_normalized
+ 1 # total_sla_breaches_normalized
+ 1 # fairness_gap
+ 1 # escalation_budget_ratio
+ 1 # last_action_valid
+ N_ACTION_TYPES # last_action_type one-hot (6)
+ N_PRIORITY_MODES # current_priority_mode one-hot (4)
+ 1 # idle_officer_ratio
+ 1 # urgent_backlog_ratio
+ 1 # officer_utilization
+ 1 # backlog_per_officer
) # = 21
OBS_DIM = N_SERVICES * PER_SERVICE_DIM + GLOBAL_DIM # 63 + 21 = 84
# ── Normalisation caps (avoid div-by-zero, keep values in [0,1]) ─────────────
_MAX_QUEUE = 200.0
_MAX_WAIT = 30.0
_MAX_URGENT = 50.0
_MAX_MISSING = 50.0
_MAX_BACKLOG = 500.0
_MAX_COMPLETED = 500.0
_MAX_SLA = 100.0
_MAX_ESC_BUDGET = 20.0
_MAX_OFFICERS = 50.0
class FeatureBuilder:
"""
Stateless transformer: ObservationModel → np.ndarray[float32, OBS_DIM].
Usage:
fb = FeatureBuilder()
vec = fb.build(obs, current_priority_mode="urgent_first",
last_action_type="advance_time")
"""
def build(
self,
obs: ObservationModel,
current_priority_mode: str = "balanced",
last_action_type: str = "advance_time",
) -> np.ndarray:
features = np.zeros(OBS_DIM, dtype=np.float32)
offset = 0
snap_dict = {
snap.service_type: snap
for snap in (obs.queue_snapshots.values() if isinstance(obs.queue_snapshots, dict) else obs.queue_snapshots)
}
# ── Per-service block ─────────────────────────────────────────────
for svc in SERVICES:
snap = snap_dict.get(svc)
if snap is None:
offset += PER_SERVICE_DIM
continue
total_in_svc = max(getattr(snap, "total_pending", getattr(snap, "active_cases", 0)), 1)
features[offset + 0] = getattr(snap, "total_pending", getattr(snap, "active_cases", 0)) / _MAX_QUEUE
features[offset + 1] = getattr(snap, "avg_age_days", getattr(snap, "avg_waiting_days", getattr(snap, "oldest_case_age_days", 0))) / _MAX_WAIT
features[offset + 2] = getattr(snap, "urgent_cases", getattr(snap, "urgent_pending", 0)) / _MAX_URGENT
features[offset + 3] = getattr(snap, "blocked_missing_docs", getattr(snap, "missing_docs_cases", 0)) / _MAX_MISSING
# Stage distribution as fractions
stage_counts = getattr(snap, "stage_counts", getattr(snap, "public_stage_counts", {})) or {}
for stg in STAGES:
count = stage_counts.get(stg, 0)
features[offset + 4 + STAGE_IDX[stg]] = count / total_in_svc
offset += PER_SERVICE_DIM
# ── Global block ──────────────────────────────────────────────────
day_ratio = obs.day / max(obs.max_days, 1)
features[offset + 0] = day_ratio
features[offset + 1] = obs.total_backlog / _MAX_BACKLOG
features[offset + 2] = obs.total_completed / _MAX_COMPLETED
features[offset + 3] = obs.total_sla_breaches / _MAX_SLA
features[offset + 4] = float(getattr(obs, "fairness_gap", getattr(obs, "fairness_index", 0.0)) or 0.0)
features[offset + 5] = obs.escalation_budget_remaining / _MAX_ESC_BUDGET
features[offset + 6] = float(obs.last_action_valid)
offset += 7
# Last action type one-hot
at_vec = np.zeros(N_ACTION_TYPES, dtype=np.float32)
try:
at_vec[AT_IDX[ActionType(last_action_type)]] = 1.0
except (ValueError, KeyError):
pass
features[offset: offset + N_ACTION_TYPES] = at_vec
offset += N_ACTION_TYPES
# Current priority mode one-hot
pm_vec = np.zeros(N_PRIORITY_MODES, dtype=np.float32)
try:
pm_vec[PM_IDX[PriorityMode(current_priority_mode)]] = 1.0
except (ValueError, KeyError):
pass
features[offset: offset + N_PRIORITY_MODES] = pm_vec
offset += N_PRIORITY_MODES
# Officer-derived scalars
pool = obs.officer_pool
total_officers = max(getattr(pool, "total_officers", 1) if not callable(getattr(pool, "total_officers", None)) else pool.total_officers(), 1)
idle_officers = getattr(pool, "idle_officers", getattr(pool, "reserve_officers", 0))
idle_ratio = idle_officers / total_officers
total_backlog_safe = max(obs.total_backlog, 1)
urgent_total = sum(
getattr(snap_dict[s], "urgent_cases", getattr(snap_dict[s], "urgent_pending", 0))
for s in SERVICES
if s in snap_dict
)
urgent_ratio = urgent_total / total_backlog_safe
utilization = (total_officers - idle_officers) / total_officers
backlog_per_off = obs.total_backlog / total_officers
features[offset + 0] = float(np.clip(idle_ratio, 0.0, 1.0))
features[offset + 1] = float(np.clip(urgent_ratio, 0.0, 1.0))
features[offset + 2] = float(np.clip(utilization, 0.0, 1.0))
features[offset + 3] = float(np.clip(backlog_per_off / _MAX_OFFICERS, 0.0, 1.0))
assert offset + 4 == OBS_DIM, f"OBS_DIM mismatch: {offset + 4} != {OBS_DIM}"
return features
# -- Action space layout (N_ACTIONS = 28) -------------------------------------
#
# 0 - 3 : set_priority_mode (4 modes in PRIORITY_MODES order)
# 4 - 10 : request_missing_documents per service (7)
# 11 - 17 : escalate_service per service (7)
# 18 : advance_time
# 19 - 25 : reallocate_officers from source service -> most loaded other service
# 26 : assign_capacity +1 to most-loaded service
# 27 : assign_capacity +1 to most-urgent service
N_ACTIONS = 4 + N_SERVICES + N_SERVICES + 1 + N_SERVICES + 2 # = 28
ACTION_DECODE_TABLE = {}
idx = 0
for m in PRIORITY_MODES:
ACTION_DECODE_TABLE[idx] = ("set_priority_mode", None, m.value, None)
idx += 1
for s in SERVICES:
ACTION_DECODE_TABLE[idx] = ("request_missing_documents", s.value, None, None)
idx += 1
for s in SERVICES:
ACTION_DECODE_TABLE[idx] = ("escalate_service", s.value, None, None)
idx += 1
ACTION_DECODE_TABLE[idx] = ("advance_time", None, None, None); idx += 1
for s in SERVICES:
ACTION_DECODE_TABLE[idx] = ("reallocate_officers", s.value, "most_loaded_other", 1)
idx += 1
ACTION_DECODE_TABLE[idx] = ("assign_capacity", "__most_loaded__", None, 1); idx += 1
ACTION_DECODE_TABLE[idx] = ("assign_capacity", "__most_urgent__", None, 1); idx += 1
assert len(ACTION_DECODE_TABLE) == N_ACTIONS
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