Gmer4Lfe
6623d1e776
Codebase-wide audit pass: fixed real bugs (SSH hangs missing BatchMode, local-outside-function no-ops, variable name collisions, a truncated ratio calc, wrong state-dir path, DARK vs NO_INTERNET drift, and more), then pulled logic that was duplicated across multiple scripts — arr cleanup safety gates, docker restart ordering, container maintenance stop/restart, watchdog state-file helpers, partnership role resolution, cert expiry checks, remote node discovery, and TMDB discovery scoring — into common.sh so each now has a single implementation.
128 lines
4.9 KiB
Bash
Executable File
128 lines
4.9 KiB
Bash
Executable File
#!/bin/bash
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# ==============================================================================================
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# ================================= Decision Engine ============================================
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# ==============================================================================================
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#
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# PURPOSE
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# ─────────────────────────────────────────────────────────────────────────────
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# Behavior-driven scoring kernel for media automation. Sourced by consumer
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# scripts — not run directly. Evaluates candidates, applies weighted scoring,
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# temporal decay, and deduplication, then returns a verdict.
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#
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# Does NOT download media, search indexers, or manage applications. Has no
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# side effects — no file writes, no API calls, no deletions.
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#
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# Currently paired with: Arrs_Stack/playback_aware_lidarr_discovery.sh
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#
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# ==============================================================================================
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# DESIGN PRINCIPLES
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# ==============================================================================================
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#
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# Domain-Agnostic Core
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# The engine itself has no knowledge of music vs TV vs movies. Consumers
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# define thresholds, weights, and strictness profiles — the engine just
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# scores and decides. This prevents cross-domain bias pollution: music
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# strictness cannot contaminate TV intake logic.
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#
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# Lidarr consumers → highly selective, quality-first discovery
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# Sonarr consumers → balanced, family-aware episodic intake
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# Radarr consumers → broader flexibility with intelligent filtering
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#
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# Temporal Decay
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# Old behavioral signals lose influence over time (one decay unit per 30
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# days). Prevents permanent genre lock-in, historical bias accumulation,
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# and dead-user score dominance.
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#
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# Consumer Owns the Decision
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# The engine returns ACCEPT/REJECT/SCORE. What happens next is entirely
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# the consumer's concern — the engine never acts on its own verdict.
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#
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# ==============================================================================================
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# FUNCTIONS
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# ==============================================================================================
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#
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# score_candidate user_score popularity_score recency_score quality_score
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# Returns TOTAL_SCORE (integer sum). Consumer defines actual weight values.
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#
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# evaluate_threshold score minimum
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# Returns 0 (pass) or 1 (fail). Used as: if evaluate_threshold ...
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#
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# apply_temporal_decay score age_days
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# Returns adjusted score. Subtracts (age_days / 30), floor at 0.
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#
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# is_duplicate_candidate candidate history_file
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# Returns 0 (duplicate found in history_file) or 1 (not found).
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#
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# make_decision score threshold
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# Returns "ACCEPT" or "REJECT". Calls evaluate_threshold internally.
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#
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# ==============================================================================================
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# ── score_candidate ───────────────────────────────────────────────────────────
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score_candidate() {
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local user_score="${1:-0}"
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local popularity_score="${2:-0}"
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local recency_score="${3:-0}"
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local quality_score="${4:-0}"
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local TOTAL_SCORE
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TOTAL_SCORE=$(( \
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user_score + \
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popularity_score + \
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recency_score + \
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quality_score \
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))
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echo "$TOTAL_SCORE"
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}
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# ── evaluate_threshold ───────────────────────────────────────────────────────
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evaluate_threshold() {
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local score="$1"
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local minimum="$2"
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if (( score >= minimum )); then
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return 0
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fi
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return 1
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}
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# ── apply_temporal_decay ─────────────────────────────────────────────────────
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apply_temporal_decay() {
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local score="$1"
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local age_days="$2"
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local decay=$(( age_days / 30 ))
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local adjusted=$(( score - decay ))
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(( adjusted < 0 )) && adjusted=0
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echo "$adjusted"
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}
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# ── is_duplicate_candidate ───────────────────────────────────────────────────
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is_duplicate_candidate() {
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local candidate="$1"
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local history_file="$2"
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grep -qi "^${candidate}$" "$history_file" 2>/dev/null
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}
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# ── make_decision ─────────────────────────────────────────────────────────────
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make_decision() {
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local score="$1"
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local threshold="$2"
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if evaluate_threshold "$score" "$threshold"; then
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echo "ACCEPT"
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else
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echo "REJECT"
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fi
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} |