# Project Codex Development Roadmap

## Phase 1: Core Stability & Reliability (Immediate)

Focus: Fixing the "flaky" node connections and ensuring data reliability.

- [ ] Refactor Node MQTT Logic (node_main.py)
  - [ ] Move initial API check-in out of on_connect blocking callback.
  - [ ] Implement mqtt_lifecycle_manager with a 30s heartbeat loop.
  - [ ] Add explicit "Clean Shutdown" signal to the finally block to trigger immediate offline status.
  - [ ] Verify LWT (Last Will and Testament) triggers only on ungraceful crashes.

- [ ] Update C2 Brain Logic (c2_main.py)
  - [ ] Update handle_message to refresh last_seen timestamp on any message type.
  - [ ] Add logic to mark a node as "Unknown/Stale" if last_seen > 90 seconds.

- [ ] Standardize Node Configuration
  - [ ] Add location object (lat, lng, description) to the node's local config.json.
  - [ ] Ensure config.json is sent during the initial MQTT Check-in so the C2 knows where the node is geographically.

## Phase 2: The Metadata Pipeline ("The Sidecar")

Focus: Getting real-time talkgroup data out of OP25 and into the cloud.

- [ ] Create Metadata Sidecar (Edge Node)
  - [ ] Update node_main.py to spawn a subprocess that tails OP25's UDP metadata port or log file.
  - [ ] Parse lines for: Frequency, Talkgroup ID, Alpha Tag, Signal Strength.
  - [ ] Publish payload to topic: nodes/{NODE_ID}/metadata.

- [ ] C2 Metadata Ingestion
  - [ ] Subscribe C2 to nodes/+/metadata.
  - [ ] Write received metadata to a Firestore Subcollection: nodes/{node_id}/history (for historical playback/logs).
  - [ ] Update the current_call field on the main node document (for "Now Playing" UI).

## Phase 3: The Web Command Center (Frontend)

Focus: The User Interface for management and monitoring.

Setup
- [ ] Initialize Next.js 14+ (App Router) project with Tailwind CSS.
- [ ] Configure Firebase Client SDK (Auth + Firestore).

### Page: Fleet Dashboard (/app/dashboard/page.tsx)
- [ ] Component: NodeList: Real-time cards for physical radio nodes (Online/Offline status).
- [ ] Component: SystemLoader: Control panel to push configs to nodes.

### Page: The Live Map (/app/map/page.tsx)

This is the primary intelligence view.
- [ ] Data Source: Subscribe to incidents collection (not just nodes).
- [ ] Layer: Incidents
- [ ] Icons: Dynamic markers based on type (Fire, Police, EMS, Hazard).
- [ ] Status Indication: Pulse animation for "Active"; Static/Dimmed for "Cleared".
- [ ] Filter Controls: "Rolling Window" slider (Active Only <-> Active + Past 30 mins <-> Past 24 hours).
- [ ] Interaction:
  - [ ] Click Icon -> Preview Popup (Type, 1-line summary, active units).
  - [ ] Click "More Info" -> Navigates to Incident Detail Page.

### Page: Incident Detail (/app/incidents/[id]/page.tsx)

- [ ] Component: IncidentHeader: Status (Active/Cleared), Duration, Incident Type.
- [ ] Component: LiveSummary: Streaming text summary of the event so far (generated by LLM).
- [ ] Component: UnitTracker: List of units currently detected on scene.
- [ ] Component: TranscriptFeed:
  - [ ] Filtered list of audio/text clips specifically tagged to this incident_id.
  - [ ] Support multi-system interleaving (e.g., PD and FD audio mixed chronologically).
- [ ] Component: LocationHistory: Mini-map showing the incident location (and breadcrumbs if it was mobile/chase).

## Phase 4: Audio & Discord Distribution

- [ ] Persistent Command Bot (Text Interface)
  - [ ] Create Python bot using discord.py (always online).
  - [ ] Implement C2 Listener: Subscribes to MQTT discord/commands.
  - [ ] Feature: !status -> Queries C2 API for active nodes.
  - [ ] Feature: !join {node_id} -> Spawns/Commands a Voice Bot to join.

- [ ] Voice Streamer Bots (Audio Retransmission)
  - [ ] Create lightweight bot instances specifically for audio piping.
  - [ ] Logic: Join voice channel requested by Command Bot.
  - [ ] Audio: Connect to icecast://central-server/{node_id} using FFmpeg/Opus.
  - [ ] Presence: Update "Playing" status with current Icecast metadata (Talkgroup/Alpha Tag).

## Phase 5: The Intelligence Engine (Backend)

Focus: Transcribing, Classifying, and Aggregating.

- [ ] Intelligence Service (radio-intelligence-engine)
- [ ] Module: Transcriber: Whisper STT on "Call End".
- [ ] Module: Analyzer (LLM):
  - [ ] Extract Incident Type, Location, Units Involved.
  - [ ] Generate 1-sentence summary of the transmission.
- [ ] Module: Incident Aggregator (The "Global Brain"):
  - [ ] Input: New transcript + Location + Time.
  - [ ] Logic: Query active incidents within X miles and Y minutes.
  - [ ] Decision:
    - Match Found: Append transcript to existing incident_id, update summary, update units, extend "Last Updated" time.
    - No Match: Create new Incident document in Firestore.
- [ ] Cross-System Merge: Allow merging transcripts from Node A (Police) and Node B (Fire) into the same Incident if location/context matches.