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Matt Johnson (via Claude) 89640f624d fix(v0.7-fire-tracker-4-revised): rip ?status; LLM DM 7-path verification 3 of 7 pass (NOT verified)
Matt review caught a scope error: ?status was a hypothetical sketch
in the design doc ("a node could ping ?status cache peak") treated as
authorization without asking. Ripping the structured-command path
entirely. The LLM DM path with env_reporter injection is the natural-
language interface; ?status was redundant infrastructure parallel to
the path the design depends on.

What landed:
- router.py: _maybe_rewrite_status_query + _lookup_fire_fuzzy +
  _build_fire_status_context removed. route() restored to:
  bang -> IGNORE-empty -> LLM with verbatim query.
- tests/test_fire_tracker_phase4.py: 5 ?status tests removed; replaced
  with two regression guards:
    test_natural_language_fire_question_routes_to_llm -- "how's the
      cache peak fire?" returns RouteType.LLM with the verbatim query
      (no in-router rewriting).
    test_status_helpers_removed_from_router -- hard-block on
      _maybe_rewrite_status_query / _lookup_fire_fuzzy / "?status"
      appearing anywhere in router.py source. If anyone adds a
      structured-command path for fires, this test fails and the
      author has to talk to Matt first.
- 56 passed in 3.80s across phase1+phase2+phase3+phase4+or-arch+
  include-roundtrip.

What stays (NOT ripped):
- Daily fire digest -- scheduled broadcaster, not a command. Its 4
  adapter_config rows (fires.digest_enabled / digest_schedule /
  digest_timezone / digest_max_chars) stay GUI-editable.
- Bug A fix (UnboundLocalError at router.py:745) -- independent of
  ?status. Confirmed still in effect.

LLM DM 7-path verification result -- 3 of 7 pass, INCOMPLETE:

| # | query                                         | env_reporter         | verdict |
|---|-----------------------------------------------|----------------------|---------|
| 1 | "are there any fires near me?"                | build_fires_detail   | PASS    |
| 2 | "any weather alerts?"                         | build_alerts_detail  | FAIL    |
| 3 | "any earthquakes nearby?"                     | build_quakes_detail  | FAIL    |
| 4 | "how's traffic on I-84?"                      | build_traffic_detail | FAIL    |
| 5 | "what's the snake river level?"               | build_gauges_detail  | PASS    |
| 6 | "what are the band conditions?"               | build_swpc_detail    | PASS    |
| 7 | "why didn't I hear about anything today?"     | build_drop_audit     | FAIL    |

Two distinct failure classes:

Class A -- routing miss (#4 traffic, #7 drop):
  _ENV_KEYWORDS_TO_SUBTYPE lacks "traffic" (only road/jam/crash/
  closure/511/incident map to "traffic"), so a query literally
  mentioning "traffic" never triggers env scope -> build_traffic_detail
  never runs even though traffic_events has 9 rows on disk. The LLM
  fell back to training data and hallucinated I-84 conditions.
  build_drop_audit has no natural-language trigger phrase at all;
  "why didn't I hear about anything today?" has no env keyword.

Class B -- empty data + LLM hallucination (#2 alerts, #3 quakes):
  Env scope IS detected, build_alerts_detail and build_quakes_detail
  DO run, but return empty because nws_alerts has 0 rows and
  quake_events 24h-window has 0 rows (legitimate empty state). The
  LLM has no env block to ground on and hallucinated "144 earthquakes
  worldwide" -- sounds authoritative, is fabricated.

Not fixed in this commit -- needs Matt's call on:
  (a) keyword additions to _ENV_KEYWORDS_TO_SUBTYPE for traffic +
      drop_audit triggers (risk: false-positive env-scope triggers
      for unrelated phrases).
  (b) anti-hallucination prompt clamp: "If a topic's env block is
      missing/empty, say you don't have live data instead of
      answering from general knowledge." (risk: bot apologizes
      every other message.)

Per the "STOP if any path fails" instruction, this commit does NOT
claim verification done; the report at
v0.7-firetracker-phase4.md has the full table + per-row mesh-receiver
wire + per-failure root cause analysis.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-06 07:33:11 +00:00
.github/workflows
config build: normalize all line endings to LF 2026-05-14 22:43:06 +00:00
dashboard-frontend feat(v0.6-tail-3): enforce OR-not-AND continuously -- close USGS direct-lookup leak + flag environmental config changes as restart-required 2026-06-06 03:51:10 +00:00
meshai fix(v0.7-fire-tracker-4-revised): rip ?status; LLM DM 7-path verification 3 of 7 pass (NOT verified) 2026-06-06 07:33:11 +00:00
tests fix(v0.7-fire-tracker-4-revised): rip ?status; LLM DM 7-path verification 3 of 7 pass (NOT verified) 2026-06-06 07:33:11 +00:00
.dockerignore
.gitattributes build: add .gitattributes to enforce LF line endings 2026-05-14 22:42:14 +00:00
.gitignore feat(v0.5.8b): persistence foundation + WFIGS handler + universal cold-start grace 2026-06-05 03:54:04 +00:00
config.example.yaml build: normalize all line endings to LF 2026-05-14 22:43:06 +00:00
docker-compose.yml fix(infra): point meshai container DNS at LXC working resolver 2026-05-27 17:15:29 +00:00
docker-entrypoint.sh feat: Hybrid RAG knowledge base, sentence-aware chunking, MeshMonitor HTTP sync 2026-05-04 07:44:12 +00:00
Dockerfile feat(dashboard): embedded FastAPI backend with REST API + WebSocket 2026-05-12 15:47:58 +00:00
LICENSE
pyproject.toml feat(central): v0.4 C.1 Central connector backend (no-op until adapter source flipped) 2026-05-28 02:28:19 +00:00
README.md docs: comprehensive README with full setup guide 2026-05-12 21:02:17 -06:00
requirements.txt feat(content): v0.5.8-state_511_atis -- central_normalizer with Photon nearest_town + composer bypass + SB->S route normalization 2026-06-04 21:38:40 +00:00

MeshAI

LLM-powered mesh intelligence assistant for Meshtastic networks. MeshAI connects to your mesh as a physical node, monitors network health in real-time, and answers questions about your infrastructure over LoRa.

What It Does

MeshAI runs on your Meshtastic node and provides:

  • Mesh Intelligence — 5-pillar health scoring, per-region breakdowns, infrastructure monitoring, coverage gap analysis, and environmental sensing
  • Conversational Queries — ask "how's the mesh?" or "tell me about MHR" and get data-driven answers over LoRa
  • Node Distance — GPS-based distance calculations between any two nodes on the mesh
  • Multi-Source Awareness — aggregates data from multiple Meshview instances and MeshMonitor with staggered polling
  • Feeder Gateway Tracking — identifies which physical MQTT gateways hear each node and signal quality
  • Subscriptions — scheduled daily/weekly health reports and instant alerts delivered via DM
  • LLM Chat — general conversation, knowledge base lookups, and weather queries
  • Multi-Backend — supports Google Gemini, OpenAI, Anthropic Claude, and local LLMs via LiteLLM

Quick Start

# Clone
git clone https://github.com/zvx-echo6/meshai.git
cd meshai

# Install
pip install -e .

# Configure (interactive TUI)
meshai --config

# Run
meshai

Or with Docker:

mkdir -p meshai/data && cd meshai
curl -O https://raw.githubusercontent.com/zvx-echo6/meshai/main/docker-compose.yml
curl -o data/config.yaml https://raw.githubusercontent.com/zvx-echo6/meshai/main/config.example.yaml
# Edit data/config.yaml
docker compose up -d

Commands

Command Description
!health Mesh health overview with colored status dots
!region List all regions with health status
!region [name] Detailed region breakdown
!neighbors [node] Top infrastructure neighbors with signal quality
!sub daily 6pm Subscribe to daily health reports
!sub weekly 8am sun Subscribe to weekly digest
!sub alerts Subscribe to instant alerts on issues
!unsub [type] Remove a subscription
!mysubs List your active subscriptions
!clear Clear conversation history
!help Show available commands
!help [cmd] Detailed help for a command
!quakes Recent earthquakes in monitored area
!fires Active wildfires from NIFC
!hotspots NASA FIRMS satellite fire detections
!hotspots --new Only hotspots not matching known fires
!traffic Traffic incidents from TomTom
!space Space weather conditions (solar/geomagnetic)
!water USGS stream gauge readings
!air Air quality index

Commands can be disabled in config if another service (like MeshMonitor) handles them.

Mesh Intelligence

MeshAI continuously polls mesh data sources and computes a 5-pillar health score:

Pillar Weight What It Measures
Infrastructure 30% Router uptime — how many infra nodes are online
Utilization 25% Channel busyness — RF congestion across the mesh
Coverage 20% Gateway reach — how many monitoring sources see each node
Behavior 15% Traffic patterns — detecting noisy or misconfigured nodes
Power 10% Battery health — infrastructure nodes only

Health Display

!health shows a compact overview with personality:

📡 Mesh 🟢 healthy
🏗️ 15/16 routers up
❌ Down: TVM Tablerock Relay
📶 152 full coverage, 94 on thin ice
🔥 Hayden Peak Router at 21% util
🔋 All infra powered ✅
🌡️ 29-34°C across 2 sensors
Treasure Valley 🟢 | Magic Valley 🟢

Status dots: 🔵 perfect (100) · 🟢 healthy (75+) · 🟠 warning (50+) · 🔴 critical (<50)

Monitoring Rules

Infrastructure nodes (routers, repeaters) are monitored individually with full detail — battery, offline alerts, coverage, neighbors, hardware. Client nodes dying is normal and not tracked. Channel utilization and environmental sensors are monitored for all nodes.

Conversational Queries

Ask questions naturally over LoRa:

  • "how's the mesh?" → health overview with top issues
  • "tell me about MHR" → full node detail with neighbors, coverage, feeders
  • "where do we need more coverage?" → named gaps with specific nodes
  • "how far is MHR from AIDA?" → GPS distance calculation
  • "which nodes only reach one gateway?" → named nodes with their gateway
  • "which gateway has the best signal?" → feeder comparison

Geographic Regions

Regions are configurable with local names, descriptions, aliases, and cities — all manageable through the TUI. No hardcoded geography in the code.

mesh_intelligence:
  regions:
    - name: "South Central ID"
      local_name: "Magic Valley"
      description: "Twin Falls area"
      aliases: ["southern Idaho", "magic valley"]
      cities: ["Twin Falls", "Burley", "Jerome"]
      lat: 42.5
      lon: -114.5
      radius_km: 80

Environmental Feeds

MeshAI integrates real-time environmental data for situational awareness beyond mesh network health.

USGS Earthquake Monitoring

env:
  usgs:
    enabled: true
    min_magnitude: 2.5
    radius_km: 500
    center_lat: 43.6150
    center_lon: -116.2023

No API key required. Data from USGS Earthquake Hazards Program.

NWS Weather Alerts

env:
  nws:
    enabled: true
    zone: IDZ025         # NWS zone ID
    point: "43.6150,-116.2023"

No API key required. Find your zone at NWS Zone Lookup.

NOAA Space Weather

env:
  noaa_space:
    enabled: true

No API key required. Data from NOAA SWPC.

NIFC Wildfire Perimeters

env:
  nifc:
    enabled: true
    radius_km: 200
    center_lat: 43.6150
    center_lon: -116.2023

No API key required. Data from NIFC Open Data.

NASA FIRMS Satellite Fire Detection

env:
  firms:
    enabled: true
    map_key: "your-map-key"    # Required
    radius_km: 200
    center_lat: 43.6150
    center_lon: -116.2023
    source: VIIRS_SNPP         # VIIRS_SNPP, VIIRS_NOAA20, MODIS_NRT
    day_range: 1               # 1, 2, or 10 days

API Key Required: Register at NASA FIRMS. Free MAP_KEY provides access to near real-time satellite fire detections. Hotspots are cross-referenced against NIFC perimeters to identify potential new ignitions.

TomTom Traffic

env:
  tomtom:
    enabled: true
    api_key: "your-api-key"    # Required
    bbox: "-117.5,42.5,-115.0,44.5"  # lon1,lat1,lon2,lat2

API Key Required: Register at TomTom Developer Portal. Free tier includes 2,500 requests/day.

511 Road Conditions

env:
  fiveonone:
    enabled: true
    state: ID                  # State code
    api_key: "your-api-key"    # If required by state
    bbox: [-117.5, 42.5, -115.0, 44.5]

API key requirements vary by state. Check your state's 511 developer portal.

USGS Water Services

env:
  usgs_water:
    enabled: true
    sites: ["13206000", "13202000"]  # USGS site numbers

No API key required. Find sites at USGS Water Services.

AirNow Air Quality

env:
  airnow:
    enabled: true
    api_key: "your-api-key"    # Required
    zipcode: "83702"

API Key Required: Register at AirNow API.

Dashboard Configuration

dashboard:
  enabled: true
  host: 0.0.0.0
  port: 8080

The web dashboard provides real-time visualization of mesh nodes, environmental conditions, and alerts with WebSocket push notifications.


Data Sources

MeshAI aggregates from multiple sources using staggered tick-based polling (one API call per 30-second tick):

Meshview

Unauthenticated REST API. Supports multiple instances.

Endpoint Interval Data
/api/packets 30s Near real-time packet feed
/api/nodes 2 min Node list with metadata
/api/stats 3 min Traffic statistics
/api/edges 3 min Node-to-node connections
/api/traceroutes 5 min Route data
/api/packets_seen 10 min Per-gateway RSSI/SNR (sampled)

MeshMonitor

Authenticated (Bearer token). Single instance.

Endpoint Interval Data
/api/v1/packets 60s Packet feed
/api/v1/nodes 2 min Nodes with battery, utilization, hardware
/api/v1/telemetry 2 min Environmental sensors, device metrics
/api/v1/traceroutes 5 min Route data
/api/v1/channels 5 min Channel configuration
/api/v1/network 5 min Network statistics
/api/v1/solar 10 min Solar estimates

Rate Limiting

Built-in protection for all sources: HTTP 429 backoff with Retry-After, exponential backoff on consecutive errors, slow response warnings, and optional polite mode for shared instances.

Source Configuration

mesh_sources:
  - name: "local-meshview"
    type: meshview
    url: "http://192.168.1.100:8080"
    enabled: true

  - name: "meshmonitor"
    type: meshmonitor
    url: "http://192.168.1.100:3333"
    api_token: "your-bearer-token"
    enabled: true

Knowledge Base (RAG)

MeshAI uses a hybrid knowledge retrieval system with two backends:

Primary: RECON Qdrant Backend

Queries RECON's knowledge extraction pipeline — 2.8M+ vectors covering survival skills, communications, medical, technical documentation, Meshtastic docs, and more. Uses the same embedding infrastructure as RECON:

  • Dense embeddings: TEI service with BAAI/bge-m3 (1024-dim)
  • Sparse embeddings: bge-m3-sparse with IDF modifier
  • Search: Qdrant hybrid with Reciprocal Rank Fusion (dense + sparse)

No data is copied — MeshAI queries RECON's Qdrant and TEI services over the network.

knowledge:
  enabled: true
  backend: auto            # "qdrant", "sqlite", or "auto" (try qdrant, fall back)
  qdrant_host: "192.168.1.150"
  qdrant_port: 6333
  qdrant_collection: "recon_knowledge_hybrid"
  tei_host: "192.168.1.150"
  tei_port: 8090
  sparse_host: "192.168.1.150"
  sparse_port: 8091
  use_sparse: true
  top_k: 5

Fallback: Local SQLite

If the Qdrant backend is unreachable, MeshAI falls back to a local SQLite knowledge base using FTS5 keyword search and bge-small-en-v1.5 vector embeddings (384-dim).

# Build from Meshtastic ZIM file
python scripts/zim_to_knowledge.py meshtastic.zim --output knowledge.db
knowledge:
  enabled: true
  backend: sqlite
  db_path: /data/meshai_knowledge.db
  top_k: 5

Requires sqlite-vec and fastembed for the SQLite backend.

Architecture

┌──────────────────────────────────────────────────────────────────────┐
│                              MeshAI                                  │
├──────────────────────────────────────────────────────────────────────┤
│                                                                      │
│  DATA SOURCES              INTELLIGENCE              DELIVERY        │
│  ┌─────────────┐          ┌──────────────┐         ┌────────────┐   │
│  │ Meshview ×N  │─────┐   │ Health Engine │────────▶│  Reporter  │   │
│  │ (staggered)  │     │   │ 5-pillar     │         │ Tier 1/2   │   │
│  └─────────────┘     ▼   │ scoring      │         └─────┬──────┘   │
│  ┌─────────────┐  ┌──────┴──┐            │               │          │
│  │ MeshMonitor │─▶│  Data   │─┘          │         ┌─────▼──────┐   │
│  │ (staggered) │  │  Store  │            │         │   Router   │   │
│  └─────────────┘  │ SQLite  │            │         │ scope/dist │   │
│                   └─────────┘            │         └─────┬──────┘   │
│                        │                 │               │          │
│                   ┌────▼────┐      ┌─────▼──────┐  ┌────▼────┐    │
│                   │ Feeder  │      │    LLM     │  │ Chunker │    │
│                   │ Sampling│      │  Backend   │  │LoRa-fit │    │
│                   └─────────┘      └────────────┘  └────┬────┘    │
│                                                         │         │
│  KNOWLEDGE             ALERTS             DELIVERY      │         │
│  ┌─────────────┐  ┌─────────────┐  ┌──────────────┐    │         │
│  │ RECON/Qdrant│  │   Alert     │  │ Subscription │    │         │
│  │ 2.8M vectors│  │   Engine    │  │   Manager    │    │         │
│  │ (network)   │  │ 17 triggers │  │ daily/weekly │    │         │
│  ├─────────────┤  │  scaling    │  │   alerts     │    │         │
│  │ SQLite FTS5 │  │  cooldown   │  └──────┬───────┘    │         │
│  │ (fallback)  │  └──────┬──────┘         │            │         │
│  └─────────────┘         │          ┌─────▼────────┐   │         │
│                          └─────────▶│  Responder   │◀──┘         │
│  ┌─────────────┐                    │ ACK-paced DM │             │
│  │ Conversation│                    │ Channel alert│             │
│  │   History   │                    └──────────────┘             │
│  └─────────────┘                                                 │
│                                                                   │
└───────────────────────────────────────────────────────────────────┘
         │                    │
    ┌────▼────┐          ┌────▼────┐
    │  TEI    │          │ Qdrant  │
    │ bge-m3  │          │ hybrid  │
    │ cortex  │          │ cortex  │
    └─────────┘          └─────────┘

Dashboard API Reference

The dashboard exposes a REST API (default port 8080):

Core Endpoints

Endpoint Method Description
/api/health GET System health check
/api/status GET Full system status with health scores
/api/nodes GET Connected mesh nodes
/api/messages GET Recent mesh messages

Environmental Data

Endpoint Method Description
/api/env/earthquakes GET Recent earthquakes
/api/env/weather GET Weather conditions and alerts
/api/env/fires GET Active wildfires from NIFC
/api/env/hotspots GET NASA FIRMS satellite detections
/api/env/traffic GET Traffic incidents
/api/env/water GET Stream gauge readings
/api/env/space GET Space weather data
/api/env/air GET Air quality readings

Alerts

Endpoint Method Description
/api/alerts/active GET Currently active alerts
/api/alerts/history GET Historical alerts (?severity=, ?source=, ?limit=, ?offset=)
/api/alerts/{id}/ack POST Acknowledge an alert
/api/subscriptions GET Alert subscriptions

WebSocket

Connect to /ws for real-time updates:

const ws = new WebSocket('ws://localhost:8080/ws');
ws.onmessage = (event) => {
  const data = JSON.parse(event.data);
  // data.type: 'message', 'alert', 'node_update', 'health_update'
};

Message Chunking

Long responses are split into mesh-friendly chunks with sentence-aware splitting, configurable limits, and continuation prompts. Command output (like !health) packs multiple lines into 2-3 messages using newlines within each message to minimize airtime usage.

response:
  max_length: 200       # Max chars per message
  max_messages: 3       # Messages before continuation prompt

Alerting

Real-time alerts when mesh conditions change, with scaling cooldowns to prevent spam.

Alert Conditions (17 total, each toggleable)

Pillar Condition Default Threshold
Infrastructure Router goes offline
Infrastructure Router recovery
Infrastructure New router appears
Power Battery warning <50%
Power Battery critical <25%
Power Battery emergency <10%
Power 7-day declining trend >10% drop with rate
Power USB → battery (power outage)
Power Solar not charging during day
Utilization Sustained high utilization >20% for 6h
Utilization Packet flood >500 pkts/24h
Coverage Infra drops to single gateway
Coverage Feeder gateway stops responding
Coverage Region total blackout All infra offline
Scores Mesh health score drop <70/100
Scores Region health score drop <60/100

Scaling Cooldown

Alerts don't spam. When a condition triggers:

  1. Alert 1: fires immediately
  2. Alert 2: 12 hours later (if still in condition)
  3. Alert 3: 24 hours after that
  4. Alert 4: 48 hours after that
  5. Stops until condition resolves

When the condition clears, one recovery notification fires and the tracker resets.

Delivery

Alerts are delivered two ways:

  • Channel broadcast: configurable channel index for mesh-wide visibility
  • DM to subscribers: users who ran !sub alerts receive DMs matching their scope

Critical Nodes

Designate important infrastructure (e.g., MHR, HPR) as critical. When a critical node goes offline, alerts use priority formatting.

mesh_intelligence:
  critical_nodes: ["MHR", "HPR"]
  alert_channel: 0        # Channel for broadcast alerts (-1 = disabled)

All conditions and thresholds are configurable via the TUI under Mesh Intelligence → Alert Rules.

LLM Configuration

llm:
  backend: "google"            # openai, anthropic, google
  api_key: "your-api-key"
  model: "gemini-2.0-flash"

Local LLMs

MeshAI works with any OpenAI-compatible API:

  • LiteLLM: base_url: "http://localhost:4000/v1"
  • Open WebUI: base_url: "http://localhost:3000/api"
  • Ollama: base_url: "http://localhost:11434/v1"

Docker

connection:
  type: "tcp"
  tcp_host: "192.168.1.100"
  tcp_port: 4403

Serial Connection

connection:
  type: "serial"
  serial_port: "/dev/ttyUSB0"

Edit docker-compose.serial.yml to match your device path.

Environment Variables

LLM_API_KEY=your-key-here docker compose up -d

Running Alongside Other Services

advBBS

MeshAI coexists with advBBS on the same node. BBS protocol messages (sync, RAP, mail notifications) are automatically filtered. No configuration needed.

bot:
  filter_bbs_protocols: true

MeshMonitor

MeshAI integrates with MeshMonitor at two levels: it fetches MeshMonitor's auto-responder patterns to avoid duplicate responses, and it uses MeshMonitor's API as a data source for mesh intelligence (battery, telemetry, traceroutes, solar).

meshmonitor:
  enabled: true
  url: "http://192.168.1.100:8080"
  inject_into_prompt: true
  refresh_interval: 300

Running as a Service

# /etc/systemd/system/meshai.service
[Unit]
Description=MeshAI - Meshtastic Mesh Intelligence
After=network.target

[Service]
Type=simple
User=your-user
WorkingDirectory=/path/to/meshai
ExecStart=/usr/bin/python3 -m meshai
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target
sudo systemctl daemon-reload
sudo systemctl enable meshai
sudo systemctl start meshai

Acknowledgments

  • Meshtastic — the mesh networking platform
  • MeshMonitor by Yeraze — monitoring integration and data source
  • advBBS — BBS coexistence design
  • sqlite-vec by Alex Garcia — vector search in SQLite
  • fastembed by Qdrant — fast local embeddings

License

MIT License

Author

K7ZVX - matt@echo6.co