Files
meshcore-bot/modules/commands/path_command.py

789 lines
37 KiB
Python

#!/usr/bin/env python3
"""
Path Decode Command for the MeshCore Bot
Decodes hex path data to show which repeaters were involved in message routing
"""
import re
import time
import asyncio
import math
from typing import List, Optional, Dict, Any, Tuple
from .base_command import BaseCommand
from ..models import MeshMessage
class PathCommand(BaseCommand):
"""Command for decoding path data to repeater names"""
# Plugin metadata
name = "path"
keywords = ["path", "decode", "route"]
description = "Decode hex path data to show which repeaters were involved in message routing"
requires_dm = False
cooldown_seconds = 1
category = "meshcore_info"
def __init__(self, bot):
super().__init__(bot)
# Get bot location from config for geographic proximity calculations
# Check if geographic guessing is enabled (bot has location configured)
self.geographic_guessing_enabled = False
self.bot_latitude = None
self.bot_longitude = None
# Get proximity calculation method from config
self.proximity_method = bot.config.get('Path_Command', 'proximity_method', fallback='simple')
self.path_proximity_fallback = bot.config.getboolean('Path_Command', 'path_proximity_fallback', fallback=True)
self.max_proximity_range = bot.config.getfloat('Path_Command', 'max_proximity_range', fallback=200.0)
try:
# Try to get location from Bot section
if bot.config.has_section('Bot'):
lat = bot.config.getfloat('Bot', 'bot_latitude', fallback=None)
lon = bot.config.getfloat('Bot', 'bot_longitude', fallback=None)
if lat is not None and lon is not None:
# Validate coordinates
if -90 <= lat <= 90 and -180 <= lon <= 180:
self.bot_latitude = lat
self.bot_longitude = lon
self.geographic_guessing_enabled = True
self.logger.info(f"Geographic proximity guessing enabled with bot location: {lat:.4f}, {lon:.4f}")
self.logger.info(f"Proximity method: {self.proximity_method}")
else:
self.logger.warning(f"Invalid bot coordinates in config: {lat}, {lon}")
else:
self.logger.info("Bot location not configured - geographic proximity guessing disabled")
else:
self.logger.info("Bot section not found - geographic proximity guessing disabled")
except Exception as e:
self.logger.warning(f"Error reading bot location from config: {e} - geographic proximity guessing disabled")
def matches_keyword(self, message: MeshMessage) -> bool:
"""Check if message starts with 'path' keyword"""
content = message.content.strip()
# Handle exclamation prefix
if content.startswith('!'):
content = content[1:].strip()
# Check if message starts with any of our keywords
content_lower = content.lower()
for keyword in self.keywords:
# Check for exact match or keyword followed by space
if content_lower == keyword or content_lower.startswith(keyword + ' '):
return True
return False
async def execute(self, message: MeshMessage) -> bool:
"""Execute path decode command"""
self.logger.info(f"Path command executed with content: {message.content}")
# Store the current message for use in _extract_path_from_recent_messages
self._current_message = message
# Parse the message content to extract path data
content = message.content.strip()
parts = content.split()
if len(parts) < 2:
# No arguments provided - try to extract path from current message
response = await self._extract_path_from_recent_messages()
else:
# Extract path data from the command
path_input = " ".join(parts[1:])
response = await self._decode_path(path_input)
# Send the response (may be split into multiple messages if long)
await self._send_path_response(message, response)
return True
async def _decode_path(self, path_input: str) -> str:
"""Decode hex path data to repeater names"""
try:
# Parse the path input - handle various formats
# Examples: "11,98,a4,49,cd,5f,01" or "11 98 a4 49 cd 5f 01" or "1198a449cd5f01"
path_input = path_input.replace(',', ' ').replace(':', ' ')
# Extract hex values using regex
hex_pattern = r'[0-9a-fA-F]{2}'
hex_matches = re.findall(hex_pattern, path_input)
if not hex_matches:
return "❌ No valid hex values found in path data. Use format like: 11,98,a4,49,cd,5f,01"
# Convert to uppercase for consistency
# hex_matches preserves the order from the original path
node_ids = [match.upper() for match in hex_matches]
self.logger.info(f"Decoding path with {len(node_ids)} nodes: {','.join(node_ids)}")
# Look up repeater names for each node ID (order preserved)
repeater_info = await self._lookup_repeater_names(node_ids)
# Format the response
return self._format_path_response(node_ids, repeater_info)
except Exception as e:
self.logger.error(f"Error decoding path: {e}")
return f"❌ Error decoding path: {e}"
async def _lookup_repeater_names(self, node_ids: List[str]) -> Dict[str, Dict[str, Any]]:
"""Look up repeater names for given node IDs"""
repeater_info = {}
try:
# First try to get data from API cache (like prefix command does)
api_data = await self._get_api_cache_data()
# Query the database for repeaters with matching prefixes
# Node IDs are typically the first 2 characters of the public key
for node_id in node_ids:
# Check API cache first
if api_data and node_id in api_data:
api_prefix_data = api_data[node_id]
if api_prefix_data['node_names']:
# Use API data
if len(api_prefix_data['node_names']) > 1:
# Multiple matches - show collision warning
repeater_info[node_id] = {
'found': True,
'collision': True,
'matches': len(api_prefix_data['node_names']),
'node_id': node_id,
'repeaters': [
{
'name': name,
'public_key': f"{node_id}...",
'device_type': 'Unknown',
'last_seen': 'API',
'is_active': True,
'source': 'api'
} for name in api_prefix_data['node_names']
]
}
else:
# Single match
repeater_info[node_id] = {
'name': api_prefix_data['node_names'][0],
'public_key': f"{node_id}...",
'device_type': 'Unknown',
'last_seen': 'API',
'is_active': True,
'found': True,
'collision': False,
'source': 'api'
}
continue
# Fallback to complete tracking database if API cache doesn't have this prefix
# First try complete tracking database (all heard contacts, filtered by role)
if hasattr(self.bot, 'repeater_manager'):
try:
# Get repeater devices from complete database (repeaters and roomservers)
complete_db = await self.bot.repeater_manager.get_repeater_devices(include_historical=True)
results = []
for row in complete_db:
if row['public_key'].startswith(node_id):
results.append({
'name': row['name'],
'public_key': row['public_key'],
'device_type': row['device_type'],
'last_seen': row['last_heard'],
'is_active': row['is_currently_tracked'],
'latitude': row['latitude'],
'longitude': row['longitude'],
'city': row['city'],
'state': row['state'],
'country': row['country'],
'advert_count': row['advert_count'],
'signal_strength': row['signal_strength'],
'hop_count': row['hop_count'],
'role': row['role']
})
except Exception as e:
self.logger.debug(f"Error getting complete database: {e}")
results = []
# Fallback to legacy database if complete tracking fails
if not results:
query = '''
SELECT name, public_key, device_type, last_seen, is_active, latitude, longitude, city, state, country
FROM repeater_contacts
WHERE public_key LIKE ?
ORDER BY is_active DESC, last_seen DESC
'''
prefix_pattern = f"{node_id}%"
results = self.bot.db_manager.execute_query(query, (prefix_pattern,))
if results:
# Check for ID collisions (multiple repeaters with same prefix)
if len(results) > 1:
# Multiple matches - try geographic proximity selection
repeaters_data = [
{
'name': row['name'],
'public_key': row['public_key'],
'device_type': row['device_type'],
'last_seen': row['last_seen'],
'is_active': row['is_active'],
'latitude': row['latitude'],
'longitude': row['longitude'],
'city': row['city'],
'state': row['state'],
'country': row['country']
} for row in results
]
# Try to select the most likely repeater using geographic proximity
# Only attempt if geographic guessing is enabled
if self.geographic_guessing_enabled:
selected_repeater, confidence = self._select_repeater_by_proximity(repeaters_data, node_id, node_ids)
if selected_repeater and confidence >= 0.5:
# High confidence geographic selection
repeater_info[node_id] = {
'name': selected_repeater['name'],
'public_key': selected_repeater['public_key'],
'device_type': selected_repeater['device_type'],
'last_seen': selected_repeater['last_seen'],
'is_active': selected_repeater['is_active'],
'found': True,
'collision': False,
'geographic_guess': True,
'confidence': confidence
}
else:
# Low confidence or no geographic data - show collision warning
repeater_info[node_id] = {
'found': True,
'collision': True,
'matches': len(results),
'node_id': node_id,
'repeaters': repeaters_data
}
else:
# Geographic guessing disabled - show collision warning
repeater_info[node_id] = {
'found': True,
'collision': True,
'matches': len(results),
'node_id': node_id,
'repeaters': repeaters_data
}
else:
# Single match
row = results[0]
repeater_info[node_id] = {
'name': row['name'],
'public_key': row['public_key'],
'device_type': row['device_type'],
'last_seen': row['last_seen'],
'is_active': row['is_active'],
'found': True,
'collision': False
}
else:
# Also check device contacts for active repeaters
device_matches = []
if hasattr(self.bot.meshcore, 'contacts'):
for contact_key, contact_data in self.bot.meshcore.contacts.items():
public_key = contact_data.get('public_key', contact_key)
if public_key.startswith(node_id):
# Check if this is a repeater
if hasattr(self.bot, 'repeater_manager') and self.bot.repeater_manager._is_repeater_device(contact_data):
name = contact_data.get('adv_name', contact_data.get('name', 'Unknown'))
device_matches.append({
'name': name,
'public_key': public_key,
'device_type': contact_data.get('type', 'Unknown'),
'last_seen': 'Active',
'is_active': True,
'source': 'device'
})
if device_matches:
if len(device_matches) > 1:
# Multiple device matches - show collision warning
repeater_info[node_id] = {
'found': True,
'collision': True,
'matches': len(device_matches),
'node_id': node_id,
'repeaters': device_matches
}
else:
# Single device match
match = device_matches[0]
repeater_info[node_id] = {
'name': match['name'],
'public_key': match['public_key'],
'device_type': match['device_type'],
'last_seen': match['last_seen'],
'is_active': match['is_active'],
'found': True,
'collision': False,
'source': 'device'
}
else:
repeater_info[node_id] = {
'found': False,
'node_id': node_id
}
except Exception as e:
self.logger.error(f"Error looking up repeater names: {e}")
# Return basic info for all nodes
for node_id in node_ids:
repeater_info[node_id] = {
'found': False,
'node_id': node_id,
'error': str(e)
}
return repeater_info
async def _get_api_cache_data(self) -> Optional[Dict[str, Dict[str, Any]]]:
"""Get API cache data from the prefix command if available"""
try:
# Try to get the prefix command instance and its cache data
if hasattr(self.bot, 'command_manager'):
prefix_cmd = self.bot.command_manager.commands.get('prefix')
if prefix_cmd and hasattr(prefix_cmd, 'cache_data'):
# Check if cache is valid
current_time = time.time()
if current_time - prefix_cmd.cache_timestamp > prefix_cmd.cache_duration:
await prefix_cmd.refresh_cache()
return prefix_cmd.cache_data
except Exception as e:
self.logger.warning(f"Could not get API cache data: {e}")
return None
def _calculate_distance(self, lat1: float, lon1: float, lat2: float, lon2: float) -> float:
"""Calculate haversine distance between two points in kilometers"""
# Convert latitude and longitude from degrees to radians
lat1_rad = math.radians(lat1)
lon1_rad = math.radians(lon1)
lat2_rad = math.radians(lat2)
lon2_rad = math.radians(lon2)
# Haversine formula
dlat = lat2_rad - lat1_rad
dlon = lon2_rad - lon1_rad
a = math.sin(dlat/2)**2 + math.cos(lat1_rad) * math.cos(lat2_rad) * math.sin(dlon/2)**2
c = 2 * math.asin(math.sqrt(a))
# Earth's radius in kilometers
earth_radius = 6371.0
return earth_radius * c
def _select_repeater_by_proximity(self, repeaters: List[Dict[str, Any]], node_id: str = None, path_context: List[str] = None) -> Tuple[Optional[Dict[str, Any]], float]:
"""
Select the most likely repeater based on geographic proximity.
Args:
repeaters: List of repeaters to choose from
node_id: The current node ID being processed
path_context: Full path for context (for path proximity method)
Returns:
Tuple of (selected_repeater, confidence_score)
confidence_score: 0.0 to 1.0, where 1.0 is very confident
"""
if not repeaters:
return None, 0.0
# Check if geographic guessing is enabled
if not self.geographic_guessing_enabled:
return None, 0.0
# Filter repeaters that have location data
repeaters_with_location = []
for repeater in repeaters:
lat = repeater.get('latitude')
lon = repeater.get('longitude')
if lat is not None and lon is not None:
# Skip 0,0 coordinates (hidden location)
if not (lat == 0.0 and lon == 0.0):
repeaters_with_location.append(repeater)
# If no repeaters have location data, we can't make a geographic guess
if not repeaters_with_location:
return None, 0.0
# Choose proximity calculation method
if self.proximity_method == 'path' and path_context and node_id:
result = self._select_by_path_proximity(repeaters_with_location, node_id, path_context)
if result[0] is not None:
return result
elif self.path_proximity_fallback:
# Fall back to simple proximity if path proximity fails
return self._select_by_simple_proximity(repeaters_with_location)
else:
return None, 0.0
else:
return self._select_by_simple_proximity(repeaters_with_location)
def _select_by_simple_proximity(self, repeaters_with_location: List[Dict[str, Any]]) -> Tuple[Optional[Dict[str, Any]], float]:
"""Select repeater based on proximity to bot location"""
# If only one repeater has location data, check if it's within range
if len(repeaters_with_location) == 1:
repeater = repeaters_with_location[0]
distance = self._calculate_distance(
self.bot_latitude, self.bot_longitude,
repeater['latitude'], repeater['longitude']
)
# Apply maximum range threshold
if self.max_proximity_range > 0 and distance > self.max_proximity_range:
return None, 0.0 # Reject if beyond maximum range
return repeater, 0.6
# Calculate distances for all repeaters with location data
distances = []
for repeater in repeaters_with_location:
distance = self._calculate_distance(
self.bot_latitude, self.bot_longitude,
repeater['latitude'], repeater['longitude']
)
distances.append((distance, repeater))
# Sort by distance (closest first)
distances.sort(key=lambda x: x[0])
closest_distance, closest_repeater = distances[0]
# Apply maximum range threshold
if self.max_proximity_range > 0 and closest_distance > self.max_proximity_range:
return None, 0.0 # Reject if closest repeater is beyond maximum range
# Calculate confidence based on distance difference
if len(distances) == 1:
# Only one repeater with location data
return closest_repeater, 0.6
else:
# Multiple repeaters with location data
second_closest_distance = distances[1][0]
distance_ratio = closest_distance / second_closest_distance if second_closest_distance > 0 else 0
# Higher confidence if there's a significant distance difference
if distance_ratio < 0.5: # Closest is less than half the distance of second closest
confidence = 0.9
elif distance_ratio < 0.7: # Closest is less than 70% of second closest
confidence = 0.8
elif distance_ratio < 0.9: # Closest is less than 90% of second closest
confidence = 0.7
else:
# Distances are too similar, but we can still make a selection
# Use tie-breaker strategies for identical coordinates
if distance_ratio == 1.0: # Identical distances
# Try tie-breaker strategies
selected_repeater = self._apply_tie_breakers(distances)
confidence = 0.5 # Moderate confidence for tie-breaker selection
else:
# Very similar distances, low confidence
confidence = 0.4
return closest_repeater, confidence
def _apply_tie_breakers(self, distances: List[Tuple[float, Dict[str, Any]]]) -> Dict[str, Any]:
"""Apply tie-breaker strategies when repeaters have identical coordinates"""
# Get all repeaters with the same (minimum) distance
min_distance = distances[0][0]
tied_repeaters = [repeater for distance, repeater in distances if distance == min_distance]
# Tie-breaker 1: Prefer active repeaters
active_repeaters = [r for r in tied_repeaters if r.get('is_active', True)]
if len(active_repeaters) == 1:
return active_repeaters[0]
elif len(active_repeaters) > 1:
tied_repeaters = active_repeaters
# Tie-breaker 2: Prefer repeaters with more recent last_seen
# (This is a simple heuristic - in practice, you might want more sophisticated logic)
try:
# Sort by last_seen (more recent first)
tied_repeaters.sort(key=lambda r: r.get('last_seen', ''), reverse=True)
except:
pass # If sorting fails, continue with next tie-breaker
# Tie-breaker 3: Alphabetical order (deterministic)
tied_repeaters.sort(key=lambda r: r.get('name', ''))
return tied_repeaters[0]
def _select_by_path_proximity(self, repeaters_with_location: List[Dict[str, Any]], node_id: str, path_context: List[str]) -> Tuple[Optional[Dict[str, Any]], float]:
"""Select repeater based on proximity to previous/next nodes in path"""
try:
# Find current node position in path
current_index = path_context.index(node_id) if node_id in path_context else -1
if current_index == -1:
return None, 0.0
# Get previous and next node locations
prev_location = None
next_location = None
# Get previous node location
if current_index > 0:
prev_node_id = path_context[current_index - 1]
prev_location = self._get_node_location(prev_node_id)
# Get next node location
if current_index < len(path_context) - 1:
next_node_id = path_context[current_index + 1]
next_location = self._get_node_location(next_node_id)
# If we have both previous and next locations, use both for proximity
if prev_location and next_location:
return self._select_by_dual_proximity(repeaters_with_location, prev_location, next_location)
elif prev_location:
return self._select_by_single_proximity(repeaters_with_location, prev_location, "previous")
elif next_location:
return self._select_by_single_proximity(repeaters_with_location, next_location, "next")
else:
return None, 0.0
except Exception as e:
self.logger.warning(f"Error in path proximity calculation: {e}")
return None, 0.0
def _get_node_location(self, node_id: str) -> Optional[Tuple[float, float]]:
"""Get location for a node ID from the database"""
try:
# Query database for node location
query = '''
SELECT latitude, longitude FROM repeater_contacts
WHERE public_key LIKE ? AND latitude IS NOT NULL AND longitude IS NOT NULL
AND latitude != 0 AND longitude != 0
LIMIT 1
'''
prefix_pattern = f"{node_id}%"
results = self.bot.db_manager.execute_query(query, (prefix_pattern,))
if results:
row = results[0]
return (row['latitude'], row['longitude'])
return None
except Exception as e:
self.logger.warning(f"Error getting location for node {node_id}: {e}")
return None
def _select_by_dual_proximity(self, repeaters: List[Dict[str, Any]], prev_location: Tuple[float, float], next_location: Tuple[float, float]) -> Tuple[Optional[Dict[str, Any]], float]:
"""Select repeater based on proximity to both previous and next nodes"""
best_repeater = None
best_score = float('inf')
for repeater in repeaters:
# Calculate distance to previous node
prev_distance = self._calculate_distance(
prev_location[0], prev_location[1],
repeater['latitude'], repeater['longitude']
)
# Calculate distance to next node
next_distance = self._calculate_distance(
next_location[0], next_location[1],
repeater['latitude'], repeater['longitude']
)
# Combined score (lower is better)
# Weight both distances equally
combined_score = (prev_distance + next_distance) / 2
if combined_score < best_score:
best_score = combined_score
best_repeater = repeater
if best_repeater:
# Apply maximum range threshold
if self.max_proximity_range > 0 and best_score > self.max_proximity_range:
return None, 0.0 # Reject if beyond maximum range
# Calculate confidence based on how much better this choice is
confidence = min(0.9, max(0.6, 1.0 - (best_score / 100.0))) # Scale confidence based on distance
return best_repeater, confidence
return None, 0.0
def _select_by_single_proximity(self, repeaters: List[Dict[str, Any]], reference_location: Tuple[float, float], direction: str) -> Tuple[Optional[Dict[str, Any]], float]:
"""Select repeater based on proximity to single reference node"""
distances = []
for repeater in repeaters:
distance = self._calculate_distance(
reference_location[0], reference_location[1],
repeater['latitude'], repeater['longitude']
)
distances.append((distance, repeater))
# Sort by distance (closest first)
distances.sort(key=lambda x: x[0])
if not distances:
return None, 0.0
closest_distance, closest_repeater = distances[0]
# Apply maximum range threshold
if self.max_proximity_range > 0 and closest_distance > self.max_proximity_range:
return None, 0.0 # Reject if beyond maximum range
# Calculate confidence based on distance difference
if len(distances) == 1:
return closest_repeater, 0.7 # Higher confidence for single reference
else:
second_closest_distance = distances[1][0]
distance_ratio = closest_distance / second_closest_distance if second_closest_distance > 0 else 0
# Higher confidence for path proximity
if distance_ratio < 0.5:
confidence = 0.9
elif distance_ratio < 0.7:
confidence = 0.8
else:
confidence = 0.7
return closest_repeater, confidence
def _format_path_response(self, node_ids: List[str], repeater_info: Dict[str, Dict[str, Any]]) -> str:
"""Format the path decode response (max 130 chars per line)
Maintains the order of repeaters as they appear in the path (first to last)
"""
# Build response lines in path order (first to last as message traveled)
lines = []
# Process nodes in path order (first to last as message traveled)
for node_id in node_ids:
info = repeater_info.get(node_id, {})
if info.get('found', False):
if info.get('collision', False):
# Multiple repeaters with same prefix
matches = info.get('matches', 0)
line = f"{node_id}: {matches} repeaters"
elif info.get('geographic_guess', False):
# Geographic proximity selection
name = info['name']
confidence = info.get('confidence', 0.0)
# Truncate name if too long
if len(name) > 20:
name = name[:17] + "..."
# Add confidence indicator
if confidence >= 0.9:
confidence_indicator = "🎯"
elif confidence >= 0.8:
confidence_indicator = "📍"
else:
confidence_indicator = "~"
line = f"{node_id}: {name} {confidence_indicator}"
else:
# Single repeater found
name = info['name']
# Truncate name if too long
if len(name) > 27:
name = name[:24] + "..."
line = f"{node_id}: {name}"
else:
# Unknown repeater
line = f"{node_id}: Unknown"
# Ensure line fits within 130 character limit
if len(line) > 130:
line = line[:127] + "..."
lines.append(line)
# Return all lines - let _send_path_response handle the splitting
return "\n".join(lines)
async def _send_path_response(self, message: MeshMessage, response: str):
"""Send path response, splitting into multiple messages if necessary"""
if len(response) <= 130:
# Single message is fine
await self.bot.command_manager.send_response(message, response)
else:
# Split into multiple messages
lines = response.split('\n')
current_message = ""
message_count = 0
for i, line in enumerate(lines):
# Check if adding this line would exceed 130 characters
if len(current_message) + len(line) + 1 > 130: # +1 for newline
# Send current message and start new one
if current_message:
# Add ellipsis on new line to end of continued message (if not the last message)
if i < len(lines):
current_message += "\n..."
await self.bot.command_manager.send_response(message, current_message.rstrip())
await asyncio.sleep(3.0) # Delay between messages (same as other commands)
message_count += 1
# Start new message with ellipsis on new line at beginning (if not first message)
if message_count > 0:
current_message = f"...\n{line}"
else:
current_message = line
else:
# Add line to current message
if current_message:
current_message += f"\n{line}"
else:
current_message = line
# Send the last message if there's content
if current_message:
await self.bot.command_manager.send_response(message, current_message)
async def _extract_path_from_recent_messages(self) -> str:
"""Extract path from the current message's path information (same as test command)"""
try:
# Use the path information from the current message being processed
# This is the same reliable source that the test command uses
if hasattr(self, '_current_message') and self._current_message and self._current_message.path:
path_string = self._current_message.path
self.logger.info(f"Using path from current message: {path_string}")
# Check if it's a direct connection
if "Direct" in path_string or "0 hops" in path_string:
return "📡 Direct connection (0 hops)"
# Try to extract path nodes from the path string
# Path strings are typically in format: "node1,node2,node3 via ROUTE_TYPE_*"
if " via ROUTE_TYPE_" in path_string:
# Extract just the path part before the route type
path_part = path_string.split(" via ROUTE_TYPE_")[0]
else:
path_part = path_string
# Check if it looks like a comma-separated path
if ',' in path_part:
path_input = path_part
self.logger.info(f"Found path from current message: {path_input}")
return await self._decode_path(path_input)
else:
# Single node or unknown format
return f"📡 Path: {path_string}"
else:
return "❌ No path information available in current message"
except Exception as e:
self.logger.error(f"Error extracting path from current message: {e}")
return f"❌ Error extracting path from current message: {e}"
def get_help(self) -> str:
"""Get help text for the path command"""
return """Path: !path [hex] - Decode path to show repeaters. Use !path alone for recent message path, or !path [7e,01] for specific path."""
def get_help_text(self) -> str:
"""Get help text for the path command (used by help system)"""
return self.get_help()