dandri/meshcore-bot
1
0
Fork 0
mirror of https://github.com/agessaman/meshcore-bot.git synced 2026-07-29 14:59:52 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add greeter command configuration to config.ini.example and implement greeter functionality in message handling. Introduce favorite status management for repeaters, allowing users to toggle favorite status via API. Update path command and test command to incorporate favorite bias in scoring. Enhance database schema to support star status tracking for repeaters and roomservers.

Browse Source
This commit is contained in:
agessaman
2025-11-25 17:26:40 -08:00
parent 732b7551ba
commit 82aa5ee160
8 changed files with 1127 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/commands/path_command.py
+33 -9
View File
@@ -44,6 +44,11 @@ class PathCommand(BaseCommand):
self.recency_weight = max(0.0, min(1.0, recency_weight)) # Clamp to 0.0-1.0
self.proximity_weight = 1.0 - self.recency_weight
# Get star bias multiplier (how much to boost starred repeaters' scores)
# Default 2.5 means starred repeaters get 2.5x their normal score
self.star_bias_multiplier = bot.config.getfloat('Path_Command', 'star_bias_multiplier', fallback=2.5)
self.star_bias_multiplier = max(1.0, self.star_bias_multiplier) # Ensure at least 1.0
# Get confidence indicator symbols from config
self.high_confidence_symbol = bot.config.get('Path_Command', 'high_confidence_symbol', fallback='🎯')
self.medium_confidence_symbol = bot.config.get('Path_Command', 'medium_confidence_symbol', fallback='📍')
@@ -194,7 +199,8 @@ class PathCommand(BaseCommand):
'advert_count': row['advert_count'],
'signal_strength': row['signal_strength'],
'hop_count': row['hop_count'],
'role': row['role']
'role': row['role'],
'is_starred': bool(row.get('is_starred', 0)) # Include star status for bias
})
except Exception as e:
self.logger.debug(f"Error getting complete database: {e}")
@@ -209,7 +215,7 @@ class PathCommand(BaseCommand):
query = '''
SELECT name, public_key, device_type, last_heard, last_heard as last_seen,
last_advert_timestamp, latitude, longitude, city, state, country,
advert_count, signal_strength, hop_count, role
advert_count, signal_strength, hop_count, role, is_starred
FROM complete_contact_tracking
WHERE public_key LIKE ? AND role IN ('repeater', 'roomserver')
AND (
@@ -222,7 +228,7 @@ class PathCommand(BaseCommand):
query = '''
SELECT name, public_key, device_type, last_heard, last_heard as last_seen,
last_advert_timestamp, latitude, longitude, city, state, country,
advert_count, signal_strength, hop_count, role
advert_count, signal_strength, hop_count, role, is_starred
FROM complete_contact_tracking
WHERE public_key LIKE ? AND role IN ('repeater', 'roomserver')
ORDER BY COALESCE(last_advert_timestamp, last_heard) DESC
@@ -250,7 +256,8 @@ class PathCommand(BaseCommand):
'advert_count': row.get('advert_count', 0),
'signal_strength': row.get('signal_strength'),
'hop_count': row.get('hop_count'),
'role': row.get('role')
'role': row.get('role'),
'is_starred': bool(row.get('is_starred', 0)) # Include star status for bias
} for row in results
]
except Exception as e:
@@ -272,7 +279,8 @@ class PathCommand(BaseCommand):
'longitude': row['longitude'],
'city': row['city'],
'state': row['state'],
'country': row['country']
'country': row['country'],
'is_starred': row.get('is_starred', False) # Include star status for bias
} for row in results
]
@@ -510,6 +518,12 @@ class PathCommand(BaseCommand):
# Use configurable weighting (default: 40% recency, 60% proximity)
combined_score = (recency_score * self.recency_weight) + (proximity_score * self.proximity_weight)
# Apply star bias multiplier if repeater is starred
if repeater.get('is_starred', False):
combined_score *= self.star_bias_multiplier
self.logger.debug(f"Applied star bias ({self.star_bias_multiplier}x) to {repeater.get('name', 'unknown')}")
combined_scores.append((combined_score, distance, repeater))
if not combined_scores:
@@ -805,22 +819,22 @@ class PathCommand(BaseCommand):
# Use last_advert_timestamp if available, otherwise fall back to last_heard
if self.max_repeater_age_days > 0:
query = '''
SELECT latitude, longitude FROM complete_contact_tracking
SELECT latitude, longitude, is_starred FROM complete_contact_tracking
WHERE public_key LIKE ? AND latitude IS NOT NULL AND longitude IS NOT NULL
AND latitude != 0 AND longitude != 0 AND role IN ('repeater', 'roomserver')
AND (
(last_advert_timestamp IS NOT NULL AND last_advert_timestamp >= datetime('now', '-{} days'))
OR (last_advert_timestamp IS NULL AND last_heard >= datetime('now', '-{} days'))
)
ORDER BY COALESCE(last_advert_timestamp, last_heard) DESC
ORDER BY is_starred DESC, COALESCE(last_advert_timestamp, last_heard) DESC
LIMIT 1
'''.format(self.max_repeater_age_days, self.max_repeater_age_days)
else:
query = '''
SELECT latitude, longitude FROM complete_contact_tracking
SELECT latitude, longitude, is_starred FROM complete_contact_tracking
WHERE public_key LIKE ? AND latitude IS NOT NULL AND longitude IS NOT NULL
AND latitude != 0 AND longitude != 0 AND role IN ('repeater', 'roomserver')
ORDER BY COALESCE(last_advert_timestamp, last_heard) DESC
ORDER BY is_starred DESC, COALESCE(last_advert_timestamp, last_heard) DESC
LIMIT 1
'''
@@ -871,6 +885,11 @@ class PathCommand(BaseCommand):
# Use configurable weighting (default: 40% recency, 60% proximity)
combined_score = (recency_score * self.recency_weight) + (proximity_score * self.proximity_weight)
# Apply star bias multiplier if repeater is starred
if repeater.get('is_starred', False):
combined_score *= self.star_bias_multiplier
self.logger.debug(f"Applied star bias ({self.star_bias_multiplier}x) to {repeater.get('name', 'unknown')}")
if combined_score > best_combined_score:
best_combined_score = combined_score
best_repeater = repeater
@@ -928,6 +947,11 @@ class PathCommand(BaseCommand):
# Use configurable weighting (default: 40% recency, 60% proximity)
combined_score = (recency_score * self.recency_weight) + (proximity_score * self.proximity_weight)
# Apply star bias multiplier if repeater is starred
if repeater.get('is_starred', False):
combined_score *= self.star_bias_multiplier
self.logger.debug(f"Applied star bias ({self.star_bias_multiplier}x) to {repeater.get('name', 'unknown')}")
if combined_score > best_combined_score:
best_combined_score = combined_score
best_repeater = repeater