File size: 10,590 Bytes
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9052ef3
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9052ef3
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
261e0ce
5a24119
 
261e0ce
 
 
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
261e0ce
 
 
 
5a24119
261e0ce
 
 
 
 
 
 
 
5a24119
 
 
 
 
 
 
 
 
 
261e0ce
 
 
 
5a24119
261e0ce
 
 
 
 
 
 
 
 
 
 
 
 
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9052ef3
5a24119
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
# ────────────────────────────── utils/analytics.py ──────────────────────────────
"""
Analytics and Usage Tracking System

Tracks user-specific usage of models and agents for analytics dashboard.
"""

import time
from datetime import datetime, timezone
from typing import Dict, Any, List, Optional
from pymongo.collection import Collection
from pymongo.database import Database
from pymongo import MongoClient
from utils.logger import get_logger

logger = get_logger("ANALYTICS", __name__)

class AnalyticsTracker:
    """Tracks user usage analytics for models and agents."""
    
    def __init__(self, mongo_client: MongoClient, db_name: str = "studybuddy"):
        self.client = mongo_client
        self.db = mongo_client[db_name]
        self.usage_collection = self.db["usage_analytics"]
        self._ensure_indexes()
    
    def _ensure_indexes(self):
        """Create necessary indexes for efficient queries."""
        try:
            # Compound index for user_id + timestamp
            self.usage_collection.create_index([("user_id", 1), ("timestamp", -1)])
            # Index for aggregation queries
            self.usage_collection.create_index([("user_id", 1), ("type", 1), ("timestamp", -1)])
            logger.info("[ANALYTICS] Indexes created successfully")
        except Exception as e:
            logger.warning(f"[ANALYTICS] Failed to create indexes: {e}")
    
    async def track_model_usage(self, user_id: str, model_name: str, provider: str, 
                               context: str = "", metadata: Optional[Dict] = None):
        """Track model usage for analytics."""
        try:
            usage_record = {
                "user_id": user_id,
                "type": "model",
                "model_name": model_name,
                "provider": provider,
                "context": context,
                "timestamp": time.time(),
                "created_at": datetime.now(timezone.utc),
                "metadata": metadata or {}
            }
            
            self.usage_collection.insert_one(usage_record)
            logger.debug(f"[ANALYTICS] Tracked model usage: {model_name} for user {user_id}")
            
        except Exception as e:
            logger.error(f"[ANALYTICS] Failed to track model usage: {e}")
    
    async def track_agent_usage(self, user_id: str, agent_name: str, action: str,
                              context: str = "", metadata: Optional[Dict] = None):
        """Track agent usage for analytics."""
        try:
            usage_record = {
                "user_id": user_id,
                "type": "agent",
                "agent_name": agent_name,
                "action": action,
                "context": context,
                "timestamp": time.time(),
                "created_at": datetime.now(timezone.utc),
                "metadata": metadata or {}
            }
            
            self.usage_collection.insert_one(usage_record)
            logger.debug(f"[ANALYTICS] Tracked agent usage: {agent_name} for user {user_id}")
            
        except Exception as e:
            logger.error(f"[ANALYTICS] Failed to track agent usage: {e}")
    
    async def get_user_analytics(self, user_id: str, days: int = 30) -> Dict[str, Any]:
        """Get comprehensive analytics for a user."""
        try:
            # Calculate time range
            cutoff_time = time.time() - (days * 24 * 60 * 60)
            
            # Model usage analytics
            model_pipeline = [
                {"$match": {"user_id": user_id, "type": "model", "timestamp": {"$gte": cutoff_time}}},
                {"$group": {
                    "_id": "$model_name",
                    "count": {"$sum": 1},
                    "provider": {"$first": "$provider"},
                    "last_used": {"$max": "$timestamp"}
                }},
                {"$sort": {"count": -1}}
            ]
            
            model_usage = list(self.usage_collection.aggregate(model_pipeline))
            
            # Agent usage analytics
            agent_pipeline = [
                {"$match": {"user_id": user_id, "type": "agent", "timestamp": {"$gte": cutoff_time}}},
                {"$group": {
                    "_id": "$agent_name",
                    "count": {"$sum": 1},
                    "actions": {"$addToSet": "$action"},
                    "last_used": {"$max": "$timestamp"}
                }},
                {"$sort": {"count": -1}}
            ]
            
            agent_usage = list(self.usage_collection.aggregate(agent_pipeline))
            
            # Daily usage trends
            daily_pipeline = [
                {"$match": {"user_id": user_id, "timestamp": {"$gte": cutoff_time}}},
                {"$addFields": {"date": {"$toDate": {"$multiply": ["$timestamp", 1000]}}}},
                {"$group": {
                    "_id": {
                        "year": {"$year": "$date"},
                        "month": {"$month": "$date"},
                        "day": {"$dayOfMonth": "$date"}
                    },
                    "total_requests": {"$sum": 1},
                    "model_requests": {"$sum": {"$cond": [{"$eq": ["$type", "model"]}, 1, 0]}},
                    "agent_requests": {"$sum": {"$cond": [{"$eq": ["$type", "agent"]}, 1, 0]}}
                }},
                {"$sort": {"_id.year": 1, "_id.month": 1, "_id.day": 1}}
            ]
            
            daily_usage = list(self.usage_collection.aggregate(daily_pipeline))
            
            return {
                "user_id": user_id,
                "period_days": days,
                "model_usage": model_usage,
                "agent_usage": agent_usage,
                "daily_usage": daily_usage,
                "total_requests": sum(item["count"] for item in model_usage + agent_usage),
                "generated_at": datetime.now(timezone.utc).isoformat()
            }
            
        except Exception as e:
            logger.error(f"[ANALYTICS] Failed to get user analytics: {e}")
            return {
                "user_id": user_id,
                "period_days": days,
                "model_usage": [],
                "agent_usage": [],
                "daily_usage": [],
                "total_requests": 0,
                "error": str(e),
                "generated_at": datetime.now(timezone.utc).isoformat()
            }
    
    async def get_global_analytics(self, days: int = 30) -> Dict[str, Any]:
        """Get global analytics across all users."""
        try:
            cutoff_time = time.time() - (days * 24 * 60 * 60)
            
            # Global model usage
            model_pipeline = [
                {"$match": {"type": "model", "timestamp": {"$gte": cutoff_time}}},
                {"$group": {
                    "_id": {
                        "provider": "$provider",
                        "model": "$model_name"
                    },
                    "count": {"$sum": 1},
                    "unique_users": {"$addToSet": "$user_id"}
                }},
                {"$project": {
                    "_id": 0,
                    "model_name": "$_id.model",
                    "provider": "$_id.provider",
                    "count": 1,
                    "unique_user_count": {"$size": "$unique_users"}
                }},
                {"$sort": {"count": -1}}
            ]
            
            global_model_usage = list(self.usage_collection.aggregate(model_pipeline))
            
            # Global agent usage
            agent_pipeline = [
                {"$match": {"type": "agent", "timestamp": {"$gte": cutoff_time}}},
                {"$group": {
                    "_id": {
                        "agent": "$agent_name",
                        "action": "$action"
                    },
                    "count": {"$sum": 1},
                    "unique_users": {"$addToSet": "$user_id"}
                }},
                {"$group": {
                    "_id": "$_id.agent",
                    "count": {"$sum": "$count"},
                    "unique_users": {"$addToSet": "$unique_users"},
                    "actions": {"$addToSet": "$_id.action"}
                }},
                {"$project": {
                    "_id": 1,
                    "count": 1,
                    "actions": 1,
                    "unique_user_count": {"$size": {"$setUnion": "$unique_users"}}
                }},
                {"$sort": {"count": -1}}
            ]
            
            global_agent_usage = list(self.usage_collection.aggregate(agent_pipeline))
            
            return {
                "period_days": days,
                "global_model_usage": global_model_usage,
                "global_agent_usage": global_agent_usage,
                "total_requests": sum(item["count"] for item in global_model_usage + global_agent_usage),
                "generated_at": datetime.now(timezone.utc).isoformat()
            }
            
        except Exception as e:
            logger.error(f"[ANALYTICS] Failed to get global analytics: {e}")
            return {
                "period_days": days,
                "global_model_usage": [],
                "global_agent_usage": [],
                "total_requests": 0,
                "error": str(e),
                "generated_at": datetime.now(timezone.utc).isoformat()
            }
    
    async def cleanup_old_data(self, days_to_keep: int = 90):
        """Clean up old analytics data to prevent database bloat."""
        try:
            cutoff_time = time.time() - (days_to_keep * 24 * 60 * 60)
            result = self.usage_collection.delete_many({"timestamp": {"$lt": cutoff_time}})
            logger.info(f"[ANALYTICS] Cleaned up {result.deleted_count} old records")
            return result.deleted_count
        except Exception as e:
            logger.error(f"[ANALYTICS] Failed to cleanup old data: {e}")
            return 0


# Global analytics tracker instance
analytics_tracker: Optional[AnalyticsTracker] = None

def init_analytics(mongo_client, db_name: str = "studybuddy"):
    """Initialize the global analytics tracker."""
    global analytics_tracker
    analytics_tracker = AnalyticsTracker(mongo_client, db_name)
    logger.info("[ANALYTICS] Analytics tracker initialized")

def get_analytics_tracker() -> Optional[AnalyticsTracker]:
    """Get the global analytics tracker instance."""
    return analytics_tracker