add personal assistant usage stats (#3543)

backend/ee/onyx/db/analytics.py

@@ -2,6 +2,7 @@ import datetime
 from collections.abc import Sequence
 from uuid import UUID
 
+from sqlalchemy import and_
 from sqlalchemy import case
 from sqlalchemy import cast
 from sqlalchemy import Date
@@ -14,6 +15,9 @@ from onyx.configs.constants import MessageType
 from onyx.db.models import ChatMessage
 from onyx.db.models import ChatMessageFeedback
 from onyx.db.models import ChatSession
+from onyx.db.models import Persona
+from onyx.db.models import User
+from onyx.db.models import UserRole
 
 
 def fetch_query_analytics(
@@ -234,3 +238,121 @@ def fetch_persona_unique_users(
     )
 
     return [tuple(row) for row in db_session.execute(query).all()]
+
+
+def fetch_assistant_message_analytics(
+    db_session: Session,
+    assistant_id: int,
+    start: datetime.datetime,
+    end: datetime.datetime,
+) -> list[tuple[int, datetime.date]]:
+    """
+    Gets the daily message counts for a specific assistant in the given time range.
+    """
+    query = (
+        select(
+            func.count(ChatMessage.id),
+            cast(ChatMessage.time_sent, Date),
+        )
+        .join(
+            ChatSession,
+            ChatMessage.chat_session_id == ChatSession.id,
+        )
+        .where(
+            or_(
+                ChatMessage.alternate_assistant_id == assistant_id,
+                ChatSession.persona_id == assistant_id,
+            ),
+            ChatMessage.time_sent >= start,
+            ChatMessage.time_sent <= end,
+            ChatMessage.message_type == MessageType.ASSISTANT,
+        )
+        .group_by(cast(ChatMessage.time_sent, Date))
+        .order_by(cast(ChatMessage.time_sent, Date))
+    )
+
+    return [tuple(row) for row in db_session.execute(query).all()]
+
+
+def fetch_assistant_unique_users(
+    db_session: Session,
+    assistant_id: int,
+    start: datetime.datetime,
+    end: datetime.datetime,
+) -> list[tuple[int, datetime.date]]:
+    """
+    Gets the daily unique user counts for a specific assistant in the given time range.
+    """
+    query = (
+        select(
+            func.count(func.distinct(ChatSession.user_id)),
+            cast(ChatMessage.time_sent, Date),
+        )
+        .join(
+            ChatSession,
+            ChatMessage.chat_session_id == ChatSession.id,
+        )
+        .where(
+            or_(
+                ChatMessage.alternate_assistant_id == assistant_id,
+                ChatSession.persona_id == assistant_id,
+            ),
+            ChatMessage.time_sent >= start,
+            ChatMessage.time_sent <= end,
+            ChatMessage.message_type == MessageType.ASSISTANT,
+        )
+        .group_by(cast(ChatMessage.time_sent, Date))
+        .order_by(cast(ChatMessage.time_sent, Date))
+    )
+
+    return [tuple(row) for row in db_session.execute(query).all()]
+
+
+def fetch_assistant_unique_users_total(
+    db_session: Session,
+    assistant_id: int,
+    start: datetime.datetime,
+    end: datetime.datetime,
+) -> int:
+    """
+    Gets the total number of distinct users who have sent or received messages from
+    the specified assistant in the given time range.
+    """
+    query = (
+        select(func.count(func.distinct(ChatSession.user_id)))
+        .select_from(ChatMessage)
+        .join(
+            ChatSession,
+            ChatMessage.chat_session_id == ChatSession.id,
+        )
+        .where(
+            or_(
+                ChatMessage.alternate_assistant_id == assistant_id,
+                ChatSession.persona_id == assistant_id,
+            ),
+            ChatMessage.time_sent >= start,
+            ChatMessage.time_sent <= end,
+            ChatMessage.message_type == MessageType.ASSISTANT,
+        )
+    )
+
+    result = db_session.execute(query).scalar()
+    return result if result else 0
+
+
+# Users can view assistant stats if they created the persona,
+# or if they are an admin
+def user_can_view_assistant_stats(
+    db_session: Session, user: User | None, assistant_id: int
+) -> bool:
+    # If user is None, assume the user is an admin or auth is disabled
+    if user is None or user.role == UserRole.ADMIN:
+        return True
+
+    # Check if the user created the persona
+    stmt = select(Persona).where(
+        and_(Persona.id == assistant_id, Persona.user_id == user.id)
+    )
+
+    persona = db_session.execute(stmt).scalar_one_or_none()
+    return persona is not None

backend/ee/onyx/server/analytics/api.py

@@ -1,17 +1,24 @@
 import datetime
 from collections import defaultdict
+from typing import List
 
 from fastapi import APIRouter
 from fastapi import Depends
+from fastapi import HTTPException
 from pydantic import BaseModel
 from sqlalchemy.orm import Session
 
+from ee.onyx.db.analytics import fetch_assistant_message_analytics
+from ee.onyx.db.analytics import fetch_assistant_unique_users
+from ee.onyx.db.analytics import fetch_assistant_unique_users_total
 from ee.onyx.db.analytics import fetch_onyxbot_analytics
 from ee.onyx.db.analytics import fetch_per_user_query_analytics
 from ee.onyx.db.analytics import fetch_persona_message_analytics
 from ee.onyx.db.analytics import fetch_persona_unique_users
 from ee.onyx.db.analytics import fetch_query_analytics
+from ee.onyx.db.analytics import user_can_view_assistant_stats
 from onyx.auth.users import current_admin_user
+from onyx.auth.users import current_user
 from onyx.db.engine import get_session
 from onyx.db.models import User
 
@@ -191,3 +198,74 @@ def get_persona_unique_users(
             )
         )
     return unique_user_counts
+
+
+class AssistantDailyUsageResponse(BaseModel):
+    date: datetime.date
+    total_messages: int
+    total_unique_users: int
+
+
+class AssistantStatsResponse(BaseModel):
+    daily_stats: List[AssistantDailyUsageResponse]
+    total_messages: int
+    total_unique_users: int
+
+
+@router.get("/assistant/{assistant_id}/stats")
+def get_assistant_stats(
+    assistant_id: int,
+    start: datetime.datetime | None = None,
+    end: datetime.datetime | None = None,
+    user: User | None = Depends(current_user),
+    db_session: Session = Depends(get_session),
+) -> AssistantStatsResponse:
+    """
+    Returns daily message and unique user counts for a user's assistant,
+    along with the overall total messages and total distinct users.
+    """
+    start = start or (
+        datetime.datetime.utcnow() - datetime.timedelta(days=_DEFAULT_LOOKBACK_DAYS)
+    )
+    end = end or datetime.datetime.utcnow()
+
+    if not user_can_view_assistant_stats(db_session, user, assistant_id):
+        raise HTTPException(
+            status_code=403, detail="Not allowed to access this assistant's stats."
+        )
+
+    # Pull daily usage from the DB calls
+    messages_data = fetch_assistant_message_analytics(
+        db_session, assistant_id, start, end
+    )
+    unique_users_data = fetch_assistant_unique_users(
+        db_session, assistant_id, start, end
+    )
+
+    # Map each day => (messages, unique_users).
+    daily_messages_map = {date: count for count, date in messages_data}
+    daily_unique_users_map = {date: count for count, date in unique_users_data}
+    all_dates = set(daily_messages_map.keys()) | set(daily_unique_users_map.keys())
+
+    # Merge both sets of metrics by date
+    daily_results: list[AssistantDailyUsageResponse] = []
+    for date in sorted(all_dates):
+        daily_results.append(
+            AssistantDailyUsageResponse(
+                date=date,
+                total_messages=daily_messages_map.get(date, 0),
+                total_unique_users=daily_unique_users_map.get(date, 0),
+            )
+        )
+
+    # Now pull a single total distinct user count across the entire time range
+    total_msgs = sum(d.total_messages for d in daily_results)
+    total_users = fetch_assistant_unique_users_total(
+        db_session, assistant_id, start, end
+    )
+
+    return AssistantStatsResponse(
+        daily_stats=daily_results,
+        total_messages=total_msgs,
+        total_unique_users=total_users,
+    )