(feat) use clickhouse for viewing data on Admin UI

enterprise/utils.py

@@ -1,4 +1,5 @@
 # Enterprise Proxy Util Endpoints
+from litellm._logging import verbose_logger
 
 
 async def get_spend_by_tags(start_date=None, end_date=None, prisma_client=None):
@@ -14,3 +15,85 @@ async def get_spend_by_tags(start_date=None, end_date=None, prisma_client=None):
     )
 
     return response
+
+
+async def view_spend_logs_from_clickhouse(
+    api_key=None, user_id=None, request_id=None, start_date=None, end_date=None
+):
+    verbose_logger.debug("Reading logs from Clickhouse")
+    import os
+
+    # if user has setup clickhouse
+    # TODO: Move this to be a helper function
+    # querying clickhouse for this data
+    import clickhouse_connect
+    from datetime import datetime
+
+    port = os.getenv("CLICKHOUSE_PORT")
+    if port is not None and isinstance(port, str):
+        port = int(port)
+
+    client = clickhouse_connect.get_client(
+        host=os.getenv("CLICKHOUSE_HOST"),
+        port=port,
+        username=os.getenv("CLICKHOUSE_USERNAME", ""),
+        password=os.getenv("CLICKHOUSE_PASSWORD", ""),
+    )
+    if (
+        start_date is not None
+        and isinstance(start_date, str)
+        and end_date is not None
+        and isinstance(end_date, str)
+    ):
+        # Convert the date strings to datetime objects
+        start_date_obj = datetime.strptime(start_date, "%Y-%m-%d")
+        end_date_obj = datetime.strptime(end_date, "%Y-%m-%d")
+
+        # get top spend per day
+        response = client.query(
+            f"""
+                SELECT
+                    toDate(startTime) AS day,
+                    sum(spend) AS total_spend
+                FROM
+                    spend_logs
+                WHERE
+                    toDate(startTime) BETWEEN toDate('2024-02-01') AND toDate('2024-02-29')
+                GROUP BY
+                    day
+                ORDER BY
+                    total_spend
+                """
+        )
+
+        results = []
+        result_rows = list(response.result_rows)
+        for response in result_rows:
+            current_row = {}
+            current_row["users"] = {"example": 0.0}
+            current_row["models"] = {}
+
+            current_row["spend"] = float(response[1])
+            current_row["startTime"] = str(response[0])
+
+            # stubbed api_key
+            current_row[""] = 0.0  # type: ignore
+            results.append(current_row)
+
+        return results
+    else:
+        # check if spend logs exist, if it does then return last 10 logs, sorted in descending order of startTime
+        response = client.query(
+            """
+                SELECT
+                    *
+                FROM
+                    default.spend_logs
+                ORDER BY
+                    startTime DESC
+                LIMIT
+                    10
+            """
+        )
+        raw_rows = list(response.result_rows)
+        return raw_rows