(feat) /predict/spend endpoint

enterprise/utils.py

@@ -251,26 +251,27 @@ def _forecast_daily_cost(data: list):
     import requests
     from datetime import datetime, timedelta
 
-    # Get the current date
-    current_date = datetime.now().date()
-
     # Get the last entry in the data
     last_entry = data[-1]
 
     # Parse the date from the last entry
     last_entry_date = datetime.strptime(last_entry["date"], "%Y-%m-%d").date()
+    # print("Last Entry Date:", last_entry_date)
 
     # Get the month of the last entry
     last_entry_month = last_entry_date.month
+    # print("Last Entry Month:", last_entry_month)
 
     # Calculate the last day of the month
     last_day_of_month = (
         datetime(last_entry_date.year, last_entry_date.month % 12 + 1, 1)
         - timedelta(days=1)
     ).day
+    # print("Last Day of Month:", last_day_of_month)
 
     # Calculate the remaining days in the month
     remaining_days = last_day_of_month - last_entry_date.day
+    # print("Remaining Days:", remaining_days)
 
     series = {}
     for entry in data:
@@ -278,7 +279,7 @@ def _forecast_daily_cost(data: list):
         spend = entry["spend"]
         series[date] = spend
 
-    payload = {"series": series, "count": 5}
+    payload = {"series": series, "count": remaining_days}
     print("Prediction Data:", payload)
 
     headers = {
@@ -294,23 +295,34 @@ def _forecast_daily_cost(data: list):
     json_response = response.json()
     forecast_data = json_response["forecast"]
 
-    print("Forecast Data:", forecast_data)
+    # print("Forecast Data:", forecast_data)
+
+    response_data = []
+    for date in forecast_data:
+        spend = forecast_data[date]
+        entry = {
+            "date": date,
+            "predicted_spend": spend,
+        }
+        response_data.append(entry)
+    # print("Response Data:", response_data)
+    return response_data
 
     # print(f"Date: {entry['date']}, Spend: {entry['spend']}, Response: {response.text}")
 
 
-_forecast_daily_cost(
-    [
-        {"date": "2022-01-01", "spend": 100},
-        {"date": "2022-01-02", "spend": 200},
-        {"date": "2022-01-03", "spend": 300},
-        {"date": "2022-01-04", "spend": 400},
-        {"date": "2022-01-05", "spend": 500},
-        {"date": "2022-01-06", "spend": 600},
-        {"date": "2022-01-07", "spend": 700},
-        {"date": "2022-01-08", "spend": 800},
-        {"date": "2022-01-09", "spend": 900},
-        {"date": "2022-01-10", "spend": 1000},
-        {"date": "2022-01-11", "spend": 50},
-    ]
-)
+# _forecast_daily_cost(
+#     [
+#         {"date": "2022-01-01", "spend": 100},
+#         {"date": "2022-01-02", "spend": 200},
+#         {"date": "2022-01-03", "spend": 300},
+#         {"date": "2022-01-04", "spend": 400},
+#         {"date": "2022-01-05", "spend": 500},
+#         {"date": "2022-01-06", "spend": 600},
+#         {"date": "2022-01-07", "spend": 700},
+#         {"date": "2022-01-08", "spend": 800},
+#         {"date": "2022-01-09", "spend": 900},
+#         {"date": "2022-01-10", "spend": 1000},
+#         {"date": "2022-01-11", "spend": 50},
+#     ]
+# )

litellm/proxy/proxy_server.py

@@ -4190,6 +4190,18 @@ async def global_spend_models(
     return response
 
 
+@router.post(
+    "/global/predict/spend/logs",
+    tags=["Budget & Spend Tracking"],
+    dependencies=[Depends(user_api_key_auth)],
+)
+async def global_predict_spend_logs(request: Request):
+    from litellm.proxy.enterprise.utils import _forecast_daily_cost
+
+    data = await request.json()
+    return _forecast_daily_cost(data)
+
+
 @router.get(
     "/daily_metrics",
     summary="Get daily spend metrics",