preparing pre-flight requests

backend/app/plan/router.py

@@ -43,6 +43,18 @@ async def trigger_plan_entrypoint(body: PlanTriggerRequest):
         logger.error("Failed to parse request body: %s", e)
         return {"message": "Invalid request"}, 400
 
+    # TODO: Warm up the lambdas here
+    # from backend.ml_models.api import ModelApi
+    # model_api = ModelApi(
+    #     portfolio_id=body.portfolio_id,
+    #     timestamp="2020-01-01T00:00:00",
+    #     prediction_buckets=[],
+    #     max_retries=1
+    # )
+    # await model_api.async_warm_up_lambdas(
+    #     model_prefies=model_api.KWH_MODEL_PREFIXES + model_api.MODEL_PREFIXES
+    # )
+
     # If file_format is domna_asset_list and type is xlsx, read and chunk it
     if data.get("file_format") == "domna_asset_list" and data.get("file_type") == "xlsx":
         try:

backend/ml_models/api.py

@@ -257,8 +257,10 @@ class ModelApi:
         model_prefixes = self.MODEL_PREFIXES if model_prefies is None else model_prefies
         session = self.get_aiohttp_session()
         tasks = [
-            self._send_warm_up_request(session, f"{self.base_url}/{self.MODEL_URLS[model_prefix]}/predict",
-                                       model_prefix)
+            self._send_warm_up_request(
+                session, f"{self.base_url}/{self.MODEL_URLS[model_prefix]}/predict",
+                model_prefix
+            )
             for model_prefix in model_prefixes
         ]
         await asyncio.gather(*tasks, return_exceptions=True)
@@ -271,7 +273,10 @@ class ModelApi:
                 "file_location": "s3://warm-up-placeholder",
                 "portfolio_id": 0,
                 "property_id": "",
-                "created_at": "2020-01-01T00:00:00"
+                "created_at": "2020-01-01T00:00:00",
+                "warm": True
+                # The presence of this key will send the api down a specific warm up route, to call
+                # prediction and load the font manager, because that is a key bottleneck for cold starts
             }
             async with session.post(url, json=json_payload, timeout=10) as response:
                 text = await response.text()