test bamboo build

image_prediction/flask.py

@@ -3,7 +3,6 @@ import traceback
 from typing import Callable
 
 from flask import Flask, request, jsonify
-from prometheus_client import generate_latest, CollectorRegistry, Summary
 
 from image_prediction.utils import get_logger
 
@@ -35,10 +34,6 @@ def wrap_in_process(func_to_wrap):
 
 def make_prediction_server(predict_fn: Callable):
     app = Flask(__name__)
-    registry = CollectorRegistry(auto_describe=True)
-    metric = Summary(
-        f"redactmanager_imageClassification_seconds", f"Time spent on image-service classification.", registry=registry
-    )
 
     @app.route("/ready", methods=["GET"])
     def ready():
@@ -59,7 +54,6 @@ def make_prediction_server(predict_fn: Callable):
 
     @app.route("/predict", methods=["POST"])
     @app.route("/", methods=["POST"])
-    @metric.time()
     def predict():
 
         # Tensorflow does not free RAM. Workaround: Run prediction function (which instantiates a model) in sub-process.
@@ -77,8 +71,4 @@ def make_prediction_server(predict_fn: Callable):
             logger.error("Analysis failed.")
             return __failure()
 
-    @app.route("/prometheus", methods=["GET"])
-    def prometheus():
-        return generate_latest(registry=registry)
-
     return app

requirements.txt

@@ -20,5 +20,4 @@ coverage==6.3.2
 Pillow==9.1.0
 PDFNetPython3==9.1.0
 pdf2image==1.16.0
-frozendict==2.3.0
-prometheus-client==0.13.1
+frozendict==2.3.0