edited docker file to set env variables

docker-compose.yml

@@ -7,7 +7,6 @@ services: # definisce servizi
       - '3000:3000'
     volumes: # dove salvare affinché sopravviva al container
       - grafana-storage:/var/lib/grafana
-      - ./grafana-provisioning:/etc/grafana/provisioning # Optional: for provisioning
     environment:
       - GF_INSTALL_PLUGINS= #grafana-infinity-datasource # Install the Infinity plugin
   prometheus:

env_config.sh

@@ -1,6 +1,6 @@
 export MODEL_SOURCE="hf"
 export EVAL_SAMPLE_SIZE=100
-export EVAL_PERIOD_MIN=30
+export EVAL_PERIOD_MIN=1
 export EVAL_BATCH_SIZE=64
 export TRAIN_FRACTION_SIZE=0.2
 export EVAL_FRACTION_SIZE=0.4

prometheus.yml

@@ -1,5 +1,5 @@
 global:
-  scrape_interval: 60s   # più gentile verso HF
+  scrape_interval: 60s
 
 scrape_configs:
   - job_name: "fastapi_hf"
@@ -8,8 +8,4 @@ scrape_configs:
     static_configs:
       - targets:
           #- "host.docker.internal:8000"
-          - "lucabadiali-ml-ops-project.hf.space:443"
-    # Se l#a Space è privata, aggiungi:
-    # authorization:
-    #   type: Bearer
-    #   credentials: "hf_XXXXXXXXXXXX"   # token read-only
+          - "lucabadiali-ml-ops-project.hf.space:443"

src/app/config.py

@@ -10,7 +10,7 @@ MODEL_SOURCE = ModelSource(os.getenv("MODEL_SOURCE", "hf"))
 HF_MODEL = f"cardiffnlp/twitter-roberta-base-sentiment-latest"
 DATASET_PATH = Path("data/dataset")
 EVAL_SAMPLE_SIZE = int(os.getenv("EVAL_SAMPLE_SIZE", "100"))
-EVAL_PERIOD_MIN = float(os.getenv("EVAL_PERIOD_MIN", "30"))
+EVAL_PERIOD_MIN = float(os.getenv("EVAL_PERIOD_MIN", "1"))
 EVAL_BATCH_SIZE = int(os.getenv("EVAL_BATCH_SIZE", "64"))
 TRAIN_FRACTION_SIZE = float(os.getenv("TRAIN_FRACTION_SIZE", "0.2"))
 EVAL_FRACTION_SIZE = float(os.getenv("EVAL_FRACTION_SIZE", "0.4"))