Mlhbdapp New -

app = Flask(__name__)

volumes: mlhb-data: docker compose up -d # Wait a few seconds for the DB init... docker compose logs -f mlhbdapp-server You should see a log line like:

# app.py from flask import Flask, request, jsonify import mlhbdapp

# Initialise the MLHB agent (auto‑starts background thread) mlhbdapp.init( service_name="demo‑sentiment‑api", version="v0.1.3", tags="team": "nlp", # optional: custom endpoint for the server endpoint="http://localhost:8080/api/v1/telemetry" )

# Record metrics request_counter.inc() mlhbdapp.Gauge("inference_latency_ms").set(latency * 1000) mlhbdapp.Gauge("model_accuracy").set(0.92) # just for demo

# Example metric: count of requests request_counter = mlhbdapp.Counter("api_requests_total")

app = Flask(__name__)

volumes: mlhb-data: docker compose up -d # Wait a few seconds for the DB init... docker compose logs -f mlhbdapp-server You should see a log line like:

# app.py from flask import Flask, request, jsonify import mlhbdapp

# Initialise the MLHB agent (auto‑starts background thread) mlhbdapp.init( service_name="demo‑sentiment‑api", version="v0.1.3", tags="team": "nlp", # optional: custom endpoint for the server endpoint="http://localhost:8080/api/v1/telemetry" )

# Record metrics request_counter.inc() mlhbdapp.Gauge("inference_latency_ms").set(latency * 1000) mlhbdapp.Gauge("model_accuracy").set(0.92) # just for demo

# Example metric: count of requests request_counter = mlhbdapp.Counter("api_requests_total")