server.py

import os
from flask import Flask, send_from_directory, Response

from mlflow.server import handlers
from mlflow.server.handlers import (
    get_artifact_handler,
    _add_static_prefix,
    get_model_version_artifact_handler,
)

PROMETHEUS_EXPORTER_ENV_VAR = "prometheus_multiproc_dir"
REL_STATIC_DIR = "build"

app = Flask(__name__, static_folder=REL_STATIC_DIR)
STATIC_DIR = os.path.join(app.root_path, REL_STATIC_DIR)

for http_path, handler, methods in handlers.get_endpoints():
    app.add_url_rule(http_path, handler.__name__, handler, methods=methods)

if os.getenv(PROMETHEUS_EXPORTER_ENV_VAR):
    from mlflow.server.prometheus_exporter import activate_prometheus_exporter

    prometheus_metrics_path = os.getenv(PROMETHEUS_EXPORTER_ENV_VAR)
    if not os.path.exists(prometheus_metrics_path):
        os.makedirs(prometheus_metrics_path)
    activate_prometheus_exporter(app)


# Provide a health check endpoint to ensure the application is responsive
@app.route("/health")
def health():
    return "OK", 200


# Serve the "get-artifact" route.
@app.route(_add_static_prefix("/get-artifact"))
def serve_artifacts():
    return get_artifact_handler()

# Serve the "model-versions/get-artifact" route.
@app.route(_add_static_prefix("/model-versions/get-artifact"))
def serve_model_version_artifact():
    return get_model_version_artifact_handler()


# We expect the react app to be built assuming it is hosted at /static-files, so that requests for
# CSS/JS resources will be made to e.g. /static-files/main.css and we can handle them here.
@app.route(_add_static_prefix("/static-files/<path:path>"))
def serve_static_file(path):
    return send_from_directory(STATIC_DIR, path)


# Serve the index.html for the React App for all other routes.
@app.route(_add_static_prefix("/"))
def serve():
    if os.path.exists(os.path.join(STATIC_DIR, "index.html")):
        return send_from_directory(STATIC_DIR, "index.html")

    text = textwrap.dedent(
        """
    Unable to display MLflow UI - landing page (index.html) not found.

    You are very likely running the MLflow server using a source installation of the Python MLflow
    package.

    If you are a developer making MLflow source code changes and intentionally running a source
    installation of MLflow, you can view the UI by running the Javascript dev server:
    https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.rst#running-the-javascript-dev-server

    Otherwise, uninstall MLflow via 'pip uninstall mlflow', reinstall an official MLflow release
    from PyPI via 'pip install mlflow', and rerun the MLflow server.
    """
    )
    return Response(text, mimetype="text/plain")