import streamlit as st
import streamlit.components.v1 as components

from metaflow import Flow, Run, namespace
from metaflow.cards import get_cards
from metaflow.integrations import ArgoEvent

CARD_PREFIX = '/p/default/api/flows'
RUN_PREFIX = '/dashboard/runs/p/default'

def card_url(path):
    parts = path.split('/')
    parts[-1] = parts[-1].replace('-', '/').replace('.html', '')
    return '/'.join([CARD_PREFIX] + parts)

namespace(None)
run = Flow("ForecastFlow").latest_successful_run
st.markdown(f"#### Inspecting run\n[**{run.pathspec}**]({RUN_PREFIX}/{run.pathspec})")
deployed = False
if 'deployed' in run.tags:
    st.markdown("✅ Deployed")   
    deployed=True
else:
    st.markdown("Not deployed")
path = get_cards(run['end'].task)[0].path
components.iframe(card_url(path), height=500)

if st.button(label='Deploy', type='primary', icon='🚀', disabled=deployed):
    # you can call any external system here, e.g. a CI/CD, to start a
    # deployment, or trigger a Metaflow run through an event like below:
    event = ArgoEvent('deploy_request').publish({'run': run.pathspec})
    run.add_tag("deployed")
    st.toast(f"Deployment request published: {event}")
    st.rerun()