app.py

import streamlit as st
from graphviz import Digraph
import time
import random

# Define the emoji to use for the swim lanes
SWIM_LANES = {
    "Data Pipelines": "🔍",
    "Build and Train Models": "🧪",
    "Deploy and Predict": "🚀"
}

# Define the graph structure
graph = Digraph()
graph.attr(rankdir="TB") # Top to Bottom or LR Left to Right
graph.attr(fontsize="20")
graph.attr(compound="true")
graph.attr(nodesep="0.5")

# Define the nodes
nodes = [
    "📊 Data Collection",
    "🧹 Data Cleaning",
    "🔧 Data Transformation",
    "🔎 Feature Engineering",
    "⚙️ Model Selection",
    "🎓 Model Training",
    "🚢 Model Deployment",
    "📡 Model Serving",
    "🔮 Predictions",
    "👍 Feedback Collection",
    "🤔 Feedback Processing",
    "✍️ Model Updating"
]

for node in nodes:
    graph.node(node)

# Add the swim lanes
with graph.subgraph(name="cluster_0") as c:
    c.attr(rank="1")
    c.attr(label=SWIM_LANES["Data Pipelines"])
    c.edge("📊 Data Collection", "🧹 Data Cleaning", style="invis")
    c.edge("🧹 Data Cleaning", "🔧 Data Transformation", style="invis")

with graph.subgraph(name="cluster_1") as c:
    c.attr(rank="2")
    c.attr(label=SWIM_LANES["Build and Train Models"])
    c.edge("🔎 Feature Engineering", "⚙️ Model Selection", style="invis")
    c.edge("⚙️ Model Selection", "🎓 Model Training", style="invis")

with graph.subgraph(name="cluster_2") as c:
    c.attr(rank="3")
    c.attr(label=SWIM_LANES["Deploy and Predict"])
    c.edge("🚢 Model Deployment", "📡 Model Serving", style="invis")
    c.edge("📡 Model Serving", "🔮 Predictions", style="invis")

with graph.subgraph(name="cluster_3") as c:
    c.attr(rank="4")
    c.attr(label="Reinforcement Learning Human Feedback")
    c.edge("🔮 Predictions", "👍 Feedback Collection", style="invis")
    c.edge("👍 Feedback Collection", "🤔 Feedback Processing", style="invis")
    c.edge("🤔 Feedback Processing", "✍️ Model Updating", style="invis")

def render_graph():
    st.graphviz_chart(graph.source)

def update_graph():
    for i in range(10):
        # Randomly select two nodes and add an edge between them
        node1, node2 = random.sample(nodes, 2)
        graph.edge(node1, node2)
        
        # Render the updated graph
        render_graph()
        
        # Wait for 1 second
        time.sleep(1)
        
# Render the initial graph
render_graph()

# Update the graph every second for 60 seconds
update_graph()