awacke1/Self-Modifying-Graph-Visualization

1import streamlit as st2from graphviz import Digraph3import time4import random5 6# Define the emoji to use for the swim lanes7SWIM_LANES = {8    "Data Pipelines": "🔍",9    "Build and Train Models": "🧪",10    "Deploy and Predict": "🚀"11}12 13# Define the graph structure14graph = Digraph()15graph.attr(rankdir="TB") # Top to Bottom or LR Left to Right16graph.attr(fontsize="20")17graph.attr(compound="true")18graph.attr(nodesep="0.5")19 20# Define the nodes21nodes = [22    "📊 Data Collection",23    "🧹 Data Cleaning",24    "🔧 Data Transformation",25    "🔎 Feature Engineering",26    "⚙️ Model Selection",27    "🎓 Model Training",28    "🚢 Model Deployment",29    "📡 Model Serving",30    "🔮 Predictions",31    "👍 Feedback Collection",32    "🤔 Feedback Processing",33    "✍️ Model Updating"34]35 36for node in nodes:37    graph.node(node)38 39# Add the swim lanes40with graph.subgraph(name="cluster_0") as c:41    c.attr(rank="1")42    c.attr(label=SWIM_LANES["Data Pipelines"])43    c.edge("📊 Data Collection", "🧹 Data Cleaning", style="invis")44    c.edge("🧹 Data Cleaning", "🔧 Data Transformation", style="invis")45 46with graph.subgraph(name="cluster_1") as c:47    c.attr(rank="2")48    c.attr(label=SWIM_LANES["Build and Train Models"])49    c.edge("🔎 Feature Engineering", "⚙️ Model Selection", style="invis")50    c.edge("⚙️ Model Selection", "🎓 Model Training", style="invis")51 52with graph.subgraph(name="cluster_2") as c:53    c.attr(rank="3")54    c.attr(label=SWIM_LANES["Deploy and Predict"])55    c.edge("🚢 Model Deployment", "📡 Model Serving", style="invis")56    c.edge("📡 Model Serving", "🔮 Predictions", style="invis")57 58with graph.subgraph(name="cluster_3") as c:59    c.attr(rank="4")60    c.attr(label="Reinforcement Learning Human Feedback")61    c.edge("🔮 Predictions", "👍 Feedback Collection", style="invis")62    c.edge("👍 Feedback Collection", "🤔 Feedback Processing", style="invis")63    c.edge("🤔 Feedback Processing", "✍️ Model Updating", style="invis")64 65def render_graph():66    st.graphviz_chart(graph.source)67 68def update_graph():69    for i in range(10):70        # Randomly select two nodes and add an edge between them71        node1, node2 = random.sample(nodes, 2)72        graph.edge(node1, node2)73        74        # Render the updated graph75        render_graph()76        77        # Wait for 1 second78        time.sleep(1)79        80# Render the initial graph81render_graph()82 83# Update the graph every second for 60 seconds84update_graph()85