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topicBuzz

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Integrated a whole lot of supabase and more stateful and reading stuff

273764c 11 months ago

9.97 kB

import streamlit as st
import networkx as nx
import pickle
import os
import json
from pyvis.network import Network
import streamlit.components.v1 as components

# --- CONFIGURATION ---
CACHE_FILE = "mastodon_network.pkl"
LABELS_FILE = "topic_labels.json"

# --- PAGE CONFIG ---
st.set_page_config(layout="wide", page_title="Topic Pathfinder")
st.title("🔗 Topic Pathfinder")
st.markdown("Find the **strongest social bridge** between two topics through shared users.")

# --- 1. LOAD DATA ---
@st.cache_resource
def load_data():
    data = {"G": None, "labels": {}}
    
    if os.path.exists(CACHE_FILE):
        with open(CACHE_FILE, 'rb') as f:
            data["G"] = pickle.load(f)
            
    if os.path.exists(LABELS_FILE):
        with open(LABELS_FILE, 'r') as f:
            data["labels"] = json.load(f)
            
    return data

data = load_data()
G = data["G"]
labels_map = data["labels"]

if G is None:
    st.error(f"Cache file '{CACHE_FILE}' not found!")
    st.stop()

OUTLIER_ID = "Topic_0" 

if G.has_node(OUTLIER_ID):
    G.remove_node(OUTLIER_ID)

# --- HELPER: Compute Costs ---
# We invert the weight so that High Posts = Low Cost (Short Path)
# This trick lets Dijkstra's algorithm find the "Strongest" path
for u, v, d in G.edges(data=True):
    weight = d.get('weight', 1)
    # Avoid division by zero, prioritize heavy weights
    # 1 post = cost 1.0
    # 100 posts = cost 0.01
    d['cost'] = 1 / weight 

# --- HELPER: Labeling ---
def get_label(node_id):
    if node_id.startswith("Topic_") and node_id in labels_map:
        return f"{labels_map[node_id]} ({node_id})"
    if node_id.startswith("User_"):
        return f"User {node_id.replace('User_', '')}"
    return node_id

# --- SIDEBAR SELECTION ---
st.sidebar.header("Select Path Endpoints")

# Filter for Topic Nodes only
topic_nodes = [n for n in G.nodes if n.startswith("Topic_")]
topic_options = {get_label(n): n for n in topic_nodes}
sorted_options = sorted(topic_options.keys())

start_label = st.sidebar.selectbox("Start Topic", sorted_options, index=0)
end_label = st.sidebar.selectbox("End Topic", sorted_options, index=len(sorted_options)-1)

start_node = topic_options[start_label]
end_node = topic_options[end_label]

if st.sidebar.button("Find Connection"):
    if start_node == end_node:
        st.warning("Start and End topics are the same!")
        st.stop()

    try:
        # 1. Calculate STRONGEST Path (Weighted by activity)
        path_strongest = nx.shortest_path(G, source=start_node, target=end_node, weight='cost')
        
        # 2. Calculate SHORTEST Path (Fewest hops/intermediaries)
        path_shortest = nx.shortest_path(G, source=start_node, target=end_node) # No weight = BFS

        # Create Tabs for the two views
        tab1, tab2 = st.tabs(["💪 Strongest Connection", "⚡ Shortest Connection"])

        # ==========================================
        # TAB 1: STRONGEST CONNECTION (Your original logic)
        # ==========================================
        with tab1:
            st.subheader("Strongest Social Bridge (Most Activity)")
            st.caption("This path follows the users with the highest post counts.")

            # --- Visualization Pipeline (Strongest) ---
            steps = []
            total_posts = 0
            
            with st.container():
                col_list = st.columns(len(path_strongest))
                
                for i, node in enumerate(path_strongest):
                    # Calculate edge weight to previous node
                    posts_in = 0
                    if i > 0:
                        prev = path_strongest[i-1]
                        posts_in = G[prev][node]['weight']
                        total_posts += posts_in

                    # Display Node
                    clean_name = get_label(node)
                    is_user = node.startswith("User_")
                    
                    with col_list[i]:
                        if is_user:
                            st.markdown(f"""
                            <div style="text-align: center; border: 1px solid #444; border-radius: 10px; padding: 10px; background-color: #222;">
                                <div style="font-size: 20px;">👤</div>
                                <div style="font-size: 14px; color: #97C2FC;">{clean_name}</div>
                            </div>
                            """, unsafe_allow_html=True)
                            if i < len(path_strongest)-1:
                                st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'></div>", unsafe_allow_html=True)
                        else:
                            color = "#00FF00" if i == 0 or i == len(path_strongest)-1 else "#FB7E81"
                            st.markdown(f"""
                            <div style="text-align: center; border: 2px solid {color}; border-radius: 10px; padding: 10px; background-color: #333;">
                                <div style="font-size: 20px;">📚</div>
                                <div style="font-size: 14px; font-weight: bold;">{clean_name.split('(')[0]}</div>
                            </div>
                            """, unsafe_allow_html=True)
                            if i < len(path_strongest)-1:
                                st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'></div>", unsafe_allow_html=True)

            # --- PyVis Graph (Strongest) ---
            st.divider()
            nt = Network(height="500px", width="100%", bgcolor="#222222", font_color="white")
            
            for node in path_strongest:
                attr = G.nodes[node]
                label = get_label(node).split('(')[0]
                if node == start_node or node == end_node:
                    nt.add_node(node, label=label, color="#00FF00", size=30)
                elif node.startswith("User_"):
                    nt.add_node(node, label=label, color="#97C2FC", size=15)
                else:
                    nt.add_node(node, label=label, color="#FB7E81", size=20)

            for i in range(len(path_strongest) - 1):
                u = path_strongest[i]
                v = path_strongest[i+1]
                weight = G[u][v]['weight']
                nt.add_edge(u, v, value=weight, title=f"{weight} posts", color="#FFFF00")

            nt.barnes_hut()
            nt.save_graph("strongest_graph.html")
            with open("strongest_graph.html", 'r', encoding='utf-8') as f:
                components.html(f.read(), height=520)

        # ==========================================
        # TAB 2: SHORTEST CONNECTION (New Logic)
        # ==========================================
        with tab2:
            st.subheader("Shortest Connection Graph (Fewest Hops)")
            st.caption("This path finds the quickest way to connect topics, even if the users aren't very active.")

            # --- Visualization Pipeline (Shortest) ---
            with st.container():
                col_list_s = st.columns(len(path_shortest))
                for i, node in enumerate(path_shortest):
                    clean_name = get_label(node)
                    is_user = node.startswith("User_")
                    
                    with col_list_s[i]:
                        if is_user:
                             st.markdown(f"""
                            <div style="text-align: center; border: 1px solid #444; border-radius: 10px; padding: 10px; background-color: #222;">
                                <div style="font-size: 20px;">👤</div>
                                <div style="font-size: 12px; color: #97C2FC;">{clean_name}</div>
                            </div>""", unsafe_allow_html=True)
                        else:
                             st.markdown(f"""
                            <div style="text-align: center; border: 2px solid #888; border-radius: 10px; padding: 10px; background-color: #333;">
                                <div style="font-size: 20px;">📚</div>
                                <div style="font-size: 12px; font-weight: bold;">{clean_name.split('(')[0]}</div>
                            </div>""", unsafe_allow_html=True)
                    
                        # if i < len(path_shortest)-1:
                        #         st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'>➜</div>", unsafe_allow_html=True)

            # --- PyVis Graph (Shortest) ---
            st.divider()
            nt_short = Network(height="500px", width="100%", bgcolor="#222222", font_color="white")
            
            for node in path_shortest:
                attr = G.nodes[node]
                label = get_label(node).split('(')[0]
                if node == start_node or node == end_node:
                    nt_short.add_node(node, label=label, color="#00FF00", size=30)
                elif node.startswith("User_"):
                    nt_short.add_node(node, label=label, color="#97C2FC", size=15)
                else:
                    nt_short.add_node(node, label=label, color="#FB7E81", size=20)

            for i in range(len(path_shortest) - 1):
                u = path_shortest[i]
                v = path_shortest[i+1]
                weight = G[u][v]['weight']
                # Use CYAN for the shortest path to distinguish it
                nt_short.add_edge(u, v, value=1, title=f"{weight} posts", color="#00FFFF")

            nt_short.barnes_hut()
            nt_short.save_graph("shortest_graph.html")
            with open("shortest_graph.html", 'r', encoding='utf-8') as f:
                components.html(f.read(), height=520)

    except nx.NetworkXNoPath:
        st.error(f"No path found between **{start_label}** and **{end_label}**. These communities might be completely disconnected.")

else:
    st.info("👈 Select two topics from the sidebar and click **Find Connection**.")

	import streamlit as st
	import networkx as nx
	import pickle
	import os
	import json
	from pyvis.network import Network
	import streamlit.components.v1 as components

	# --- CONFIGURATION ---
	CACHE_FILE = "mastodon_network.pkl"
	LABELS_FILE = "topic_labels.json"

	# --- PAGE CONFIG ---
	st.set_page_config(layout="wide", page_title="Topic Pathfinder")
	st.title("🔗 Topic Pathfinder")
	st.markdown("Find the strongest social bridge between two topics through shared users.")

	# --- 1. LOAD DATA ---
	@st.cache_resource
	def load_data():
	data = {"G": None, "labels": {}}

	if os.path.exists(CACHE_FILE):
	with open(CACHE_FILE, 'rb') as f:
	data["G"] = pickle.load(f)

	if os.path.exists(LABELS_FILE):
	with open(LABELS_FILE, 'r') as f:
	data["labels"] = json.load(f)

	return data

	data = load_data()
	G = data["G"]
	labels_map = data["labels"]

	if G is None:
	st.error(f"Cache file '{CACHE_FILE}' not found!")
	st.stop()

	OUTLIER_ID = "Topic_0"

	if G.has_node(OUTLIER_ID):
	G.remove_node(OUTLIER_ID)

	# --- HELPER: Compute Costs ---
	# We invert the weight so that High Posts = Low Cost (Short Path)
	# This trick lets Dijkstra's algorithm find the "Strongest" path
	for u, v, d in G.edges(data=True):
	weight = d.get('weight', 1)
	# Avoid division by zero, prioritize heavy weights
	# 1 post = cost 1.0
	# 100 posts = cost 0.01
	d['cost'] = 1 / weight

	# --- HELPER: Labeling ---
	def get_label(node_id):
	if node_id.startswith("Topic_") and node_id in labels_map:
	return f"{labels_map[node_id]} ({node_id})"
	if node_id.startswith("User_"):
	return f"User {node_id.replace('User_', '')}"
	return node_id

	# --- SIDEBAR SELECTION ---
	st.sidebar.header("Select Path Endpoints")

	# Filter for Topic Nodes only
	topic_nodes = [n for n in G.nodes if n.startswith("Topic_")]
	topic_options = {get_label(n): n for n in topic_nodes}
	sorted_options = sorted(topic_options.keys())

	start_label = st.sidebar.selectbox("Start Topic", sorted_options, index=0)
	end_label = st.sidebar.selectbox("End Topic", sorted_options, index=len(sorted_options)-1)

	start_node = topic_options[start_label]
	end_node = topic_options[end_label]

	if st.sidebar.button("Find Connection"):
	if start_node == end_node:
	st.warning("Start and End topics are the same!")
	st.stop()

	try:
	# 1. Calculate STRONGEST Path (Weighted by activity)
	path_strongest = nx.shortest_path(G, source=start_node, target=end_node, weight='cost')

	# 2. Calculate SHORTEST Path (Fewest hops/intermediaries)
	path_shortest = nx.shortest_path(G, source=start_node, target=end_node) # No weight = BFS

	# Create Tabs for the two views
	tab1, tab2 = st.tabs(["💪 Strongest Connection", "⚡ Shortest Connection"])

	# ==========================================
	# TAB 1: STRONGEST CONNECTION (Your original logic)
	# ==========================================
	with tab1:
	st.subheader("Strongest Social Bridge (Most Activity)")
	st.caption("This path follows the users with the highest post counts.")

	# --- Visualization Pipeline (Strongest) ---
	steps = []
	total_posts = 0

	with st.container():
	col_list = st.columns(len(path_strongest))

	for i, node in enumerate(path_strongest):
	# Calculate edge weight to previous node
	posts_in = 0
	if i > 0:
	prev = path_strongest[i-1]
	posts_in = G[prev][node]['weight']
	total_posts += posts_in

	# Display Node
	clean_name = get_label(node)
	is_user = node.startswith("User_")

	with col_list[i]:
	if is_user:
	st.markdown(f"""
	<div style="text-align: center; border: 1px solid #444; border-radius: 10px; padding: 10px; background-color: #222;">
	<div style="font-size: 20px;">👤</div>
	<div style="font-size: 14px; color: #97C2FC;">{clean_name}</div>
	</div>
	""", unsafe_allow_html=True)
	if i < len(path_strongest)-1:
	st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'></div>", unsafe_allow_html=True)
	else:
	color = "#00FF00" if i == 0 or i == len(path_strongest)-1 else "#FB7E81"
	st.markdown(f"""
	<div style="text-align: center; border: 2px solid {color}; border-radius: 10px; padding: 10px; background-color: #333;">
	<div style="font-size: 20px;">📚</div>
	<div style="font-size: 14px; font-weight: bold;">{clean_name.split('(')[0]}</div>
	</div>
	""", unsafe_allow_html=True)
	if i < len(path_strongest)-1:
	st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'></div>", unsafe_allow_html=True)

	# --- PyVis Graph (Strongest) ---
	st.divider()
	nt = Network(height="500px", width="100%", bgcolor="#222222", font_color="white")

	for node in path_strongest:
	attr = G.nodes[node]
	label = get_label(node).split('(')[0]
	if node == start_node or node == end_node:
	nt.add_node(node, label=label, color="#00FF00", size=30)
	elif node.startswith("User_"):
	nt.add_node(node, label=label, color="#97C2FC", size=15)
	else:
	nt.add_node(node, label=label, color="#FB7E81", size=20)

	for i in range(len(path_strongest) - 1):
	u = path_strongest[i]
	v = path_strongest[i+1]
	weight = G[u][v]['weight']
	nt.add_edge(u, v, value=weight, title=f"{weight} posts", color="#FFFF00")

	nt.barnes_hut()
	nt.save_graph("strongest_graph.html")
	with open("strongest_graph.html", 'r', encoding='utf-8') as f:
	components.html(f.read(), height=520)

	# ==========================================
	# TAB 2: SHORTEST CONNECTION (New Logic)
	# ==========================================
	with tab2:
	st.subheader("Shortest Connection Graph (Fewest Hops)")
	st.caption("This path finds the quickest way to connect topics, even if the users aren't very active.")

	# --- Visualization Pipeline (Shortest) ---
	with st.container():
	col_list_s = st.columns(len(path_shortest))
	for i, node in enumerate(path_shortest):
	clean_name = get_label(node)
	is_user = node.startswith("User_")

	with col_list_s[i]:
	if is_user:
	st.markdown(f"""
	<div style="text-align: center; border: 1px solid #444; border-radius: 10px; padding: 10px; background-color: #222;">
	<div style="font-size: 20px;">👤</div>
	<div style="font-size: 12px; color: #97C2FC;">{clean_name}</div>
	</div>""", unsafe_allow_html=True)
	else:
	st.markdown(f"""
	<div style="text-align: center; border: 2px solid #888; border-radius: 10px; padding: 10px; background-color: #333;">
	<div style="font-size: 20px;">📚</div>
	<div style="font-size: 12px; font-weight: bold;">{clean_name.split('(')[0]}</div>
	</div>""", unsafe_allow_html=True)

	# if i < len(path_shortest)-1:
	# st.markdown(f"<div style='text-align:center; font-size: 20px; color: #aaa;'>➜</div>", unsafe_allow_html=True)

	# --- PyVis Graph (Shortest) ---
	st.divider()
	nt_short = Network(height="500px", width="100%", bgcolor="#222222", font_color="white")

	for node in path_shortest:
	attr = G.nodes[node]
	label = get_label(node).split('(')[0]
	if node == start_node or node == end_node:
	nt_short.add_node(node, label=label, color="#00FF00", size=30)
	elif node.startswith("User_"):
	nt_short.add_node(node, label=label, color="#97C2FC", size=15)
	else:
	nt_short.add_node(node, label=label, color="#FB7E81", size=20)

	for i in range(len(path_shortest) - 1):
	u = path_shortest[i]
	v = path_shortest[i+1]
	weight = G[u][v]['weight']
	# Use CYAN for the shortest path to distinguish it
	nt_short.add_edge(u, v, value=1, title=f"{weight} posts", color="#00FFFF")

	nt_short.barnes_hut()
	nt_short.save_graph("shortest_graph.html")
	with open("shortest_graph.html", 'r', encoding='utf-8') as f:
	components.html(f.read(), height=520)

	except nx.NetworkXNoPath:
	st.error(f"No path found between {start_label} and {end_label}. These communities might be completely disconnected.")

	else:
	st.info("👈 Select two topics from the sidebar and click Find Connection.")