connect to pw-recsys to get rankings for user

app.py

@@ -4,6 +4,8 @@ from pyvis.network import Network
 import pickle
 import math
 import random
+import requests
+import os
 
 # Dictionary to map brands to their respective pickle files
 BRAND_GRAPHS = {
@@ -13,18 +15,18 @@ BRAND_GRAPHS = {
     'guitareo': 'guitareo_pop_items_labels.pkl'
 }
 
+# API Authorization Token
+AUTH_TOKEN = os.getenv('HF_TOKEN')
+
+API_URL = "https://MusoraProductDepartment-PWGenerator.hf.space/rank_items/"
+
+
 @st.cache_resource
 def load_graph(brand):
-    """
-    Load the graph for the selected brand.
-    """
     with open(BRAND_GRAPHS[brand], 'rb') as f:
         return pickle.load(f)
 
 def filter_graph(graph, node_threshold=10, edge_threshold=5):
-    """
-    Filters the graph to include only popular nodes and edges.
-    """
     popular_nodes = [
         node for node in graph.nodes
         if graph.degree(node) >= node_threshold
@@ -38,7 +40,49 @@ def filter_graph(graph, node_threshold=10, edge_threshold=5):
 
     return filtered_graph
 
-def dynamic_visualize_graph(graph, start_node, layers=3, top_k=5, show_titles=False):
+def get_rankings_from_api(brand, user_id, content_ids):
+    """
+    Call the rank_items API to fetch rankings for the given user and content IDs.
+    """
+    try:
+        payload = {
+            "brand": brand.upper(),
+            "user_id": user_id,
+            "content_ids": content_ids
+        }
+        headers = {
+            "Authorization": f"Bearer {AUTH_TOKEN}",
+            "accept": "application/json",
+            "Content-Type": "application/json"
+        }
+        response = requests.post(API_URL, json=payload, headers=headers)
+        response.raise_for_status()
+        rankings = response.json()
+        return rankings
+    except Exception as e:
+        st.error(f"Error calling rank_items API: {e}")
+        return {}
+
+
+def rank_to_color(rank, max_rank):
+    """
+    Map a rank to a grayscale color, where dark gray indicates high relevance (low rank),
+    and light gray indicates low relevance (high rank).
+
+    Parameters:
+        rank (int): The rank of the item.
+        max_rank (int): The maximum rank (for normalizing the gradient).
+
+    Returns:
+        str: Hex color code for the grayscale shade.
+    """
+    if rank > max_rank:  # Handle items without ranking
+        return "#E8E8E8"  # Very light gray for unranked items
+    intensity = int(55 + (rank / max_rank) * 200)  # Scale intensity (darker for lower ranks)
+    return f"rgb({intensity}, {intensity}, {intensity})"  # Grayscale
+
+
+def dynamic_visualize_graph(graph, start_node, layers=3, top_k=5, show_titles=False, rankings=None):
     net = Network(notebook=False, width="100%", height="600px", directed=True)
     net.set_options("""
     var options = {
@@ -55,18 +99,27 @@ def dynamic_visualize_graph(graph, start_node, layers=3, top_k=5, show_titles=Fa
     added_edges = set()
     current_nodes = [int(start_node)]
 
+    max_rank = len(rankings) if rankings else 0
+
     # Add the starting node, color it red, and include a tooltip
     start_title = graph.nodes[int(start_node)].get('title', 'No title available')
     start_in_degree = graph.in_degree(int(start_node))
     start_out_degree = graph.out_degree(int(start_node))
     start_node_size = (start_in_degree + start_out_degree) * 0.15
-    label = str(start_node) if not show_titles else f"{str(start_node)}: {start_title[:15]}..."  # Adjust title length
+    start_rank = rankings.index(int(start_node)) if rankings and int(start_node) in rankings else max_rank + 1
+    if rankings:
+        start_border_color = rank_to_color(start_rank, max_rank)
+    else:
+        start_border_color = 'darkblue'
+    label = str(start_node) if not show_titles else f"{str(start_node)}: {start_title[:15]}..."
     net.add_node(
         int(start_node),
         label=label,
-        color="darkblue",
-        title=f"{start_title} In-degree: {start_in_degree}, Out-degree: {start_out_degree}",
-        size=start_node_size
+        color={"background": "darkblue", "border": start_border_color},
+        title=f"{start_title}, In-degree: {start_in_degree}, Out-degree: {start_out_degree}, Rank: {start_rank}",
+        size=start_node_size,
+        borderWidth=3,
+        borderWidthSelected=6
     )
     visited_nodes.add(int(start_node))
 
@@ -85,15 +138,24 @@ def dynamic_visualize_graph(graph, start_node, layers=3, top_k=5, show_titles=Fa
                     neighbor_in_degree = graph.in_degree(neighbor)
                     neighbor_out_degree = graph.out_degree(neighbor)
                     neighbor_size = (neighbor_in_degree + neighbor_out_degree) * 0.15
+                    neighbor_rank = rankings.index(neighbor) if rankings and neighbor in rankings else max_rank + 1
+
                     node_color = 'red' if neighbor_in_degree > neighbor_out_degree * 1.5 else \
-                                 'green' if neighbor_out_degree > neighbor_in_degree * 1.5 else 'lightblue'
+                        'green' if neighbor_out_degree > neighbor_in_degree * 1.5 else 'lightblue'
+                    if rankings:
+                        neighbor_border_color = rank_to_color(neighbor_rank, max_rank)
+                    else:
+                        neighbor_border_color = node_color
+
                     label = str(neighbor) if not show_titles else f"{str(neighbor)}: {neighbor_title[:15]}..."
                     net.add_node(
                         neighbor,
                         label=label,
-                        title=f"{neighbor_title} In-degree: {neighbor_in_degree}, Out-degree: {neighbor_out_degree}",
+                        title=f"{neighbor_title}, In-degree: {neighbor_in_degree}, Out-degree: {neighbor_out_degree}, Rank: {neighbor_rank}",
                         size=neighbor_size,
-                        color=node_color
+                        color={"background": node_color, "border": neighbor_border_color},
+                        borderWidth=3,
+                        borderWidthSelected=6
                     )
                 edge = (node, neighbor)
                 if edge not in added_edges:
@@ -109,7 +171,7 @@ def dynamic_visualize_graph(graph, start_node, layers=3, top_k=5, show_titles=Fa
     st.components.v1.html(html_content, height=600, scrolling=False)
 
 
-st.title("Popular Path Expansion")
+st.title("Popular Path Expansion + Personalization")
 
 # Brand Selection
 selected_brand = st.selectbox("Select a brand:", options=list(BRAND_GRAPHS.keys()))
@@ -136,6 +198,10 @@ start_node = st.number_input(
     step=1
 )
 
+# Input: Student ID
+student_id = st.text_input("Enter a student ID (optional):", value="")
+
+
 # Toggle for showing content titles
 show_titles = st.checkbox("Show content titles", value=False)
 
@@ -144,11 +210,19 @@ node_degree_threshold = 1
 edge_weight_threshold = 1
 G_filtered = filter_graph(G, node_threshold=node_degree_threshold, edge_threshold=edge_weight_threshold)
 
+# Fetch rankings if student ID is provided
+rankings = {}
+if student_id:
+    content_ids = list(G_filtered.nodes)
+    rankings = get_rankings_from_api(selected_brand, int(student_id), content_ids)
+    if rankings:
+        rankings = rankings['ranked_content_ids']
+#print(rankings)
 layers = st.slider("Depth to explore:", 1, 6, value=3)
 top_k = st.slider("Branching factor (per node):", 1, 6, value=3)
 
 if st.button("Expand Graph"):
     if start_node in G_filtered:
-        dynamic_visualize_graph(G_filtered, start_node, layers=layers, top_k=top_k, show_titles=show_titles)
+        dynamic_visualize_graph(G_filtered, start_node, layers=layers, top_k=top_k, show_titles=show_titles, rankings=rankings)
     else:
         st.error("The starting node is not in the graph!")