Update app.py

app.py

@@ -2,7 +2,7 @@ import os
 from collections.abc import Iterator
 from threading import Thread
 import networkx as nx
-from pyvis.network import Network
+import matplotlib.pyplot as plt
 import gradio as gr
 import spaces
 import torch
@@ -37,10 +37,18 @@ def generate_knowledge_graph():
     G.add_edge("AI", "ML")
     G.add_edge("ML", "DL")
 
-    # Visualize the graph using pyvis
-    net = Network(notebook=True, cdn_resources='remote')
-    net.from_nx(G)
-    net.show("knowledge_graph.html")
+    # Draw the graph using matplotlib
+    plt.figure(figsize=(8, 6))
+    pos = nx.spring_layout(G)
+    nx.draw(G, pos, with_labels=True, node_size=3000, node_color="lightblue", font_size=10, font_weight="bold")
+    plt.title("Knowledge Graph")
+
+    # Save the graph as a PDF
+    pdf_path = "knowledge_graph.pdf"
+    plt.savefig(pdf_path, format="pdf")
+    plt.close()
+
+    return pdf_path
 
 @spaces.GPU(duration=120)
 def generate(
@@ -89,8 +97,8 @@ def generate(
     # Ensure the thread is joined after completion
     t.join()
 
-# Generate the knowledge graph HTML file
-generate_knowledge_graph()
+# Generate the knowledge graph PDF file
+pdf_path = generate_knowledge_graph()
 
 demo = gr.ChatInterface(
     fn=generate,
@@ -130,7 +138,7 @@ demo = gr.ChatInterface(
             step=0.05,
             value=1.2,
         ),
-        gr.HTML("<a href='knowledge_graph.html' target='_blank'>View Knowledge Graph</a>")
+        gr.File(label="Download Knowledge Graph (PDF)", value=pdf_path, visible=True),
     ],
     stop_btn=None,
     examples=[