Update render_report.py

render_report.py

@@ -1,21 +1,23 @@
 
-
 import json
 import os
 import matplotlib.pyplot as plt
 import networkx as nx
+from html import escape
+
+def safe_escape(val):
+    return escape(str(val)) if val is not None else "N/A"
 
-# Set safe output path
 output_dir = "/tmp"
 
 # Load data
 with open(os.path.join(output_dir, "data.json"), "r", encoding="utf-8") as f:
     data = json.load(f)
 
-# Generate sentiment chart
+# Sentiment Chart
 sentiment_path = os.path.join(output_dir, "sentiment_pie_chart.png")
-labels = list(data["sentiment_overview"].keys())
-sizes = list(data["sentiment_overview"].values())
+labels = list(data.get("sentiment_overview", {}).keys())
+sizes = list(data.get("sentiment_overview", {}).values())
 colors = ['#4CAF50', '#FFC107', '#F44336']
 fig, ax = plt.subplots()
 ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140, colors=colors)
@@ -24,10 +26,10 @@ plt.title('Sentiment Overview')
 plt.savefig(sentiment_path, bbox_inches='tight')
 plt.close()
 
-# Generate network graph
+# Network Graph
 network_path = os.path.join(output_dir, "network_graph.png")
 G = nx.Graph()
-for cluster in data["network_analysis"]["clusters"]:
+for cluster in data.get("network_analysis", {}).get("clusters", []):
     nodes = cluster["nodes"]
     for i in range(len(nodes)):
         G.add_node(nodes[i])
@@ -41,11 +43,9 @@ plt.title("Network Influence Graph")
 plt.savefig(network_path, bbox_inches='tight')
 plt.close()
 
-# Format data into HTML
-from html import escape
-
+# Helper formatters
 def bullet_list(items):
-    return "\n".join(f"<li>{escape(item)}</li>" for item in items)
+    return "\n".join(f"<li>{escape(item)}<\/li>" for item in items)
 
 def user_blocks(users):
     return "\n".join(f"<p><strong>{escape(u['username'])} ({u['type']}):</strong> {escape(u['activity_summary'])}</p>" for u in users)
@@ -53,24 +53,24 @@ def user_blocks(users):
 def cluster_blocks(clusters):
     return "\n".join(f"<p><strong>{escape(c['label'])}:</strong> {escape(c['summary'])}</p>" for c in clusters)
 
-# Load dark HTML template
+# Load HTML template
 with open("osint_dark_template.html", "r", encoding="utf-8") as tpl:
     template = tpl.read()
 
+# Fill content
 html_filled = template.format(
-    summary=escape(data["summary"]),
-    topics=", ".join(escape(topic) for topic in data["top_topics"]),
-    users=user_blocks(data["notable_users"]),
-    clusters=cluster_blocks(data["network_analysis"]["clusters"]),
-    positive=data["sentiment_overview"]["positive"],
-    neutral=data["sentiment_overview"]["neutral"],
-    negative=data["sentiment_overview"]["negative"],
-    flags=bullet_list(data["risk_flags"]),
-    start=escape(data["timestamp_range"]["from"]),
-    end=escape(data["timestamp_range"]["to"])
+    summary=safe_escape(data.get("summary")),
+    topics=", ".join(escape(t) for t in data.get("top_topics", [])),
+    users=user_blocks(data.get("notable_users", [])),
+    clusters=cluster_blocks(data.get("network_analysis", {}).get("clusters", [])),
+    positive=data.get("sentiment_overview", {}).get("positive", 0),
+    neutral=data.get("sentiment_overview", {}).get("neutral", 0),
+    negative=data.get("sentiment_overview", {}).get("negative", 0),
+    flags=bullet_list(data.get("risk_flags", [])),
+    start=safe_escape(data.get("timestamp_range", {}).get("from")),
+    end=safe_escape(data.get("timestamp_range", {}).get("to"))
 )
 
-# Write final report
+# Save HTML
 with open(os.path.join(output_dir, "OSINT_Report.html"), "w", encoding="utf-8") as f:
-    f.write(html_filled)
-
+    f.write(html_filled)