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Basti1110 commited on May 21, 2025

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8b5bb08

verified ·

1 Parent(s): db46f4e

Update render_report.py

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Files changed (1) hide show

render_report.py +35 -98

render_report.py CHANGED Viewed

@@ -1,24 +1,19 @@
 import json
 import os
 import matplotlib.pyplot as plt
 import networkx as nx
-# Define safe output directory
 output_dir = "/tmp"
-# Load JSON
-with open("/tmp/data.json", "r", encoding="utf-8") as f:
     data = json.load(f)
-# Save charts
-sentiment_chart = os.path.join(output_dir, "sentiment_pie_chart.png")
-network_chart = os.path.join(output_dir, "network_graph.png")
-html_output = os.path.join(output_dir, "OSINT_Report.html")
-# Generate sentiment pie chart
 labels = list(data["sentiment_overview"].keys())
 sizes = list(data["sentiment_overview"].values())
 colors = ['#4CAF50', '#FFC107', '#F44336']
@@ -26,11 +21,11 @@ fig, ax = plt.subplots()
 ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140, colors=colors)
 ax.axis('equal')
 plt.title('Sentiment Overview')
-sentiment_chart = "/tmp/sentiment_pie_chart.png"
-plt.savefig(sentiment_chart, bbox_inches='tight')
 plt.close()
 # Generate network graph
 G = nx.Graph()
 for cluster in data["network_analysis"]["clusters"]:
     nodes = cluster["nodes"]
@@ -38,102 +33,44 @@ for cluster in data["network_analysis"]["clusters"]:
         G.add_node(nodes[i])
         for j in range(i + 1, len(nodes)):
             G.add_edge(nodes[i], nodes[j])
 plt.figure(figsize=(8, 6))
 pos = nx.spring_layout(G, seed=42)
 node_colors = ['lightblue' if 'Trump' in node else 'salmon' for node in G.nodes()]
 nx.draw(G, pos, with_labels=True, node_color=node_colors, edge_color='gray', node_size=1200, font_size=8)
 plt.title("Network Influence Graph")
-network_chart = "/tmp/network_graph.png"
-plt.savefig(network_chart, bbox_inches='tight')
 plt.close()
-# Generate HTML report
-html_content = f"""
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <title>OSINT Intelligence Report</title>
-    <style>
-        body {{
-            font-family: Arial, sans-serif;
-            margin: 40px;
-            background-color: #f9f9f9;
-        }}
-        h1 {{
-            color: #2c3e50;
-            text-align: center;
-        }}
-        h2 {{
-            color: #34495e;
-            border-bottom: 2px solid #ccc;
-            padding-bottom: 5px;
-        }}
-        .section {{
-            margin-bottom: 30px;
-        }}
-        .image {{
-            text-align: center;
-            margin: 20px 0;
-        }}
-    </style>
-</head>
-<body>
-    <h1>OSINT Intelligence Report</h1>
-    <div class="section">
-        <h2>Summary</h2>
-        <p>{data["summary"]}</p>
-    </div>
-    <div class="section">
-        <h2>Top Topics</h2>
-        <p>{', '.join(data["top_topics"])}</p>
-    </div>
-    <div class="section">
-        <h2>Notable Users</h2>
-        {''.join([f"<p><strong>{u['username']} ({u['type']}):</strong> {u['activity_summary']}</p>" for u in data["notable_users"]])}
-    </div>
-    <div class="section">
-        <h2>Network Analysis</h2>
-        {''.join([f"<p><strong>{c['label']}:</strong> {c['summary']}</p>" for c in data["network_analysis"]["clusters"]])}
-    </div>
-    <div class="section">
-        <h2>Sentiment Overview</h2>
-        <p>Positive: {data['sentiment_overview']['positive']}%</p>
-        <p>Neutral: {data['sentiment_overview']['neutral']}%</p>
-        <p>Negative: {data['sentiment_overview']['negative']}%</p>
-        <div class="image">
-            <img src="sentiment_pie_chart.png" width="500">
-        </div>
-    </div>
-    <div class="section">
-        <h2>Network Influence Graph</h2>
-        <div class="image">
-            <img src="network_graph.png" width="600">
-        </div>
-    </div>
-    <div class="section">
-        <h2>Risk Flags</h2>
-        <ul>
-            {''.join([f"<li>{flag}</li>" for flag in data["risk_flags"]])}
-        </ul>
-    </div>
-    <div class="section">
-        <h2>Timestamp Range</h2>
-        <p>From: {data["timestamp_range"]["from"]}</p>
-        <p>To: {data["timestamp_range"]["to"]}</p>
-    </div>
-</body>
-</html>
-"""
-with open(html_output, "w", encoding="utf-8") as f:
-    f.write(html_content)

 import json
 import os
 import matplotlib.pyplot as plt
 import networkx as nx
+# 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_path = os.path.join(output_dir, "sentiment_pie_chart.png")
 labels = list(data["sentiment_overview"].keys())
 sizes = list(data["sentiment_overview"].values())
 colors = ['#4CAF50', '#FFC107', '#F44336']
 ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140, colors=colors)
 ax.axis('equal')
 plt.title('Sentiment Overview')
+plt.savefig(sentiment_path, bbox_inches='tight')
 plt.close()
 # Generate network graph
+network_path = os.path.join(output_dir, "network_graph.png")
 G = nx.Graph()
 for cluster in data["network_analysis"]["clusters"]:
     nodes = cluster["nodes"]
         G.add_node(nodes[i])
         for j in range(i + 1, len(nodes)):
             G.add_edge(nodes[i], nodes[j])
 plt.figure(figsize=(8, 6))
 pos = nx.spring_layout(G, seed=42)
 node_colors = ['lightblue' if 'Trump' in node else 'salmon' for node in G.nodes()]
 nx.draw(G, pos, with_labels=True, node_color=node_colors, edge_color='gray', node_size=1200, font_size=8)
 plt.title("Network Influence Graph")
+plt.savefig(network_path, bbox_inches='tight')
 plt.close()
+# Format data into HTML
+from html import escape
+def bullet_list(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)
+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
+with open("/osint_dark_template.html", "r", encoding="utf-8") as tpl:
+    template = tpl.read()
+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"])
+)
+# Write final report
+with open(os.path.join(output_dir, "OSINT_Report.html"), "w", encoding="utf-8") as f:
+    f.write(html_filled)