Create app.py

app.py

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+import gradio as gr
+import os
+import requests
+
+# Load GROQ API key from environment
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+MODEL_NAME = "llama3-8b-8192"
+
+# System Prompt for Ethical Hacking Tutor
+SYSTEM_PROMPT = """You are **HackGuard**, an Ethical Hacking Tutor with a focus on legal and responsible cybersecurity practices.  
+- You teach penetration testing, vulnerability assessment, and security best practices.  
+- You **never** provide actual exploits, malware, or illegal hacking methods.  
+- You explain concepts like SQLi, XSS, and network scanning in an educational context.  
+- You always remind users about **ethical guidelines**, legal boundaries, and bug bounty programs.  
+- If asked for illegal help, you respond with: "I can't assist with that. Ethical hackers follow the law and protect systems, not exploit them."  
+
+Example responses:  
+- "Let me explain how SQL injection works (for educational purposes only)."  
+- "Remember: Always get permission before testing a system (Penetration Testing Rules)."  
+- "Bug bounty platforms like HackerOne are great for legal security research."  
+"""
+
+def query_groq(message, chat_history, skill_level):
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+    
+    for user_msg, bot_msg in chat_history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+    
+    # Adjust explanation depth based on skill level
+    adjusted_msg = f"[Student Level: {skill_level}] {message}"
+    messages.append({"role": "user", "content": adjusted_msg})
+
+    response = requests.post(
+        GROQ_API_URL,
+        headers=headers,
+        json={
+            "model": MODEL_NAME,
+            "messages": messages,
+            "temperature": 0.5  # Lower temp for more factual responses
+        }
+    )
+
+    if response.status_code == 200:
+        reply = response.json()["choices"][0]["message"]["content"]
+        return reply
+    else:
+        return f"Error {response.status_code}: {response.text}"
+
+def respond(message, chat_history, skill_level):
+    bot_reply = query_groq(message, chat_history, skill_level)
+    chat_history.append((message, bot_reply))
+    return "", chat_history
+
+with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown("# 🔐 HackGuard - Ethical Hacking Tutor")
+    gr.Markdown("Learn penetration testing **responsibly**. Always follow the law!")
+    
+    with gr.Row():
+        skill_level = gr.Dropdown(
+            label="Your Skill Level",
+            choices=["Beginner", "Intermediate", "Advanced"],
+            value="Beginner"
+        )
+    
+    chatbot = gr.Chatbot(height=500, label="Ethical Hacking Discussion")
+    msg = gr.Textbox(label="Ask about cybersecurity concepts...", placeholder="E.g., What is SQL injection?")
+    clear = gr.Button("🚫 Clear Chat")
+    
+    msg.submit(
+        respond,
+        [msg, chatbot, skill_level],
+        [msg, chatbot]
+    )
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+demo.launch()