Create app.py

app.py

@@ -0,0 +1,166 @@
+import os
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from huggingface_hub import login
+
+# Hugging Face token (Private Space için)
+# HF_TOKEN = os.getenv("HF_TOKEN")  # Spaces secrets'tan alınacak
+
+# Model seçimi - daha kontrol edilebilir bir model
+MODEL_ID = "codellama/CodeLlama-7b-Instruct-hf"  # veya sizin tercihiniz
+
+class SecureCodeAnalyzer:
+    def __init__(self):
+        self.device = "cuda" if torch.cuda.is_available() else "cpu"
+        print(f"Using device: {self.device}")
+        
+        # Tokenizer
+        self.tokenizer = AutoTokenizer.from_pretrained(
+            MODEL_ID,
+            use_fast=True
+        )
+        self.tokenizer.pad_token = self.tokenizer.eos_token
+        
+        # Model - daha optimize yükleme
+        self.model = AutoModelForCausalLM.from_pretrained(
+            MODEL_ID,
+            torch_dtype=torch.float16,
+            device_map="auto" if self.device == "cuda" else None,
+            low_cpu_mem_usage=True
+        )
+        
+        if self.device == "cpu":
+            self.model = self.model.to(self.device)
+            
+        self.model.eval()
+    
+    def analyze(self, code, language, detail_level, custom_prompt=""):
+        try:
+            # Özel prompt kullan veya varsayılanı
+            if custom_prompt.strip():
+                base_prompt = custom_prompt
+            else:
+                base_prompt = f"""Analyze this {language} code for security vulnerabilities.
+                Provide detailed technical analysis including:
+                1. Vulnerability type
+                2. Risk level
+                3. Exploitation method
+                4. Fix recommendation
+                
+                Code to analyze:
+                {code}
+                
+                Analysis ({detail_level} level):
+                """
+            
+            inputs = self.tokenizer(
+                base_prompt,
+                return_tensors="pt",
+                truncation=True,
+                max_length=2048
+            ).to(self.device)
+            
+            with torch.no_grad():
+                outputs = self.model.generate(
+                    **inputs,
+                    max_new_tokens=500,
+                    temperature=0.3,
+                    do_sample=True,
+                    top_p=0.95,
+                    repetition_penalty=1.1
+                )
+            
+            response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+            
+            # Sadece yeni oluşturulan kısmı al
+            if base_prompt in response:
+                response = response.split(base_prompt)[-1].strip()
+                
+            return response
+            
+        except Exception as e:
+            return f"Error: {str(e)}"
+
+# Initialize analyzer
+analyzer = SecureCodeAnalyzer()
+
+# Gradio arayüzü
+def create_interface():
+    with gr.Blocks(theme=gr.themes.Soft(), title="Private Code Auditor") as demo:
+        gr.Markdown("# 🔐 Private Code Security Auditor")
+        gr.Markdown("*For internal security analysis purposes*")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                language = gr.Dropdown(
+                    ["Python", "C/C++", "JavaScript", "Java", "Go", "PHP", "Other"],
+                    value="Python",
+                    label="Code Language"
+                )
+                
+                detail = gr.Dropdown(
+                    ["Quick Scan", "Standard", "Deep Analysis"],
+                    value="Standard",
+                    label="Analysis Depth"
+                )
+                
+                custom_prompt = gr.Textbox(
+                    label="Custom Prompt (Optional)",
+                    placeholder="Enter custom analysis instructions...",
+                    lines=3
+                )
+                
+                gr.Markdown("### Instructions:")
+                gr.Markdown("""
+                - Paste code in the code editor
+                - Select language and depth
+                - Optional: Add custom prompt
+                - Click Analyze
+                """)
+            
+            with gr.Column(scale=2):
+                code_input = gr.Code(
+                    label="Source Code",
+                    language="python",
+                    lines=20,
+                    value="// Paste your code here"
+                )
+                
+                analyze_btn = gr.Button(
+                    "🔍 Analyze Code",
+                    variant="primary",
+                    size="lg"
+                )
+                
+                output = gr.Textbox(
+                    label="Security Analysis Report",
+                    lines=15,
+                    interactive=False
+                )
+        
+        # Event handler
+        analyze_btn.click(
+            fn=lambda code, lang, detail, custom: analyzer.analyze(code, lang, detail, custom),
+            inputs=[code_input, language, detail, custom_prompt],
+            outputs=output
+        )
+        
+        # Clear button
+        clear_btn = gr.Button("Clear")
+        clear_btn.click(
+            fn=lambda: ("", "", "Standard", "", ""),
+            outputs=[code_input, output, detail, custom_prompt, language]
+        )
+    
+    return demo
+
+# Uygulamayı başlat
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,  # Private için share kapalı
+        debug=False
+    )