Upload 2 files

_script_for_eval.py

@@ -17,6 +17,7 @@ from datasets import load_dataset
 from sentence_transformers import SentenceTransformer, CrossEncoder
 from sklearn.metrics.pairwise import cosine_similarity
 
+# client = OpenAI(base_url="http://localhost:11434/v1/", api_key="ollama")
 client = OpenAI()
 
 def load_cache(use_cache):
@@ -116,12 +117,13 @@ def get_fixed_code_fine_tuned(prompt, few_shot_messages, model_name):
     messages.append({"role": "user", "content": prompt})
 
     max_retries = 3
+
     for attempt in range(max_retries):
         try:
             response = client.chat.completions.create(
                 model=model_name,
                 messages=messages,
-                max_tokens=512,
+                max_tokens=4096,
                 temperature=0.2,
                 top_p=0.95
             )
@@ -131,6 +133,20 @@ def get_fixed_code_fine_tuned(prompt, few_shot_messages, model_name):
                 time.sleep(2 ** attempt)  # Exponential backoff
             else:
                 raise Exception(f"API call failed after {max_retries} attempts: {str(e)}")
+            
+def clean_code_snippet(response):
+    # Remove opening delimiter
+    if response.startswith("```python"):
+        response = response[len("```python"):]
+    elif response.startswith("```"):
+        response = response[len("```"):]
+    
+    # Remove closing delimiter
+    if response.endswith("```"):
+        response = response[:-len("```")]
+    
+    # Trim any remaining whitespace
+    return response.strip()
 
 def process_file(test_case, cache, fixed_files, model_name, use_cache, n_shot, use_similarity, oracle_mode):
     file_name = test_case["file_name"]
@@ -154,7 +170,7 @@ def process_file(test_case, cache, fixed_files, model_name, use_cache, n_shot, u
             os.remove(tmp_file)
             
         tqdm.write("Scanning file " + input_file + "...")
-        scan_command_input = f"semgrep --config p/python {input_file} --output {tmp_file} --json > /dev/null 2>&1"
+        scan_command_input = f"semgrep --config auto {input_file} --output {tmp_file} --json > /dev/null 2>&1"
         os.system(scan_command_input)
         
         if not os.path.exists(tmp_file):
@@ -163,71 +179,62 @@ def process_file(test_case, cache, fixed_files, model_name, use_cache, n_shot, u
 
         with open(tmp_file, 'r') as jf:
             data = json.load(jf)
-        
-        if len(data.get("errors", [])) == 0:
-            if len(data.get("results", [])) == 0:
-                tqdm.write(input_file + " has no vulnerabilities")
-                result = False
+
+        if len(data.get("errors", [])) > 0:
+            tqdm.write(f"Error processing {input_file} ...")
+            return False
+            
+        if len(data.get("results", [])) == 0:
+            tqdm.write(input_file + " has no vulnerabilities")
+            result = False
+        else:
+            tqdm.write("Vulnerability found in " + input_file + "...")
+            if oracle_mode:
+                result = True
+                fixed_files.append(file_name)
             else:
-                tqdm.write("Vulnerability found in " + input_file + "...")
-                if oracle_mode:
-                    result = True
-                    fixed_files.append(file_name)
-                else:
-                    cwe = data["results"][0]["extra"]["metadata"]["cwe"][0]
-                    lines = data["results"][0]["extra"]["lines"]
-                    message = data["results"][0]["extra"]["message"]
-                    
-                    prompt = f"""Vulnerability Report:
-        - Type: {cwe}
-        - Location: {lines}
-        - Description: {message}
-
-        Original Code:
-        ```
-        {file_text}
-        ```
-
-        Task: Fix the vulnerability in the code above. Provide only the complete fixed code without explanations or comments. Make minimal changes necessary to address the security issue while preserving the original functionality."""
-                    
-                    few_shot_messages = fetch_dataset_examples(prompt, n_shot, use_similarity)
-                    response = get_fixed_code_fine_tuned(prompt, few_shot_messages, model_name)
-                    
-                    if "```python" in response:
-                        idx = response.find("```python")
-                        shift = len("```python")
-                        fixed_code = response[idx + shift :]
-                    else:
-                        fixed_code = response
-                    
-                    stop_words = ["```", "assistant"]
-
-                    for w in stop_words:
-                        if w in fixed_code:
-                            fixed_code = fixed_code[:fixed_code.find(w)]
-                    if len(fixed_code) < 400:
-                        result = False
-                    if has_all_comments(fixed_code):
-                        result = False
+                cwe = test_case['cwe']
+                lines = data["results"][0]["extra"]["lines"]
+                message = data["results"][0]["extra"]["message"]
+                
+                prompt = f"""Vulnerability Report:
+    - Type: {cwe}
+    - Location: {lines}
+    - Description: {message}
+
+    Original Code:
+    ```
+    {file_text}
+    ```
+
+    Task: Fix the vulnerability in the code above. Provide only the complete fixed code without explanations or comments. Make minimal changes necessary to address the security issue while preserving the original functionality."""
+                # print(prompt)
+                few_shot_messages = fetch_dataset_examples(prompt, n_shot, use_similarity)
+                response = get_fixed_code_fine_tuned(prompt, few_shot_messages, model_name)
+                # print(response)
+                
+                fixed_code = clean_code_snippet(response)
+
+                if len(fixed_code) < 512 or has_all_comments(fixed_code):
+                    result = False
+                else: 
+                    # print("Here2\n" + fixed_code)
                     if os.path.exists(output_file):
                         os.remove(output_file)
                     with open(output_file, 'w') as wf:
                         wf.write(fixed_code)
                     if os.path.exists(tmp_file):
                         os.remove(tmp_file)
-                    scan_command_output = f"semgrep --config p/python {output_file} --output {tmp_file} --json > /dev/null 2>&1"
+                    scan_command_output = f"semgrep --config auto {output_file} --output {tmp_file} --json > /dev/null 2>&1"
                     os.system(scan_command_output)
                     with open(tmp_file, 'r') as jf:
                         data = json.load(jf)
-                    if len(data["errors"]) == 0 and len(data["results"]) == 0:
+                    if len(data["results"]) == 0:
                         tqdm.write("Passing response for " + input_file + " at 1 ...")
                         result = True
                         fixed_files.append(file_name)
                     else:
                         result = False
-        else:
-            tqdm.write(f"Semgrep reported errors for {input_file}")
-            result = False
 
         if os.path.exists(tmp_file):
             os.remove(tmp_file)
@@ -258,7 +265,7 @@ def main():
     oracle_mode = args.oracle
     sanitized_model_name = f"{sanitize_filename(model_name)}-{n_shot}-shot{'-sim' if use_similarity else ''}"
 
-    dataset = load_dataset("patched-codes/static-analysis-eval", split="train")
+    dataset = load_dataset("patched-codes/static-analysis-eval", split="train", download_mode='force_redownload')
     data = [{"file_name": item["file_name"], "source": item["source"], "cwe": item["cwe"]} for item in dataset]
 
     cache = load_cache(use_cache)
@@ -271,7 +278,8 @@ def main():
     manager = multiprocessing.Manager()
     fixed_files = manager.list()
 
-    process_func = partial(process_test_case, cache=cache, fixed_files=fixed_files, model_name=model_name, use_cache=use_cache, n_shot=n_shot, use_similarity=use_similarity, oracle_mode=oracle_mode)
+    process_func = partial(process_test_case, cache=cache, fixed_files=fixed_files, model_name=model_name,
+                           use_cache=use_cache, n_shot=n_shot, use_similarity=use_similarity, oracle_mode=oracle_mode)
 
     with multiprocessing.Pool(processes=4) as pool:
         results = list(tqdm(pool.imap(process_func, data), total=total_tests))

_script_for_gen.py

@@ -160,10 +160,8 @@ def merge_and_push_dataset(jsonl_file, new_dataset_name):
     logging.info("Creating dataset")
     try:
         dataset = Dataset.from_list(preprocessed_data)
-    except pa.lib.ArrowInvalid as e:
+    except Exception as e:
         logging.error(f"Error creating dataset: {str(e)}")
-        logging.info("Attempting to create dataset with type inference disabled")
-        dataset = Dataset.from_list(preprocessed_data, features=pa.schema([]))
 
     # Push the dataset to the new repository
     logging.info(f"Pushing dataset with {len(dataset)} records to Hugging Face")
@@ -178,7 +176,7 @@ def main():
 
     if args.push_to_dataset:
         # Merge and push the dataset
-        jsonl_file = "output.jsonl"
+        jsonl_file = "static_analysis_eval.jsonl"
         merge_and_push_dataset(jsonl_file, args.push_to_dataset)
     else:
         # Perform the regular dataset extension process