Fix formatting

Signed-off-by: Arthur Chan <[email protected]>

llm_toolkit/code_fixer.py

@@ -230,8 +230,7 @@ def remove_const_from_png_symbols(content: str) -> str:
 # ========================= LLM Fixes ========================= #
 
 
-def extract_error_message(log_path: str,
-                          project_target_basename: str,
+def extract_error_message(log_path: str, project_target_basename: str,
                           language: str) -> list[str]:
   """Extracts error message and its context from the file in |log_path|."""
 
@@ -451,7 +450,8 @@ def apply_llm_fix(ai_binary: str,
     instruction = _collect_instructions(benchmark, errors,
                                         fuzz_target_source_code)
     prompt = builder.build_fixer_prompt(benchmark, fuzz_target_source_code,
-                                        error_desc, errors, context, instruction)
+                                        error_desc, errors, context,
+                                        instruction)
     prompt.save(prompt_path)
 
   fixer_model.query_llm(prompt, response_dir)
@@ -691,10 +691,10 @@ def _collect_consume_buffers(fuzz_target_source_code: str) -> str:
   for buffer_method in ['ConsumeBytes', 'ConsumeData']:
     if buffer_method in fuzz_target_source_code:
       instruction += (
-          'IMPORTANT: the harness source code contains a call to '
-          f'`{buffer_method}`. Whenever this function is used, you MUST validate'
-          ' the size of the vector returned, and make sure that the size of the '
-          f'vector is equal to argument given to `{buffer_method}`. If it is '
+          'IMPORTANT: the harness source code contains a call to `'
+          f'{buffer_method}`. Whenever this function is used, you MUST validate'
+          ' the size of the vector returned, and make sure that the size of the'
+          f' vector is equal to argument given to `{buffer_method}`. If it is '
           'not equal, the harness should not proceed.\n')
       instruction += (
           f'Furthermore, consider changing {buffer_method} to '

llm_toolkit/prompt_builder.py

@@ -1070,8 +1070,8 @@ def __init__(self,
     self.error_str = '\n'.join(errors)
 
     # Load templates.
-    self.template_file = self._find_template(template_dir,
-                                             'jvm_requirement_error_fixing.txt')
+    self.template_file = self._find_template(
+        template_dir, 'jvm_requirement_error_fixing.txt')
 
   def _find_template(self, template_dir: str, template_name: str) -> str:
     """Finds template file based on |template_dir|."""
@@ -1106,7 +1106,7 @@ def build(self,
 
     # Add the generated harness and error string to prompt
     prompt_text = prompt_text.replace('{GENERATED_HARNESS}',
-                                       self.generated_harness)
+                                      self.generated_harness)
     prompt_text = prompt_text.replace('{ERRORS}', self.error_str)
 
     self._prompt.add_priming(prompt_text)
@@ -1595,4 +1595,3 @@ def post_process_generated_code(self, generated_code: str) -> str:
       generated_code = generated_code.replace(
           'extern "C" int LLVMFuzzerTestOneInput', 'int LLVMFuzzerTestOneInput')
     return generated_code
-

run_one_experiment.py

@@ -264,8 +264,7 @@ def generate_targets_for_analysis(
     use_context: bool,
     example_pair: list[list[str]],
     prompt_builder_to_use: str = 'DEFAULT',
-    cloud_experiment_bucket: str = '',
-    jvm_error_fix: tuple[str, str] = None) -> List[str]:
+    cloud_experiment_bucket: str = '') -> List[str]:
   """Generates a set of harnesses and build scripts ready to be evaluated
     by `check_targets`. This is where the core first LLM logic is used to
     generate harnesses.
@@ -287,14 +286,8 @@ def generate_targets_for_analysis(
   else:
     context_info = {}
 
-  if jvm_error_fix:
-    # If jvm error fix tuple is provided, use error fixing prompt builder.
-    logger.info('Fixing generated JVM harness')
-    code, error = jvm_error_fix
-    builder = prompt_builder.JvmErrorFixingBuilder(model, benchmark,
-                                                   template_dir, code, error)
-  elif benchmark.test_file_path:
-    # If this is a test benchmark then we will use a test prompt builder.
+  # If this is a test benchmark then we will use a test prompt builder.
+  if benchmark.test_file_path:
     logging.info('Generating a target for test case: %s',
                  benchmark.test_file_path)
     builder = prompt_builder.TestToHarnessConverter(model, benchmark,