diff --git a/data/inference/run_api.py b/data/inference/run_api.py
index 18fb48c40..1126fcbf3 100644
--- a/data/inference/run_api.py
+++ b/data/inference/run_api.py
@@ -29,10 +29,11 @@ async def call_chat(inputs, interpreter):
     inputs (str): The inputs to generate completions for.
     interpreter (DataInterpreter): The data interpreter to use for execution.
     """
+    requirement = "Please rewrite the code to address the issues existing in the repository and generate the correct code. Then, use the `git diff` command to output the patch based on the correct code."
     system_messages = inputs.split("\n", 1)[0]
     user_message = inputs.split("\n", 1)[1]
     try:
-        await interpreter.run([system_messages, user_message])
+        await interpreter.run([requirement, system_messages, user_message])
         return interpreter.get_last_cell_source
     except Exception as e:
         logger.error(f"Error: {e}\nInputs: {inputs}")
@@ -45,6 +46,7 @@ async def openai_inference(
     model_name_or_path,
     output_file,
     existing_ids,
+    use_reflection,
 ):
     """
     Runs inference on a dataset using the openai API.
@@ -66,7 +68,7 @@ async def openai_inference(
     print(f"Filtered to {len(test_dataset)} instances")
     with open(output_file, "a+") as f:
         for datum in tqdm(test_dataset, desc=f"Inference for {model_name_or_path}"):
-            di = DataInterpreter()
+            di = DataInterpreter(use_reflection=use_reflection)
             instance_id = datum["instance_id"]
             if instance_id in existing_ids:
                 continue
@@ -89,6 +91,7 @@ async def main(
     split="test",
     model_name_or_path=config.llm.model,
     output_dir="outputs",
+    use_reflection=True,
 ):
     """
     Performs inference on SWE-bench dataset using the Data Interpreter.
@@ -99,11 +102,7 @@ async def main(
     model_name_or_path: Name of the model to use (default: config.llm.model)
     param output_dir: Path to the output directory (default: outputs)
     """
-    if config.llm.api_type.value == "azure" and config.llm.model == "gpt-4":
-        # Actual model name is gpt-4-1106-preview for Azure
-        model_nickname = "gpt-4-1106-preview"
-    else:
-        model_nickname = Path(model_name_or_path).name
+    model_nickname = Path(model_name_or_path).name if isinstance(model_name_or_path, Path) else model_name_or_path
     output_file = f"{model_nickname}__{dataset_name_or_path.split('/')[-1]}__{split}"
     output_file = Path(output_dir, output_file + ".jsonl")
     output_file.parent.mkdir(parents=True, exist_ok=True)
@@ -136,6 +135,7 @@ async def main(
         "model_name_or_path": model_name_or_path,
         "output_file": output_file,
         "existing_ids": existing_ids,
+        "use_reflection": use_reflection,
     }
     if model_name_or_path.startswith("gpt"):
         await openai_inference(**inference_args)