req

analyzer.py

@@ -0,0 +1,19 @@
+import openai
+import os
+
+def analyze_code(code: str) -> str:
+    """
+    Uses OpenAI's GPT-4.1 mini model to analyze the given code.
+    Returns the analysis as a string.
+    """
+    system_prompt = "You are a helpful assistant. Analyze the code given to you. Provide insights, strengths, weaknesses, and suggestions for improvement."
+    response = openai.ChatCompletion.create(
+        model="gpt-4.1-mini",  # GPT-4.1 mini
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": code}
+        ],
+        max_tokens=512,
+        temperature=0.7
+    )
+    return response.choices[0].message["content"]

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import regex as re
 import csv
 import pandas as pd
-
+# from hf_utils import download_space_repo
 
 def process_repo_input(text):
     if not text:

requirements.txt

@@ -1,4 +1,3 @@
 gradio
 pandas
-csv
-regex
+