Update app.py

app.py

@@ -17,17 +17,31 @@ def get_model():
 
 def format_input(question, starter_code=""):
     answer_type = (
-        "\nUse Call-Based format\n" if starter_code else "\nUse Standard Input format\n"
+        "\
+Use Call-Based format\
+" if starter_code else "\
+Use Standard Input format\
+"
     )
-    return f"\nQUESTION:\n{question}\n{starter_code}\n{answer_type}\nANSWER:\n"
+    return f"\
+QUESTION:\
+{question}\
+{starter_code}\
+{answer_type}\
+ANSWER:\
+"
 
 
 def clean_text(generation):
     # clean up text has discussed in OpenAI's paper "Evaluating Large Language Models Trained on Code"
-    generation = generation.split("\ndef")[0]
-    generation = generation.split("\nclass")[0]
-    generation = generation.split("\n#")[0]
-    generation = generation.split("\nif")[0]
+    generation = generation.split("\
+def")[0]
+    generation = generation.split("\
+class")[0]
+    generation = generation.split("\
+#")[0]
+    generation = generation.split("\
+if")[0]
 
     return generation
 
@@ -150,9 +164,10 @@ def run():
         st.code(output, language="python")
 
         # Create link to carbon to make a nice screenshot of the generated code
-        url_code = urllib.parse.quote(f"# {question}\n{output}")
+        url_code = urllib.parse.quote(f"# {question}\
+{output}")
         st.markdown(
-            f"[Carbon Screenshot](https://carbon.now.sh/?bg=rgba%280%2C0%2C0%2C0%29&t=seti&wt=none&l=python&ds=false&dsyoff=20px&dsblur=68px&wc=true&wa=false&pv=56px&ph=56px&ln=false&fl=1&fm=Hack&fs=14px&lh=133%25&si=false&es=2x&wm=false&code={url_code})"
+            f"[Would you like a 'Carbon' copy?](https://carbon.now.sh/?bg=rgba%280%2C0%2C0%2C0%29&t=seti&wt=none&l=python&ds=false&dsyoff=20px&dsblur=68px&wc=true&wa=false&pv=56px&ph=56px&ln=false&fl=1&fm=Hack&fs=14px&lh=133%25&si=false&es=2x&wm=false&code={url_code})"
         )