update

app.py

@@ -102,8 +102,8 @@ def R1_infer1(theme, tags_gen, language):
 def R1_infer2(tags_lyrics, lyrics_input):
     client = OpenAI()
 
-    llm_prompt = """
-    {lyrics_input}This is the lyrics of a song. Each line is a line of lyrics. {tags_lyrics} is the style I want for this song. I now want to timestamp each line of lyrics of this song to get LRC. I hope that the timestamp allocation should be reasonably inferred based on the song tag, the emotion of the lyrics, and the rhythm, rather than mechanically allocated according to the length of the lyrics. The timestamp of the first line of lyrics should take into account the length of the prelude to avoid the lyrics starting directly from `[00:00.00]`. Output the lyrics strictly in LRC format, with each line in the format of `[mm:ss.xx] lyrics content`. The final result only outputs LRC, no other explanation is required.
+    llm_prompt = """`{lyrics_input}`
+This is the lyrics of a song. Each line is a line of lyrics. {tags_lyrics} is the style I want for this song. I now want to timestamp each line of lyrics of this song to get LRC. I hope that the timestamp allocation should be reasonably inferred based on the song tag, the emotion of the lyrics, and the rhythm, rather than mechanically allocated according to the length of the lyrics. The timestamp of the first line of lyrics should take into account the length of the prelude to avoid the lyrics starting directly from `[00:00.00]`. Output the lyrics strictly in LRC format, with each line in the format of `[mm:ss.xx] lyrics content`. The final result only outputs LRC, no other explanation is required.
     """
 
     response = client.chat.completions.create(