Upload app.py

app.py

@@ -2089,7 +2089,7 @@ def get_chat_completion(messages, model='gpt-4-turbo'):
 # This function chunks a text into smaller pieces based on a maximum token count and a delimiter
 def chunk_on_delimiter(input_string: str,
                        max_tokens: int,
-                       delimiter: str) -> List[str]:
+                       delimiter: str) -> list[str]:
     chunks = input_string.split(delimiter)
     combined_chunks, _, dropped_chunk_count = combine_chunks_with_no_minimum(
         chunks, max_tokens, chunk_delimiter=delimiter, add_ellipsis_for_overflow=True)
@@ -4727,7 +4727,7 @@ Sample commands:
 
 ######### Words-per-second Chunking #########
 # FIXME - WHole section needs to be re-written
-def chunk_transcript(transcript: str, chunk_duration: int, words_per_second) -> List[str]:
+def chunk_transcript(transcript: str, chunk_duration: int, words_per_second) -> list[str]:
     words = transcript.split()
     words_per_chunk = chunk_duration * words_per_second
     chunks = [' '.join(words[i:i + words_per_chunk]) for i in range(0, len(words), words_per_chunk)]
@@ -5105,7 +5105,7 @@ def add_media_with_keywords(url, title, media_type, content, keywords, prompt, s
         raise DatabaseError(f"Unexpected error: {e}")
 
 
-def fetch_all_keywords() -> List[str]:
+def fetch_all_keywords() -> list[str]:
     try:
         with db.get_connection() as conn:
             cursor = conn.cursor()
@@ -6329,7 +6329,7 @@ def download_ffmpeg():
 #
 #######################################################################################################################
 import tiktoken
-def openai_tokenize(text: str) -> List[str]:
+def openai_tokenize(text: str) -> list[str]:
     encoding = tiktoken.encoding_for_model('gpt-4-turbo')
     return encoding.encode(text)