From 6029b65e2b290c639bcde5ebe8e4e6ff359a7047 Mon Sep 17 00:00:00 2001
From: Migatu <mtuszowski@gmail.com>
Date: Sat, 21 Oct 2023 00:04:32 +0200
Subject: [PATCH] Fix

---
 bot.py | 31 +++++++++++++++++--------------
 1 file changed, 17 insertions(+), 14 deletions(-)

diff --git a/bot.py b/bot.py
index 864c70a..a2b27eb 100644
--- a/bot.py
+++ b/bot.py
@@ -337,11 +337,13 @@ async def on_message(message):
 
 def num_tokens_from_string(message, model):
     """
-    The function `num_tokens_from_string` returns the number of tokens in a given string.
+    The function takes a string message and a model as input and returns the number of tokens in the
+    message according to the given model.
 
-    :param string: The `string` parameter is a string of text that you want to count the number of
-    tokens for
-    :return: the number of tokens in the given string.
+    :param message: A string containing the message or text from which you want to count the number of
+    tokens
+    :param model: The model parameter refers to a language model or tokenizer that can be used to
+    tokenize the input string. It could be a pre-trained model or a custom tokenizer
     """
     tokens_per_message = 3
     tokens_per_name = 1
@@ -489,7 +491,6 @@ async def play(ctx, zamawial=None, arg=None):
 async def check():
     """Funkcja sprawdzająca czy grać następny kawałek."""
     while True:
-        # TODO: Tu dołożyć skanowanie rozmiaru pliku logowania oraz plików pamięci i przenoszenie ich na większy dysk.
         # trunk-ignore(codespell/misspelled)
         # TODO: dlaczego sie tu wypierdala
         if client.voice_clients:
@@ -557,6 +558,7 @@ async def check():
         await asyncio.sleep(60)
 
 
+# trunk-ignore(pylint/R0914)
 # trunk-ignore(pylint/R0913)
 # trunk-ignore(pylint/R0915)
 async def handle_response(prompt, vykidailo, bartender, history, username, music):
@@ -602,17 +604,17 @@ async def handle_response(prompt, vykidailo, bartender, history, username, music
             json.dump(file_data, file_memory, indent=4)
     history = []
     history.append(GPT_SETTINGS[0])
-    chat_GPT_tokens = num_tokens_from_string(GPT_SETTINGS[0], "gpt-4")
+    chat_gpt_config_request_size = num_tokens_from_string(GPT_SETTINGS[0], "gpt-4")
 
     for (slowo, reakcja) in word_reactions.items():
         if not reakcja[3]:
             content = "Kiedy słyszysz " + slowo + " to reagujesz lub dzieje się to " + reakcja[0]
             temp = {"role": "system", "content": content}
-            chat_GPT_tokens += num_tokens_from_string(temp, "gpt-4")
+            chat_gpt_config_request_size += num_tokens_from_string(temp, "gpt-4")
             history.append(temp)
 
     final_prompt = username + ":" + prompt
-    logger.error("Liczba tokenów przed dodaniem historii %s", chat_GPT_tokens)
+    logger.info("Rozmiar zapytania przed dodaniem historii %s", chat_gpt_config_request_size)
     if music:
         algorithm = "gpt-3.5-turbo-16k"
         table = message_table_muzyka
@@ -622,27 +624,28 @@ async def handle_response(prompt, vykidailo, bartender, history, username, music
         algorithm = "gpt-4"
         token_amount = 8000
 
-    prompt_tokens = num_tokens_from_string({"role": "user", "content": final_prompt}, "gpt-4")
+    prompt_gpt_request_size = num_tokens_from_string({"role": "user", "content": final_prompt}, "gpt-4")
     temptable = []
     for i in reversed(table):
         temp_token = num_tokens_from_string(i, "gpt-4")
-        logger.error("Liczba tokenow %s prompt token %s temp token %s", chat_GPT_tokens, prompt_tokens, temp_token)
-        if chat_GPT_tokens < token_amount + prompt_tokens + temp_token:
+        logger.info("Rozmiar zapytania %s prompt %s temp %s", chat_gpt_config_request_size, prompt_gpt_request_size, temp_token)
+        if chat_gpt_config_request_size < token_amount + prompt_gpt_request_size + temp_token:
             temptable.insert(1, i)
-            chat_GPT_tokens += temp_token
+            chat_gpt_config_request_size += temp_token
     history.extend(temptable)
     temp = {"role": "user", "content": final_prompt}
     history.append(temp)
-    logger.error("Liczba tokenów wyslana %s", chat_GPT_tokens)
+    logger.info("Rozmiar zapytania po wyslaniu %s", chat_gpt_config_request_size)
 
     response = await openai.ChatCompletion.acreate(
             model=algorithm, messages=history
         )
     logger.info("Historia wysłana:")
     logger.info(history)
-    await asyncio.sleep(10)
+    await asyncio.sleep(15)
     result = ""
     logger.debug("Odpowiedzi")
+    logger.info(response)
     logger.debug(response.choices)
     for choice in response.choices:
         result += choice.message.content