Maks1mS/ocab
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MVP status. Fix context bug.

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This commit is contained in:
armatik 2023-08-01 20:50:28 +03:00
parent 83e92c445f
commit e66901a6b8
1 changed files with 20 additions and 9 deletions
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29
src/OpenAI/GPT35turbo/OA_processing.py
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@ -33,9 +33,16 @@ def openai_response(message_formated_text):
# Считаем размер полученного текста
#print(message_formated_text)
count_length = 0
if len(message_formated_text) == 0:
message_formated_text = [
{
"role": "user",
"content": "Напиши короткий ответ говорящий что контекст сообщения слишком длинный и попроси задать вопрос отдельно без ответа на другие сообщения по ключевому слову"
}
]
for message in message_formated_text:
#print(message["content"])
count_length += len(message["content"])
count_length += int(len(message["content"]))
#print(count_length)
try:
response = openai.ChatCompletion.create(
@ -74,14 +81,7 @@ def sort_message_from_user(message_formated_text, message_id):
"content": str(*(cursor.execute("SELECT message_text FROM message_list WHERE message_id = ?",
(message_id,)).fetchone()))
})
#Проверка что длина всех сообщений в кортеже не превышает max_token_count-500
count_length = 0
for message in message_formated_text:
count_length += len(message['content'])
while count_length > max_token_count-min_token_for_answer:
message_formated_text.pop(1)
for message in message_formated_text:
count_length += len(message['content'])
#Проверка что длина всех сообщений в кортеже не превышает max_token_count-min_token_for_answer
return message_formated_text
def openai_collecting_message(message_id, message_formated_text):
@ -115,6 +115,17 @@ def openai_message_processing(message_id):
]
if ((len(str(cursor.execute("SELECT message_text FROM message_list WHERE message_id")))) < (max_token_count - len(message_formated_text[0]['content']))):
message_formated_text = openai_collecting_message(message_id, message_formated_text)
count_length = 0
# Обработка невозможности ответить на сообщение
try:
for message in message_formated_text:
count_length += len(message['content'])
while count_length > max_token_count - min_token_for_answer:
message_formated_text.pop(1)
for message in message_formated_text:
count_length += len(message['content'])
except IndexError:
message_formated_text = ""
response = openai_response(message_formated_text)
return response
else: