add logs and some bugs fixes
This commit is contained in:
queukat
parent
525e794f8b
commit
b1de845ec1
1 changed files with 4 additions and 40 deletions
44
src/gpt.py
44
src/gpt.py
|
|
@ -23,27 +23,6 @@ from src.utils import logger
|
|||
|
||||
load_dotenv()
|
||||
|
||||
# Global timestamp for rate limiting
|
||||
last_call_time = 0
|
||||
|
||||
|
||||
def global_rate_limiter(min_interval):
|
||||
def decorator(func):
|
||||
@wraps(func)
|
||||
def wrapper(*args, **kwargs):
|
||||
global last_call_time
|
||||
elapsed = time.time() - last_call_time
|
||||
if elapsed < min_interval:
|
||||
logger.debug("Rate limit hit, sleeping for %s seconds", min_interval - elapsed)
|
||||
time.sleep(min_interval - elapsed)
|
||||
last_call_time = time.time()
|
||||
return func(*args, **kwargs)
|
||||
|
||||
return wrapper
|
||||
|
||||
return decorator
|
||||
|
||||
|
||||
class LLMLogger:
|
||||
|
||||
def __init__(self, llm: ChatOpenAI):
|
||||
|
|
@ -57,7 +36,6 @@ class LLMLogger:
|
|||
logger.debug("Prompts received: %s", prompts)
|
||||
logger.debug("Parsed reply received: %s", parsed_reply)
|
||||
|
||||
# Определяем путь к файлу для записи логов
|
||||
try:
|
||||
calls_log = os.path.join(Path("data_folder/output"), "open_ai_calls.json")
|
||||
logger.debug("Logging path determined: %s", calls_log)
|
||||
|
|
@ -65,7 +43,6 @@ class LLMLogger:
|
|||
logger.error("Error determining the log path: %s", str(e))
|
||||
raise
|
||||
|
||||
# Преобразование prompts в текст или словарь
|
||||
if isinstance(prompts, StringPromptValue):
|
||||
logger.debug("Prompts are of type StringPromptValue")
|
||||
prompts = prompts.text
|
||||
|
|
@ -93,7 +70,6 @@ class LLMLogger:
|
|||
logger.error("Error converting prompts using default method: %s", str(e))
|
||||
raise
|
||||
|
||||
# Получение текущего времени
|
||||
try:
|
||||
current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
logger.debug("Current time obtained: %s", current_time)
|
||||
|
|
@ -101,7 +77,6 @@ class LLMLogger:
|
|||
logger.error("Error obtaining current time: %s", str(e))
|
||||
raise
|
||||
|
||||
# Извлечение информации о токенах
|
||||
try:
|
||||
token_usage = parsed_reply["usage_metadata"]
|
||||
output_tokens = token_usage["output_tokens"]
|
||||
|
|
@ -112,7 +87,6 @@ class LLMLogger:
|
|||
logger.error("KeyError in parsed_reply structure: %s", str(e))
|
||||
raise
|
||||
|
||||
# Извлечение имени модели
|
||||
try:
|
||||
model_name = parsed_reply["response_metadata"]["model_name"]
|
||||
logger.debug("Model name: %s", model_name)
|
||||
|
|
@ -120,7 +94,6 @@ class LLMLogger:
|
|||
logger.error("KeyError in response_metadata: %s", str(e))
|
||||
raise
|
||||
|
||||
# Вычисление стоимости использования API
|
||||
try:
|
||||
prompt_price_per_token = 0.00000015
|
||||
completion_price_per_token = 0.0000006
|
||||
|
|
@ -130,7 +103,6 @@ class LLMLogger:
|
|||
logger.error("Error calculating total cost: %s", str(e))
|
||||
raise
|
||||
|
||||
# Формирование записи лога
|
||||
try:
|
||||
log_entry = {
|
||||
"model": model_name,
|
||||
|
|
@ -147,7 +119,6 @@ class LLMLogger:
|
|||
logger.error("Error creating log entry: missing key %s in parsed_reply", str(e))
|
||||
raise
|
||||
|
||||
# Запись в файл
|
||||
try:
|
||||
with open(calls_log, "a", encoding="utf-8") as f:
|
||||
json_string = json.dumps(log_entry, ensure_ascii=False, indent=4)
|
||||
|
|
@ -166,7 +137,7 @@ class LoggerChatModel:
|
|||
|
||||
def __call__(self, messages: List[Dict[str, str]]) -> str:
|
||||
logger.debug("Entering __call__ method with messages: %s", messages)
|
||||
while True: # Бесконечный цикл до успешного выполнения
|
||||
while True:
|
||||
try:
|
||||
logger.debug("Attempting to call the LLM with messages")
|
||||
reply = self.llm(messages) # Вызов LLM
|
||||
|
|
@ -175,11 +146,10 @@ class LoggerChatModel:
|
|||
parsed_reply = self.parse_llmresult(reply)
|
||||
logger.debug("Parsed LLM reply: %s", parsed_reply)
|
||||
|
||||
# Логируем запрос и ответ
|
||||
LLMLogger.log_request(prompts=messages, parsed_reply=parsed_reply)
|
||||
logger.debug("Request successfully logged")
|
||||
|
||||
return reply # Возвращаем корректный ответ, завершаем цикл
|
||||
return reply
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error("HTTPStatusError encountered: %s", str(e))
|
||||
|
|
@ -207,12 +177,11 @@ class LoggerChatModel:
|
|||
logger.error("Unexpected error occurred: %s", str(e))
|
||||
logger.info("Waiting for 30 seconds before retrying due to an unexpected error.")
|
||||
time.sleep(30)
|
||||
continue # Продолжаем цикл
|
||||
continue
|
||||
|
||||
def parse_llmresult(self, llmresult: AIMessage) -> Dict[str, Dict]:
|
||||
logger.debug("Parsing LLM result: %s", llmresult)
|
||||
|
||||
# Извлечение данных из ответа
|
||||
try:
|
||||
content = llmresult.content
|
||||
response_metadata = llmresult.response_metadata
|
||||
|
|
@ -240,7 +209,7 @@ class LoggerChatModel:
|
|||
|
||||
except KeyError as e:
|
||||
logger.error("KeyError while parsing LLM result: missing key %s", str(e))
|
||||
raise # Повторно выбрасываем исключение, чтобы оно обрабатывалось выше
|
||||
raise
|
||||
|
||||
except Exception as e:
|
||||
logger.error("Unexpected error while parsing LLM result: %s", str(e))
|
||||
|
|
@ -293,7 +262,6 @@ class GPTAnswerer:
|
|||
logger.debug("Setting job application profile: %s", job_application_profile)
|
||||
self.job_application_profile = job_application_profile
|
||||
|
||||
#@global_rate_limiter(25)
|
||||
def summarize_job_description(self, text: str) -> str:
|
||||
logger.debug("Summarizing job description: %s", text)
|
||||
strings.summarize_prompt_template = self._preprocess_template_string(
|
||||
|
|
@ -310,7 +278,6 @@ class GPTAnswerer:
|
|||
prompt = ChatPromptTemplate.from_template(template)
|
||||
return prompt | self.llm_cheap | StrOutputParser()
|
||||
|
||||
#@global_rate_limiter(25)
|
||||
def answer_question_textual_wide_range(self, question: str) -> str:
|
||||
logger.debug("Answering textual question: %s", question)
|
||||
chains = {
|
||||
|
|
@ -438,7 +405,6 @@ class GPTAnswerer:
|
|||
logger.debug("Question answered: %s", output)
|
||||
return output
|
||||
|
||||
#@global_rate_limiter(25)
|
||||
def answer_question_numeric(self, question: str, default_experience: int = 3) -> int:
|
||||
logger.debug("Answering numeric question: %s", question)
|
||||
func_template = self._preprocess_template_string(strings.numeric_question_template)
|
||||
|
|
@ -464,7 +430,6 @@ class GPTAnswerer:
|
|||
logger.error("No numbers found in the string")
|
||||
raise ValueError("No numbers found in the string")
|
||||
|
||||
#@global_rate_limiter(25)
|
||||
def answer_question_from_options(self, question: str, options: list[str]) -> str:
|
||||
logger.debug("Answering question from options: %s", question)
|
||||
func_template = self._preprocess_template_string(strings.options_template)
|
||||
|
|
@ -476,7 +441,6 @@ class GPTAnswerer:
|
|||
logger.debug("Best option determined: %s", best_option)
|
||||
return best_option
|
||||
|
||||
#@global_rate_limiter(25)
|
||||
def resume_or_cover(self, phrase: str) -> str:
|
||||
logger.debug("Determining if phrase refers to resume or cover letter: %s", phrase)
|
||||
prompt_template = """
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue