Yurii Paniv commited on
Commit
9a7ca97
1 Parent(s): 0eb8092

Log straight away

Browse files
Files changed (1) hide show
  1. app.py +13 -9
app.py CHANGED
@@ -26,15 +26,11 @@ def check_thread(logging_queue: Queue):
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  dataset_name=getenv("OUTPUT_DATASET"),
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  private=True,
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  )
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- print("Logging thread started.")
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- print(f"Logging to '{getenv('OUTPUT_DATASET')}'")
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  while True:
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- print("Checking for logs...")
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  sleep(60)
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  batch = []
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  while not logging_queue.empty():
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  batch.append(logging_queue.get())
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- print("Batch:", batch)
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  if len(batch) > 0:
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  try:
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  logging_callback(batch)
@@ -47,10 +43,15 @@ def check_thread(logging_queue: Queue):
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48
 
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  if getenv("HF_API_TOKEN") is not None:
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- print("Starting logging thread...")
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- log_queue = Queue()
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- t = Thread(target=check_thread, args=(log_queue,))
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- t.start()
 
 
 
 
 
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  else:
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  print("No HF_API_TOKEN found. Logging is disabled.")
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@@ -83,7 +84,10 @@ def translate(input_text):
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  print(f"{datetime.utcnow()} | Translating: {input_text}")
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  if getenv("HF_API_TOKEN") is not None:
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- log_queue.put([input_text])
 
 
 
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  input_text = f"[INST] {input_text} [/INST]"
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  inputs = tokenizer([input_text], return_tensors="pt").to(model.device)
 
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  dataset_name=getenv("OUTPUT_DATASET"),
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  private=True,
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  )
 
 
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  while True:
 
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  sleep(60)
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  batch = []
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  while not logging_queue.empty():
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  batch.append(logging_queue.get())
 
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  if len(batch) > 0:
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  try:
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  logging_callback(batch)
 
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  if getenv("HF_API_TOKEN") is not None:
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+ #print("Starting logging thread...")
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+ #log_queue = Queue()
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+ #t = Thread(target=check_thread, args=(log_queue,))
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+ #t.start()
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+ logging_callback = log_data(
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+ hf_token=getenv("HF_API_TOKEN"),
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+ dataset_name=getenv("OUTPUT_DATASET"),
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+ private=True,
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+ )
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  else:
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  print("No HF_API_TOKEN found. Logging is disabled.")
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84
  print(f"{datetime.utcnow()} | Translating: {input_text}")
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  if getenv("HF_API_TOKEN") is not None:
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+ try:
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+ logging_callback([input_text])
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+ except:
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+ print("Error happened while pushing data to HF.")
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  input_text = f"[INST] {input_text} [/INST]"
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  inputs = tokenizer([input_text], return_tensors="pt").to(model.device)