Release 0.0.5

Now it displays warning message if retry count exceeds 5

README.md

@@ -44,7 +44,7 @@ resp = call_chatgpt(
     system_message=['You are a helpful assistant.'] * len(prompts),
     model_name=CHATGPT_VERSION_NAME,  # default is 'gpt-3.5-turbo'
     temperature=TEMPERATURE,  # default 0.0
-    chunk_size=CHATGPT_CHUNK_SIZE,
+    chunk_size=CONCURRENCY_NUM,
     timeout_each=TIMEOUT_EACH,
     sleep_between_chunk=SLEEP_BETWEEN_CHUNK,
     pkl_path=file_dir,  # ex) "result.pkl'
@@ -55,15 +55,12 @@ resp = call_chatgpt(
 - ```system_message```: list of system prompt. It can be a str or a list of str that has same length to human_message
 - ```model_name```: ChatGPT API name (ex: "gpt-4-1106-preview")
 - ```temperature```: Controls randomness of the generated text
-- ```chunk_size```: The number of examples which send in one batch
-- ```timeout_each```: API call timeout
+- ```chunk_size```: The number of examples which simultaneously send in one batch
+- ```timeout_each```: API call timeout (for each batch)
 - ```sleep_between_chunk```: sleep time between batches
 - ```pkl_path```: Specifies the path where output will be saved. By default, outputs are not saved.
 - ```verbose```: If true, debugging message will be printed.
 
-## Warning
-- Currently, no retry count limit is set. So, It should be manually stopped if the API is failed repeatedly. (Will be fixed soon)
-
 ## Requirements
 - langchain
 - langchain-openai

batched_chatgpt/__init__.py

@@ -1,3 +1,3 @@
 from .chatgpt_utils import call_chatgpt
 
-__version__ = '0.0.4'
+__version__ = '0.0.5'

batched_chatgpt/chatgpt_utils.py

@@ -2,6 +2,8 @@
 from pprint import pprint
 from multiprocessing import Queue, Process
 from pathlib import Path
+from logging import getLogger
+from itertools import count
 import time
 import os
 
@@ -12,6 +14,9 @@
 from .utils import pickle_bobj, get_saving_filename_safely
 
 
+logger = getLogger(__name__)
+
+
 def process_chunk_element(i, queue, item, model_name, temperature):
     chat = ChatOpenAI(model=model_name, temperature=temperature)
     res = chat.invoke(item)
@@ -62,6 +67,7 @@ def batched_multiprocess_auto_retry(
     pkl_path = get_saving_filename_safely(pkl_path) if pkl_path else None  # if pkl_path, result saved.
 
     outputs = [None] * len(items)
+    c = count()
     while not all(outputs):
         # printing remained queries if the number of remained queries is small
         num_of_remains = outputs.count(None)
@@ -83,6 +89,10 @@ def batched_multiprocess_auto_retry(
             pickle_bobj(outputs, pkl_path) if pkl_path else None
 
             time.sleep(sleep_between_chunk) if not all(outputs) else ...
+
+        # display a warning message if the global retry count exceeds 5.
+        if next(c) >= 5:
+            logger.warning("Retry count has exceeds 5. The process may be stuck due to an unresponsive item.")
     return outputs
 
 

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name="batched_chatgpt",
-    version="0.0.4",
+    version="0.0.5",
     description="Easy calling chatgpt with batched instances",
     packages=find_packages(),
     author="superheavytail",