openai-cost-logger 0.5.1

OpenAI Cost Logger

OpenAI Cost Logger

• Simple cost logger for OpenAI requests.

• Track the cost of every request you make to OpenAI and visualize them in a user-friendly way.

• Homepage on PyPI.

• Demo file with a usage example.

How to install:

• pip install openai-cost-logger

• from openai_cost_logger import OpenAICostLogger
  from openai_cost_logger import OpenAICostLoggerViz
  from openai_cost_logger import OpenAICostLoggerUtils
  from openai_cost_logger import OpenAICostLogger_Singleton
  from openai_cost_logger import DEFAULT_LOG_PATH, MODELS_COST

Key Features:

• Track the cost of every request you make and save them in a JSON file.

• Choose the feature you want to track (prompt_tokens, completion_tokens, completion, prompt, etc.).

• Check the cost of your requests filtering by model or strftime aggregation (see the docs).

Models supported:

• The generation of responses is totally up to the user. The library supports every model whose response contains the fields usage.prompt_tokens and usage.total_tokens (e.g. chat completions, embeddings, etc.).

Multithreading:

• Be aware that the classic cost logger is not thread-safe.

• If you want to use it in a multithreading environment, you should use the thread-safe version of the logger: OpenAICostLogger_Singleton. The interface is the same as the classic logger. This will prevent multiple threads from writing to the same file at the same time.

Note:

• Every cost is specified per million tokens.

• If you don’t specify the cost, the library will look to the MODELS_COST dictionary and get the cost of the model you are using. Be aware that if the model is not in the dictionary, an exception will be raised.

Viz example: