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show pricing for tg ai completion
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parent
04f8b20651
commit
1ba6b6761b
2 changed files with 46 additions and 23 deletions
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@ -563,7 +563,6 @@ def client(original_function):
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): # make it easy to get to the debugger logs if you've initialized it
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e.message += f"\n Check the log in your dashboard - {liteDebuggerClient.dashboard_url}"
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raise e
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return wrapper
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@ -571,7 +570,7 @@ def client(original_function):
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# Extract the number of billion parameters from the model name
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# together_compute
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# only used for together_computer LLMs
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def get_model_params_and_category(model_name):
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import re
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params_match = re.search(r'(\d+b)', model_name) # catch all decimals like 3b, 70b, etc
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@ -647,15 +646,23 @@ def cost_per_token(model="gpt-3.5-turbo", prompt_tokens=0, completion_tokens=0):
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def completion_cost(
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model="gpt-3.5-turbo",
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prompt="",
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completion=""
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completion="",
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completion_response=None
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):
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prompt_tokens = token_counter(model=model, text=prompt)
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completion_tokens = token_counter(model=model, text=completion)
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prompt_tokens = 0
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completion_tokens = 0
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if completion_response != None:
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# get input/output tokens from completion_response
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prompt_tokens = completion_response['usage']['prompt_tokens']
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completion_tokens = completion_response['usage']['completion_tokens']
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model = completion_response['model'] # get model from completion_response
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else:
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prompt_tokens = token_counter(model=model, text=prompt)
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completion_tokens = token_counter(model=model, text=completion)
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if "togethercomputer" in model:
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# together ai prices based on size of llm
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# get_model_params_and_category takes a model name and returns the category of LLM size it is in model_prices_and_context_window.json
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model = get_model_params_and_category(model)
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# print(together_catgeory)
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prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = cost_per_token(
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model=model, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens
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)
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