forked from phoenix/litellm-mirror
(feat) proxy_server add a track_cost_callback for streaming
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parent
68b655df51
commit
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2 changed files with 37 additions and 26 deletions
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@ -1,4 +1,6 @@
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2023-10-09 14:46:28 - Model gpt-3.5-turbo-0613 Cost: 6.1e-05
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2023-10-09 14:46:29 - Model gpt-3.5-turbo Cost: 0.0
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2023-10-09 14:48:18 - Model gpt-3.5-turbo-0613 Cost: 0.00004700
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2023-10-09 14:48:18 - Model gpt-3.5-turbo Cost: 0.00000000
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2023-10-10 11:30:40 - Model gpt-3.5-turbo Cost: $0.00126900
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2023-10-10 11:31:02 - Model gpt-3.5-turbo Cost: $0.00131700
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2023-10-10 11:31:57 - Model gpt-3.5-turbo Cost: $0.00132450
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2023-10-10 11:32:04 - Model gpt-3.5-turbo Cost: $0.00148000
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2023-10-10 11:32:05 - Model gpt-3.5-turbo Cost: $0.00138800
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2023-10-10 11:32:14 - Model gpt-3.5-turbo Cost: $0.00160450
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@ -118,36 +118,45 @@ def data_generator(response):
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print_verbose(f"returned chunk: {chunk}")
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yield f"data: {json.dumps(chunk)}\n\n"
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def custom_callback(
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def track_cost_callback(
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kwargs, # kwargs to completion
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completion_response, # response from completion
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start_time, end_time # start/end time
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):
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# Your custom code here
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print("LITELLM: in custom callback function")
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# print("kwargs", kwargs)
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# print("start_time", start_time)
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# print("end_time", end_time)
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if "complete_streaming_response" in kwargs:
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print("GOT COMPLETE STREAMING RESPINSE", kwargs["complete_streaming_response"])
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response_cost = litellm.completion_cost(
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completion_response=kwargs["complete_streaming_response"]
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try:
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# init logging config
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logging.basicConfig(
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filename='cost.log',
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level=logging.INFO,
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format='%(asctime)s - %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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print("response_cost", response_cost)
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else:
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print("completion_response", completion_response)
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response_cost = litellm.completion_cost(completion_response=completion_response)
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logging.basicConfig(
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filename='cost.log',
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level=logging.INFO,
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format='%(asctime)s - %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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logging.info(f"Model {completion_response.model} Cost: ${response_cost:.8f}")
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# check if it has collected an entire stream response
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if "complete_streaming_response" in kwargs:
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# for tracking streaming cost we pass the "messages" and the output_text to litellm.completion_cost
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completion_response=kwargs["complete_streaming_response"]
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input_text = kwargs["messages"]
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output_text = completion_response["choices"][0]["message"]["content"]
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response_cost = litellm.completion_cost(
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model = kwargs["model"],
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messages = input_text,
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completion=output_text
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)
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print("streaming response_cost", response_cost)
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logging.info(f"Model {kwargs['model']} Cost: ${response_cost:.8f}")
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# for non streaming responses
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else:
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# we pass the completion_response obj
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if kwargs["stream"] != True:
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response_cost = litellm.completion_cost(completion_response=completion_response)
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print("regular response_cost", response_cost)
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logging.info(f"Model {completion_response.model} Cost: ${response_cost:.8f}")
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except:
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pass
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litellm.success_callback = [custom_callback]
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litellm.success_callback = [track_cost_callback]
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def litellm_completion(data, type):
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try:
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