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(feat) proxy_server new cost.json on litellm. Track daily cost & num_requests

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ishaan-jaff 2023-10-12 11:37:35 -07:00
parent 171b8fce0a
commit e5ae870dd5
2 changed files with 47 additions and 10 deletions
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49
litellm/proxy/proxy_server.py
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@ -255,16 +255,20 @@ def track_cost_callback(
completion_response, # response from completion
start_time, end_time # start/end time
):
# track cost like this
# {
# "Oct12": {
# "gpt-4": 10,
# "claude-2": 12.01,
# },
# "Oct 15": {
# "ollama/llama2": 0.0,
# "gpt2": 1.2
# }
# }
try:
# init logging config
logging.basicConfig(
filename='cost.log',
level=logging.INFO,
format='%(asctime)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S'
)
# check if it has collected an entire stream response
# for streaming responses
if "complete_streaming_response" in kwargs:
# for tracking streaming cost we pass the "messages" and the output_text to litellm.completion_cost
completion_response=kwargs["complete_streaming_response"]
@ -275,8 +279,8 @@ def track_cost_callback(
messages = input_text,
completion=output_text
)
model = kwargs['model']
print("streaming response_cost", response_cost)
logging.info(f"Model {kwargs['model']} Cost: ${response_cost:.8f}")
# for non streaming responses
else:
@ -284,7 +288,32 @@ def track_cost_callback(
if kwargs["stream"] != True:
response_cost = litellm.completion_cost(completion_response=completion_response)
print("regular response_cost", response_cost)
logging.info(f"Model {completion_response.model} Cost: ${response_cost:.8f}")
model = completion_response["model"]
# read/write from json for storing daily model costs
cost_data = {}
try:
with open("costs.json") as f:
cost_data = json.load(f)
except FileNotFoundError:
cost_data = {}
import datetime
date = datetime.datetime.now().strftime("%b-%d-%Y")
if date not in cost_data:
cost_data[date] = {}
if kwargs["model"] in cost_data[date]:
cost_data[date][kwargs["model"]]["cost"] += response_cost
cost_data[date][kwargs["model"]]["num_requests"] += 1
else:
cost_data[date][kwargs["model"]] = {
"cost": response_cost,
"num_requests": 1
}
with open("costs.json", "w") as f:
json.dump(cost_data, f, indent=2)
except:
pass