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allow users to pass custom timing for replicate

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This commit is contained in:
ishaan-jaff 2023-09-06 18:32:40 -07:00
parent fc7ad0c245
commit 2880a7b6b4
3 changed files with 22 additions and 83 deletions
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14
litellm/tests/test_completion.py
View file

@ -10,7 +10,7 @@ sys.path.insert(
) # Adds the parent directory to the system path
import pytest
import litellm
from litellm import embedding, completion, text_completion
from litellm import embedding, completion, text_completion, completion_cost
litellm.vertex_project = "pathrise-convert-1606954137718"
litellm.vertex_location = "us-central1"
@ -185,14 +185,18 @@ def test_completion_cohere_stream():
def test_completion_openai():
try:
response = completion(model="gpt-3.5-turbo", messages=messages)
response_str = response["choices"][0]["message"]["content"]
response_str_2 = response.choices[0].message.content
print("response\n", response)
cost = completion_cost(completion_response=response)
print("Cost for completion call with gpt-3.5-turbo: ", f"${float(cost):.10f}")
assert response_str == response_str_2
assert type(response_str) == str
assert len(response_str) > 1
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_openai()
def test_completion_openai_prompt():
@ -361,6 +365,8 @@ def test_completion_replicate_llama_2():
custom_llm_provider="replicate"
)
print(response)
cost = completion_cost(completion_response=response)
print("Cost for completion call with llama-2: ", f"${float(cost):.10f}")
# Add any assertions here to check the response
response_str = response["choices"][0]["message"]["content"]
print(response_str)
@ -432,9 +438,11 @@ def test_completion_together_ai():
response = completion(model=model_name, messages=messages, max_tokens=256, logger_fn=logger_fn)
# Add any assertions here to check the response
print(response)
cost = completion_cost(completion_response=response)
print("Cost for completion call together-computer/llama-2-70b: ", f"${float(cost):.10f}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_together_ai()
# def test_customprompt_together_ai():
# try:
# litellm.register_prompt_template(

68
litellm/tests/test_completion_cost.py
View file

@ -1,68 +0,0 @@
import sys, os
import traceback
from dotenv import load_dotenv
load_dotenv()
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import pytest
import litellm
from litellm import embedding, completion, text_completion
from litellm.utils import completion_cost
user_message = "Write a short poem about the sky"
messages = [{"content": user_message, "role": "user"}]
def test_completion_togetherai_cost():
try:
response = completion(
model="together_ai/togethercomputer/llama-2-70b-chat",
messages=messages,
request_timeout=200,
)
# Add any assertions here to check the response
print(response)
print("Completion Cost: for togethercomputer/llama-2-70b-chat")
cost = completion_cost(completion_response=response)
formatted_string = f"${float(cost):.10f}"
print(formatted_string)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_togetherai_cost()
def test_completion_replicate_llama_2():
model_name = "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
try:
response = completion(
model=model_name,
messages=messages,
max_tokens=20,
custom_llm_provider="replicate"
)
print(response)
# Add any assertions here to check the response
response_str = response["choices"][0]["message"]["content"]
print(response_str)
# Add any assertions here to check the response
print(response)
print("Completion Cost: for togethercomputer/llama-2-70b-chat")
cost = completion_cost(completion_response=response)
formatted_string = f"${float(cost):.10f}"
print(formatted_string)
if type(response_str) != str:
pytest.fail(f"Error occurred: {e}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# v1
# test_completion_replicate_llama_2()

23
litellm/utils.py
View file

@ -594,20 +594,19 @@ def get_model_params_and_category(model_name):
return None
def get_replicate_completion_pricing(completion_response=None, run_time_in_seconds=0.0):
def get_replicate_completion_pricing(completion_response=None, total_time=0.0):
# see https://replicate.com/pricing
a100_40gb_price_per_second_public = 0.001150
# for all litellm currently supported LLMs, almost all requests go to a100_80gb
a100_80gb_price_per_second_public = 0.001400
a100_80gb_price_per_second_public = 0.001400 # assume all calls sent to A100 80GB for now
if total_time == 0.0:
start_time = completion_response['created']
end_time = completion_response["ended"]
total_time = end_time - start_time
start_time = completion_response['created']
end_time = completion_response["ended"]
run_time_in_seconds = end_time - start_time
print("total_replicate_run_time", total_time)
print("total_replicate_run_time", run_time_in_seconds)
return a100_80gb_price_per_second_public*run_time_in_seconds
return a100_80gb_price_per_second_public*total_time
def token_counter(model, text):
@ -657,10 +656,11 @@ def cost_per_token(model="gpt-3.5-turbo", prompt_tokens=0, completion_tokens=0):
def completion_cost(
completion_response=None,
model="gpt-3.5-turbo",
prompt="",
completion="",
completion_response=None
total_time=0.0, # used for replicate
):
# Handle Inputs to completion_cost
@ -686,8 +686,7 @@ def completion_cost(
model in litellm.replicate_models or
"replicate" in model
):
return get_replicate_completion_pricing(completion_response)
return get_replicate_completion_pricing(completion_response, total_time)
prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = cost_per_token(
model=model, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens
)