forked from phoenix/litellm-mirror
custom timeout decorator
This commit is contained in:
parent
79847145f8
commit
7b2901be9e
10 changed files with 121 additions and 16 deletions
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@ -25,6 +25,7 @@ open_ai_embedding_models = [
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'text-embedding-ada-002'
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'text-embedding-ada-002'
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]
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]
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from .timeout import timeout
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from .utils import client, logging, exception_type # Import all the symbols from main.py
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from .utils import client, logging, exception_type # Import all the symbols from main.py
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from .main import * # Import all the symbols from main.py
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from .main import * # Import all the symbols from main.py
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litellm/__pycache__/timeout.cpython-311.pyc
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litellm/__pycache__/timeout.cpython-311.pyc
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@ -6,8 +6,7 @@ import traceback
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import dotenv
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import dotenv
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import traceback
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import traceback
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import litellm
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import litellm
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from litellm import client, logging, exception_type
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from litellm import client, logging, exception_type, timeout, success_callback, failure_callback
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from litellm import success_callback, failure_callback
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import random
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import random
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####### ENVIRONMENT VARIABLES ###################
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####### ENVIRONMENT VARIABLES ###################
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dotenv.load_dotenv() # Loading env variables using dotenv
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dotenv.load_dotenv() # Loading env variables using dotenv
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@ -59,7 +58,7 @@ def get_optional_params(
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####### COMPLETION ENDPOINTS ################
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####### COMPLETION ENDPOINTS ################
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#############################################
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#############################################
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@client
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@client
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@func_set_timeout(180, allowOverride=True) ## https://pypi.org/project/func-timeout/ - timeouts, in case calls hang (e.g. Azure)
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@timeout(60) ## set timeouts, in case calls hang (e.g. Azure)
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def completion(
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def completion(
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model, messages, # required params
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model, messages, # required params
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# Optional OpenAI params: see https://platform.openai.com/docs/api-reference/chat/create
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# Optional OpenAI params: see https://platform.openai.com/docs/api-reference/chat/create
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@ -67,7 +66,7 @@ def completion(
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temperature=1, top_p=1, n=1, stream=False, stop=None, max_tokens=float('inf'),
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temperature=1, top_p=1, n=1, stream=False, stop=None, max_tokens=float('inf'),
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presence_penalty=0, frequency_penalty=0, logit_bias={}, user="",
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presence_penalty=0, frequency_penalty=0, logit_bias={}, user="",
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# Optional liteLLM function params
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# Optional liteLLM function params
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*, forceTimeout=60, azure=False, logger_fn=None, verbose=False
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*, force_timeout=60, azure=False, logger_fn=None, verbose=False
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):
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):
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try:
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try:
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# check if user passed in any of the OpenAI optional params
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# check if user passed in any of the OpenAI optional params
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@ -1,11 +1,3 @@
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from openai.error import AuthenticationError, InvalidRequestError, RateLimitError, OpenAIError
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import os
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import sys
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import traceback
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sys.path.insert(0, os.path.abspath('../..')) # Adds the parent directory to the system path
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import litellm
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from litellm import embedding, completion
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from concurrent.futures import ThreadPoolExecutor
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#### What this tests ####
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#### What this tests ####
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# This tests exception mapping -> trigger an exception from an llm provider -> assert if output is of the expected type
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# This tests exception mapping -> trigger an exception from an llm provider -> assert if output is of the expected type
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@ -16,6 +8,15 @@ from concurrent.futures import ThreadPoolExecutor
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# Approach: Run each model through the test -> assert if the correct error (always the same one) is triggered
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# Approach: Run each model through the test -> assert if the correct error (always the same one) is triggered
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from openai.error import AuthenticationError, InvalidRequestError, RateLimitError, OpenAIError
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import os
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import sys
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import traceback
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sys.path.insert(0, os.path.abspath('../..')) # Adds the parent directory to the system path
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import litellm
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from litellm import embedding, completion
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from concurrent.futures import ThreadPoolExecutor
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models = ["gpt-3.5-turbo", "chatgpt-test", "claude-instant-1", "command-nightly", "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"]
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models = ["gpt-3.5-turbo", "chatgpt-test", "claude-instant-1", "command-nightly", "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"]
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# Test 1: Rate Limit Errors
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# Test 1: Rate Limit Errors
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26
litellm/tests/test_timeout.py
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26
litellm/tests/test_timeout.py
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@ -0,0 +1,26 @@
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#### What this tests ####
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# This tests the timeout decorator
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import sys, os
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import traceback
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sys.path.insert(0, os.path.abspath('../..')) # Adds the parent directory to the system path
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import time
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from litellm import timeout
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@timeout(10)
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def stop_after_10_s(force_timeout=60):
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print("Stopping after 10 seconds")
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time.sleep(10)
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return
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start_time = time.time()
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try:
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stop_after_10_s(force_timeout=1)
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except:
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pass
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end_time = time.time()
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print(f"total time: {end_time-start_time}")
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80
litellm/timeout.py
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80
litellm/timeout.py
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@ -0,0 +1,80 @@
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"""
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Module containing "timeout" decorator for sync and async callables.
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"""
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import asyncio
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from concurrent import futures
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from inspect import iscoroutinefunction
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from functools import wraps
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from threading import Thread
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from openai.error import Timeout
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def timeout(
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timeout_duration: float = None, exception_to_raise = Timeout
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):
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"""
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Wraps a function to raise the specified exception if execution time
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is greater than the specified timeout.
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Works with both synchronous and asynchronous callables, but with synchronous ones will introduce
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some overhead due to the backend use of threads and asyncio.
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:param float timeout_duration: Timeout duration in seconds. If none callable won't time out.
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:param OpenAIError exception_to_raise: Exception to raise when the callable times out.
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Defaults to TimeoutError.
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:return: The decorated function.
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:rtype: callable
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"""
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def decorator(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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async def async_func():
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return func(*args, **kwargs)
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thread = _LoopWrapper()
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thread.start()
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future = asyncio.run_coroutine_threadsafe(async_func(), thread.loop)
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try:
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local_timeout_duration = timeout_duration
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if "force_timeout" in kwargs:
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local_timeout_duration = kwargs["force_timeout"]
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result = future.result(timeout=local_timeout_duration)
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except futures.TimeoutError:
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thread.stop_loop()
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raise exception_to_raise()
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thread.stop_loop()
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return result
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@wraps(func)
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async def async_wrapper(*args, **kwargs):
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try:
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value = await asyncio.wait_for(
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func(*args, **kwargs), timeout=timeout_duration
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)
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return value
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except asyncio.TimeoutError:
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raise exception_to_raise()
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if iscoroutinefunction(func):
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return async_wrapper
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return wrapper
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return decorator
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class _LoopWrapper(Thread):
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def __init__(self):
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super().__init__(daemon=True)
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self.loop = asyncio.new_event_loop()
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def run(self) -> None:
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self.loop.run_forever()
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self.loop.call_soon_threadsafe(self.loop.close)
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def stop_loop(self):
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for task in asyncio.all_tasks(self.loop):
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task.cancel()
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self.loop.call_soon_threadsafe(self.loop.stop)
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@ -1,6 +1,5 @@
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openai
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openai
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cohere
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cohere
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func_timeout
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anthropic
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anthropic
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replicate
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replicate
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pytest
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pytest
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5
setup.py
5
setup.py
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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
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setup(
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setup(
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name='litellm',
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name='litellm',
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version='0.1.206',
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version='0.1.207',
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description='Library to easily interface with LLM API providers',
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description='Library to easily interface with LLM API providers',
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author='BerriAI',
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author='BerriAI',
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packages=[
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packages=[
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@ -11,11 +11,10 @@ setup(
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install_requires=[
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install_requires=[
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'openai',
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'openai',
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'cohere',
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'cohere',
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'func_timeout',
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'pytest',
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'pytest',
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'anthropic',
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'anthropic',
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'replicate',
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'replicate',
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'python-dotenv',
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'python-dotenv',
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'openai[datalib]'
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'openai[datalib]',
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],
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],
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)
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)
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