mirror of
https://github.com/BerriAI/litellm.git
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169 lines
5.5 KiB
Python
169 lines
5.5 KiB
Python
import sys
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import os
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import io, asyncio
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# import logging
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# logging.basicConfig(level=logging.DEBUG)
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sys.path.insert(0, os.path.abspath('../..'))
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from litellm import completion
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import litellm
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litellm.num_retries = 3
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litellm.success_callback = ["dynamodb"]
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import time
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import pytest
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def test_dynamo_logging_async():
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try:
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litellm.set_verbose = True
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async def _test():
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return await litellm.acompletion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content":"This is a test"}],
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max_tokens=100,
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temperature=0.7,
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user = "ishaan-2"
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)
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response = asyncio.run(_test())
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print(f"response: {response}")
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except litellm.Timeout as e:
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pass
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except Exception as e:
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pytest.fail(f"An exception occurred - {e}")
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# test_dynamo_logging_async()
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def test_dynamo_logging_async_stream():
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try:
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litellm.set_verbose = True
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async def _test():
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response = await litellm.acompletion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content":"This is a test"}],
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max_tokens=100,
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temperature=0.7,
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user = "ishaan-2",
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stream=True
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)
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async for chunk in response:
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pass
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asyncio.run(_test())
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except litellm.Timeout as e:
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pass
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except Exception as e:
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pytest.fail(f"An exception occurred - {e}")
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# test_dynamo_logging_async_stream()
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# @pytest.mark.skip(reason="beta test - checking langfuse output")
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# def test_langfuse_logging():
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# try:
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# pre_langfuse_setup()
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# litellm.set_verbose = True
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# response = completion(model="claude-instant-1.2",
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# messages=[{
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# "role": "user",
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# "content": "Hi 👋 - i'm claude"
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# }],
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# max_tokens=10,
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# temperature=0.2,
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# )
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# print(response)
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# # time.sleep(5)
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# # # check langfuse.log to see if there was a failed response
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# # search_logs("langfuse.log")
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# except litellm.Timeout as e:
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# pass
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# except Exception as e:
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# pytest.fail(f"An exception occurred - {e}")
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# test_langfuse_logging()
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# @pytest.mark.skip(reason="beta test - checking langfuse output")
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# def test_langfuse_logging_stream():
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# try:
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# litellm.set_verbose=True
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# response = completion(model="anyscale/meta-llama/Llama-2-7b-chat-hf",
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# messages=[{
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# "role": "user",
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# "content": "this is a streaming test for llama2 + langfuse"
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# }],
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# max_tokens=20,
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# temperature=0.2,
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# stream=True
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# )
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# print(response)
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# for chunk in response:
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# pass
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# # print(chunk)
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# except litellm.Timeout as e:
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# pass
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# except Exception as e:
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# print(e)
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# # test_langfuse_logging_stream()
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# @pytest.mark.skip(reason="beta test - checking langfuse output")
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# def test_langfuse_logging_custom_generation_name():
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# try:
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# litellm.set_verbose=True
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# response = completion(model="gpt-3.5-turbo",
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# messages=[{
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# "role": "user",
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# "content": "Hi 👋 - i'm claude"
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# }],
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# max_tokens=10,
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# metadata = {
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# "langfuse/foo": "bar",
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# "langsmith/fizz": "buzz",
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# "prompt_hash": "asdf98u0j9131123"
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# }
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# )
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# print(response)
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# except litellm.Timeout as e:
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# pass
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# except Exception as e:
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# pytest.fail(f"An exception occurred - {e}")
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# print(e)
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# # test_langfuse_logging_custom_generation_name()
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# @pytest.mark.skip(reason="beta test - checking langfuse output")
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# def test_langfuse_logging_function_calling():
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# function1 = [
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# {
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# "name": "get_current_weather",
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# "description": "Get the current weather in a given location",
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# "parameters": {
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# "type": "object",
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# "properties": {
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# "location": {
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# "type": "string",
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# "description": "The city and state, e.g. San Francisco, CA",
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# },
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# "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
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# },
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# "required": ["location"],
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# },
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# }
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# ]
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# try:
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# response = completion(model="gpt-3.5-turbo",
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# messages=[{
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# "role": "user",
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# "content": "what's the weather in boston"
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# }],
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# temperature=0.1,
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# functions=function1,
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# )
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# print(response)
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# except litellm.Timeout as e:
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# pass
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# except Exception as e:
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# print(e)
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# # test_langfuse_logging_function_calling()
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