mirror of
https://github.com/BerriAI/litellm.git
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789 lines
27 KiB
Python
789 lines
27 KiB
Python
import sys, os
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import os
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import pytest
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import litellm
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from litellm import embedding, completion, text_completion, completion_cost
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user_message = "Write a short poem about the sky"
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messages = [{"content": user_message, "role": "user"}]
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def logger_fn(user_model_dict):
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print(f"user_model_dict: {user_model_dict}")
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def test_completion_custom_provider_model_name():
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try:
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response = completion(
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model="together_ai/togethercomputer/llama-2-70b-chat",
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messages=messages,
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logger_fn=logger_fn,
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)
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# Add any assertions here to check the response
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print(response)
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print(response['choices'][0]['finish_reason'])
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_custom_provider_model_name()
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def test_completion_claude():
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try:
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response = completion(
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model="claude-instant-1", messages=messages, logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_claude()
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# aleph alpha
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# def test_completion_aleph_alpha():
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# try:
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# response = completion(
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# model="luminous-base", messages=messages, logger_fn=logger_fn
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# )
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_aleph_alpha()
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# def test_completion_aleph_alpha_control_models():
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# try:
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# response = completion(
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# model="luminous-base-control", messages=messages, logger_fn=logger_fn
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# )
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_aleph_alpha_control_models()
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def test_completion_with_litellm_call_id():
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try:
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litellm.use_client = False
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response = completion(
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model="gpt-3.5-turbo", messages=messages)
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print(response)
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if 'litellm_call_id' in response:
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pytest.fail(f"Error occurred: litellm_call_id in response objects")
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litellm.use_client = True
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response2 = completion(
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model="gpt-3.5-turbo", messages=messages)
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if 'litellm_call_id' not in response2:
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pytest.fail(f"Error occurred: litellm_call_id not in response object when use_client = True")
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# Add any assertions here to check the response
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print(response2)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# commenting out as this is a flaky test on circle ci
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# def test_completion_nlp_cloud():
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# try:
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# messages = [
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# {"role": "system", "content": "You are a helpful assistant."},
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# {
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# "role": "user",
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# "content": "how does a court case get to the Supreme Court?",
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# },
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# ]
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# response = completion(model="dolphin", messages=messages, logger_fn=logger_fn)
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_nlp_cloud()
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# def test_completion_hf_api():
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# try:
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# user_message = "write some code to find the sum of two numbers"
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# messages = [{ "content": user_message,"role": "user"}]
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# api_base = "https://a8l9e3ucxinyl3oj.us-east-1.aws.endpoints.huggingface.cloud"
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# response = completion(model="huggingface/meta-llama/Llama-2-7b-chat-hf", messages=messages, api_base=api_base, logger_fn=logger_fn)
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# if "loading" in str(e):
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# pass
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_hf_api()
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# def test_completion_hf_deployed_api():
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# try:
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# user_message = "There's a llama in my garden 😱 What should I do?"
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# messages = [{ "content": user_message,"role": "user"}]
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# response = completion(model="huggingface/https://ji16r2iys9a8rjk2.us-east-1.aws.endpoints.huggingface.cloud", messages=messages, logger_fn=logger_fn)
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# using Non TGI or conversational LLMs
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# def hf_test_completion():
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# try:
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# # litellm.set_verbose=True
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# user_message = "My name is Merve and my favorite"
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# messages = [{ "content": user_message,"role": "user"}]
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# response = completion(
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# model="huggingface/roneneldan/TinyStories-3M",
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# messages=messages,
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# api_base="https://p69xlsj6rpno5drq.us-east-1.aws.endpoints.huggingface.cloud",
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# task=None,
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# )
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# hf_test_completion()
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def test_completion_cohere(): # commenting for now as the cohere endpoint is being flaky
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try:
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response = completion(
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model="command-nightly",
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messages=messages,
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max_tokens=100,
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logit_bias={40: 10},
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logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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print(response)
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response_str = response["choices"][0]["message"]["content"]
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response_str_2 = response.choices[0].message.content
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if type(response_str) != str:
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pytest.fail(f"Error occurred: {e}")
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if type(response_str_2) != str:
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pytest.fail(f"Error occurred: {e}")
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_cohere()
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def test_completion_openai():
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try:
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litellm.api_key = os.environ['OPENAI_API_KEY']
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response = completion(model="gpt-3.5-turbo", messages=messages)
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response_str = response["choices"][0]["message"]["content"]
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response_str_2 = response.choices[0].message.content
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print("response\n", response)
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cost = completion_cost(completion_response=response)
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print("Cost for completion call with gpt-3.5-turbo: ", f"${float(cost):.10f}")
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assert response_str == response_str_2
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assert type(response_str) == str
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assert len(response_str) > 1
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litellm.api_key = None
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_openai()
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def test_completion_openai_prompt():
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try:
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response = text_completion(
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model="gpt-3.5-turbo", prompt="What's the weather in SF?"
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)
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response_str = response["choices"][0]["message"]["content"]
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response_str_2 = response.choices[0].message.content
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print(response)
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assert response_str == response_str_2
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assert type(response_str) == str
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assert len(response_str) > 1
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_completion_text_openai():
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try:
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# litellm.set_verbose=True
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response = completion(model="text-davinci-003", messages=messages)
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# Add any assertions here to check the response
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_completion_gpt_instruct():
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try:
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response = completion(model="gpt-3.5-turbo-instruct", messages=messages)
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_gpt_instruct()
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def test_completion_openai_with_optional_params():
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try:
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response = completion(
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model="gpt-3.5-turbo",
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messages=messages,
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temperature=0.5,
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top_p=0.1,
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user="ishaan_dev@berri.ai",
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)
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# Add any assertions here to check the response
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_completion_openai_litellm_key():
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try:
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litellm.api_key = os.environ['OPENAI_API_KEY']
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# ensure key is set to None in .env and in openai.api_key
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os.environ['OPENAI_API_KEY'] = ""
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import openai
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openai.api_key = ""
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##########################################################
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response = completion(
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model="gpt-3.5-turbo",
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messages=messages,
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temperature=0.5,
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top_p=0.1,
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max_tokens=10,
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user="ishaan_dev@berri.ai",
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)
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# Add any assertions here to check the response
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print(response)
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###### reset environ key
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os.environ['OPENAI_API_KEY'] = litellm.api_key
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##### unset litellm var
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litellm.api_key = None
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_openai_litellm_key()
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# commented out for now, as openrouter is quite flaky - causing our deployments to fail. Please run this before pushing changes.
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# def test_completion_openrouter():
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# try:
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# response = completion(
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# model="google/palm-2-chat-bison",
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# messages=messages,
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# temperature=0.5,
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# top_p=0.1,
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# )
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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def test_completion_openai_with_more_optional_params():
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try:
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response = completion(
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model="gpt-3.5-turbo",
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messages=messages,
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temperature=0.5,
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top_p=0.1,
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n=2,
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max_tokens=150,
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presence_penalty=0.5,
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frequency_penalty=-0.5,
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logit_bias={123: 5},
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user="ishaan_dev@berri.ai",
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)
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# Add any assertions here to check the response
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print(response)
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response_str = response["choices"][0]["message"]["content"]
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response_str_2 = response.choices[0].message.content
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print(response["choices"][0]["message"]["content"])
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print(response.choices[0].message.content)
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if type(response_str) != str:
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pytest.fail(f"Error occurred: {e}")
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if type(response_str_2) != str:
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pytest.fail(f"Error occurred: {e}")
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# def test_completion_openai_azure_with_functions():
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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(
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# model="azure/chatgpt-functioncalling", messages=messages, stream=True
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# )
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# # Add any assertions here to check the response
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# print(response)
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# for chunk in response:
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# print(chunk)
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# print(chunk["choices"][0]["finish_reason"])
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_openai_azure_with_functions()
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def test_completion_azure():
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try:
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print("azure gpt-3.5 test\n\n")
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response = completion(
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model="azure/chatgpt-v-2",
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messages=messages,
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)
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# Add any assertions here to check the response
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_azure()
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# new azure test for using litellm. vars,
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# use the following vars in this test and make an azure_api_call
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# litellm.api_type = self.azure_api_type
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# litellm.api_base = self.azure_api_base
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# litellm.api_version = self.azure_api_version
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# litellm.api_key = self.api_key
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def test_completion_azure_with_litellm_key():
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try:
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print("azure gpt-3.5 test\n\n")
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import openai
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#### set litellm vars
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litellm.api_type = "azure"
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litellm.api_base = os.environ['AZURE_API_BASE']
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litellm.api_version = os.environ['AZURE_API_VERSION']
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litellm.api_key = os.environ['AZURE_API_KEY']
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######### UNSET ENV VARs for this ################
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os.environ['AZURE_API_BASE'] = ""
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os.environ['AZURE_API_VERSION'] = ""
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os.environ['AZURE_API_KEY'] = ""
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######### UNSET OpenAI vars for this ##############
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openai.api_type = ""
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openai.api_base = "gm"
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openai.api_version = "333"
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openai.api_key = "ymca"
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response = completion(
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model="azure/chatgpt-v-2",
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messages=messages,
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)
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# Add any assertions here to check the response
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print(response)
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######### RESET ENV VARs for this ################
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os.environ['AZURE_API_BASE'] = litellm.api_base
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os.environ['AZURE_API_VERSION'] = litellm.api_version
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os.environ['AZURE_API_KEY'] = litellm.api_key
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######### UNSET litellm vars
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litellm.api_type = None
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litellm.api_base = None
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litellm.api_version = None
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litellm.api_key = None
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_azure()
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def test_completion_azure_deployment_id():
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try:
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response = completion(
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deployment_id="chatgpt-v-2",
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model="gpt-3.5-turbo",
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messages=messages,
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)
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# Add any assertions here to check the response
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_azure_deployment_id()
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|
|
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# def test_completion_anthropic_litellm_proxy():
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# try:
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# response = completion(
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# model="claude-2",
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# messages=messages,
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# api_key="sk-litellm-1234"
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# )
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# # Add any assertions here to check the response
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|
# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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|
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|
# test_completion_anthropic_litellm_proxy()
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# def test_hf_conversational_task():
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# try:
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# messages = [{ "content": "There's a llama in my garden 😱 What should I do?","role": "user"}]
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# # e.g. Call 'facebook/blenderbot-400M-distill' hosted on HF Inference endpoints
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# response = completion(model="huggingface/facebook/blenderbot-400M-distill", messages=messages, task="conversational")
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# print(f"response: {response}")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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|
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# test_hf_conversational_task()
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# Replicate API endpoints are unstable -> throw random CUDA errors -> this means our tests can fail even if our tests weren't incorrect.
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# def test_completion_replicate_llama_2():
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# model_name = "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
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# try:
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# response = completion(
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# model=model_name,
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# messages=messages,
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# max_tokens=20,
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# custom_llm_provider="replicate"
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# )
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# print(response)
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# cost = completion_cost(completion_response=response)
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# print("Cost for completion call with llama-2: ", f"${float(cost):.10f}")
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# # Add any assertions here to check the response
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# response_str = response["choices"][0]["message"]["content"]
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# print(response_str)
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# if type(response_str) != str:
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# pytest.fail(f"Error occurred: {e}")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_replicate_llama_2()
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def test_completion_replicate_vicuna():
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model_name = "replicate/vicuna-13b:6282abe6a492de4145d7bb601023762212f9ddbbe78278bd6771c8b3b2f2a13b"
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try:
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response = completion(
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model=model_name,
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messages=messages,
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custom_llm_provider="replicate",
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temperature=0.1,
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max_tokens=20,
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)
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print(response)
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# Add any assertions here to check the response
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|
response_str = response["choices"][0]["message"]["content"]
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print(response_str)
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if type(response_str) != str:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
|
|
# def test_completion_replicate_stability_stream():
|
|
# model_name = "stability-ai/stablelm-tuned-alpha-7b:c49dae362cbaecd2ceabb5bd34fdb68413c4ff775111fea065d259d577757beb"
|
|
# try:
|
|
# response = completion(
|
|
# model=model_name,
|
|
# messages=messages,
|
|
# # stream=True,
|
|
# custom_llm_provider="replicate",
|
|
# )
|
|
# # print(response)
|
|
# # Add any assertions here to check the response
|
|
# # for chunk in response:
|
|
# # print(chunk["choices"][0]["delta"])
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
# test_completion_replicate_stability_stream()
|
|
|
|
|
|
|
|
|
|
|
|
######## Test TogetherAI ########
|
|
def test_completion_together_ai():
|
|
model_name = "togethercomputer/llama-2-70b-chat"
|
|
try:
|
|
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(
|
|
# model="OpenAssistant/llama2-70b-oasst-sft-v10",
|
|
# roles={"system":"<|im_start|>system", "assistant":"<|im_start|>assistant", "user":"<|im_start|>user"}, # tell LiteLLM how you want to map the openai messages to this model
|
|
# pre_message_sep= "\n",
|
|
# post_message_sep= "\n"
|
|
# )
|
|
# response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
def test_completion_sagemaker():
|
|
try:
|
|
response = completion(
|
|
model="sagemaker/jumpstart-dft-meta-textgeneration-llama-2-7b",
|
|
messages=messages,
|
|
temperature=0.2,
|
|
max_tokens=80,
|
|
logger_fn=logger_fn
|
|
)
|
|
# Add any assertions here to check the response
|
|
print(response)
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
def test_completion_bedrock_titan():
|
|
try:
|
|
response = completion(
|
|
model="bedrock/amazon.titan-tg1-large",
|
|
messages=messages,
|
|
temperature=0.2,
|
|
max_tokens=200,
|
|
top_p=0.8,
|
|
logger_fn=logger_fn
|
|
)
|
|
# Add any assertions here to check the response
|
|
print(response)
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
# test_completion_bedrock_titan()
|
|
|
|
|
|
def test_completion_bedrock_ai21():
|
|
try:
|
|
litellm.set_verbose = False
|
|
response = completion(
|
|
model="bedrock/ai21.j2-mid",
|
|
messages=messages,
|
|
temperature=0.2,
|
|
top_p=0.2,
|
|
max_tokens=20
|
|
)
|
|
# Add any assertions here to check the response
|
|
print(response)
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
######## Test VLLM ########
|
|
# def test_completion_vllm():
|
|
# try:
|
|
# response = completion(
|
|
# model="vllm/facebook/opt-125m",
|
|
# messages=messages,
|
|
# temperature=0.2,
|
|
# max_tokens=80,
|
|
# )
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_completion_vllm()
|
|
|
|
# def test_completion_hosted_chatCompletion():
|
|
# # this tests calling a server where vllm is hosted
|
|
# # this should make an openai.Completion() call to the specified api_base
|
|
# # send a request to this proxy server: https://replit.com/@BerriAI/openai-proxy#main.py
|
|
# # it checks if model == facebook/opt-125m and returns test passed
|
|
# try:
|
|
# litellm.set_verbose = True
|
|
# response = completion(
|
|
# model="facebook/opt-125m",
|
|
# messages=messages,
|
|
# temperature=0.2,
|
|
# max_tokens=80,
|
|
# api_base="https://openai-proxy.berriai.repl.co",
|
|
# custom_llm_provider="openai"
|
|
# )
|
|
# print(response)
|
|
|
|
# if response['choices'][0]['message']['content'] != "passed":
|
|
# # see https://replit.com/@BerriAI/openai-proxy#main.py
|
|
# pytest.fail(f"Error occurred: proxy server did not respond")
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_completion_hosted_chatCompletion()
|
|
|
|
# def test_completion_custom_api_base():
|
|
# try:
|
|
# response = completion(
|
|
# model="custom/meta-llama/Llama-2-13b-hf",
|
|
# messages=messages,
|
|
# temperature=0.2,
|
|
# max_tokens=10,
|
|
# api_base="https://api.autoai.dev/inference",
|
|
# request_timeout=300,
|
|
# )
|
|
# # Add any assertions here to check the response
|
|
# print("got response\n", response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_completion_custom_api_base()
|
|
|
|
# def test_vertex_ai():
|
|
# litellm.vertex_project = "hardy-device-386718"
|
|
# litellm.vertex_location = "us-central1"
|
|
# test_models = litellm.vertex_chat_models + litellm.vertex_code_chat_models + litellm.vertex_text_models + litellm.vertex_code_text_models
|
|
# for model in test_models:
|
|
# try:
|
|
# print("making request", model)
|
|
# response = completion(model=model, messages=[{"role": "user", "content": "write code for saying hi"}])
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
# test_vertex_ai()
|
|
|
|
# def test_vertex_ai_stream():
|
|
# litellm.vertex_project = "hardy-device-386718"
|
|
# litellm.vertex_location = "us-central1"
|
|
# test_models = litellm.vertex_chat_models + litellm.vertex_code_chat_models + litellm.vertex_text_models + litellm.vertex_code_text_models
|
|
# for model in test_models:
|
|
# try:
|
|
# print("making request", model)
|
|
# response = completion(model=model, messages=[{"role": "user", "content": "write code for saying hi"}], stream=True)
|
|
# print(response)
|
|
# for chunk in response:
|
|
# print(chunk)
|
|
# # pass
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
# test_vertex_ai_stream()
|
|
|
|
|
|
def test_completion_with_fallbacks():
|
|
fallbacks = ["gpt-3.5-turb", "gpt-3.5-turbo", "command-nightly"]
|
|
try:
|
|
response = completion(
|
|
model="bad-model", messages=messages, force_timeout=120, fallbacks=fallbacks
|
|
)
|
|
# Add any assertions here to check the response
|
|
print(response)
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
|
|
# def test_baseten():
|
|
# try:
|
|
|
|
# response = completion(model="baseten/7qQNLDB", messages=messages, logger_fn=logger_fn)
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_baseten()
|
|
# def test_baseten_falcon_7bcompletion():
|
|
# model_name = "qvv0xeq"
|
|
# try:
|
|
# response = completion(model=model_name, messages=messages, custom_llm_provider="baseten")
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
# test_baseten_falcon_7bcompletion()
|
|
|
|
# def test_baseten_falcon_7bcompletion_withbase():
|
|
# model_name = "qvv0xeq"
|
|
# litellm.api_base = "https://app.baseten.co"
|
|
# try:
|
|
# response = completion(model=model_name, messages=messages)
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
# litellm.api_base = None
|
|
|
|
# test_baseten_falcon_7bcompletion_withbase()
|
|
|
|
|
|
# def test_baseten_wizardLMcompletion_withbase():
|
|
# model_name = "q841o8w"
|
|
# litellm.api_base = "https://app.baseten.co"
|
|
# try:
|
|
# response = completion(model=model_name, messages=messages)
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_baseten_wizardLMcompletion_withbase()
|
|
|
|
# def test_baseten_mosaic_ML_completion_withbase():
|
|
# model_name = "31dxrj3"
|
|
# litellm.api_base = "https://app.baseten.co"
|
|
# try:
|
|
# response = completion(model=model_name, messages=messages)
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
#### Test A121 ###################
|
|
def test_completion_ai21():
|
|
model_name = "j2-light"
|
|
try:
|
|
response = completion(model=model_name, messages=messages)
|
|
# Add any assertions here to check the response
|
|
print(response)
|
|
except Exception as e:
|
|
pytest.fail(f"Error occurred: {e}")
|
|
|
|
# test_completion_ai21()
|
|
# test config file with completion #
|
|
# def test_completion_openai_config():
|
|
# try:
|
|
# litellm.config_path = "../config.json"
|
|
# litellm.set_verbose = True
|
|
# response = litellm.config_completion(messages=messages)
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# litellm.config_path = None
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# import asyncio
|
|
# def test_completion_together_ai_stream():
|
|
# user_message = "Write 1pg about YC & litellm"
|
|
# messages = [{ "content": user_message,"role": "user"}]
|
|
# try:
|
|
# response = completion(model="togethercomputer/llama-2-70b-chat", messages=messages, stream=True, max_tokens=800)
|
|
# print(response)
|
|
# asyncio.run(get_response(response))
|
|
# # print(string_response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# async def get_response(generator):
|
|
# async for elem in generator:
|
|
# print(elem)
|
|
# return
|
|
|
|
# test_completion_together_ai_stream()
|