mirror of
https://github.com/BerriAI/litellm.git
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637 lines
21 KiB
Python
637 lines
21 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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litellm.vertex_project = "pathrise-convert-1606954137718"
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litellm.vertex_location = "us-central1"
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litellm.use_client = True
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# from infisical import InfisicalClient
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# litellm.set_verbose = True
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# litellm.secret_manager_client = InfisicalClient(token=os.environ["INFISICAL_TOKEN"])
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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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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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# 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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def test_completion_claude_stream():
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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="claude-2", messages=messages, stream=True)
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# Add any assertions here to check the response
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for chunk in response:
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print(chunk["choices"][0]["delta"]) # same as openai format
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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_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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# response = completion(model="stabilityai/stablecode-completion-alpha-3b-4k", messages=messages, custom_llm_provider="huggingface", 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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# 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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# )
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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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# print(f"str response{response_str}")
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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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def test_completion_cohere_stream():
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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(
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model="command-nightly", messages=messages, stream=True, max_tokens=50
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)
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# Add any assertions here to check the response
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for chunk in response:
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print(chunk["choices"][0]["delta"]) # same as openai format
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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():
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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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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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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_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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# 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_with_stream():
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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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stream=True,
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frequency_penalty=-0.5,
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logit_bias={27000: 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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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_completion_openai_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="gpt-3.5-turbo", messages=messages, functions=function1
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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_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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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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# 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:
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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_vicuna()
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def test_completion_replicate_llama_stream():
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model_name = "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"
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try:
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response = completion(model=model_name, messages=messages, stream=True)
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# Add any assertions here to check the response
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for result in response:
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print(result)
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# chunk_text = result['choices'][0]['delta']['content']
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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_stream()
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# def test_completion_replicate_stability_stream():
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# model_name = "stability-ai/stablelm-tuned-alpha-7b:c49dae362cbaecd2ceabb5bd34fdb68413c4ff775111fea065d259d577757beb"
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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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# # stream=True,
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# custom_llm_provider="replicate",
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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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# # for chunk in response:
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# # print(chunk["choices"][0]["delta"])
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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_replicate_stability_stream()
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######## Test TogetherAI ########
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def test_completion_together_ai():
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model_name = "togethercomputer/llama-2-70b-chat"
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try:
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response = completion(model=model_name, messages=messages, max_tokens=256, 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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cost = completion_cost(completion_response=response)
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print("Cost for completion call together-computer/llama-2-70b: ", f"${float(cost):.10f}")
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# test_completion_together_ai()
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# def test_customprompt_together_ai():
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# try:
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# litellm.register_prompt_template(
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# model="OpenAssistant/llama2-70b-oasst-sft-v10",
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# 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
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# pre_message_sep= "\n",
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# post_message_sep= "\n"
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# )
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# response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", 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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def test_completion_sagemaker():
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try:
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response = completion(
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model="sagemaker/jumpstart-dft-meta-textgeneration-llama-2-7b",
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messages=messages,
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temperature=0.2,
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max_tokens=80,
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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 VLLM ########
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# def test_completion_vllm():
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# try:
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# response = completion(
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# model="vllm/facebook/opt-125m",
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# messages=messages,
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# temperature=0.2,
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# max_tokens=80,
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# )
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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_vllm()
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# def test_completion_custom_api_base():
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# try:
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# response = completion(
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# model="custom/meta-llama/Llama-2-13b-hf",
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# messages=messages,
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# temperature=0.2,
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# max_tokens=10,
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# api_base="https://api.autoai.dev/inference",
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# request_timeout=300,
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# )
|
|
# # 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():
|
|
# model_name = "chat-bison"
|
|
# try:
|
|
# response = completion(model=model_name, messages=messages, logger_fn=logger_fn)
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
# def test_petals():
|
|
# model_name = "stabilityai/StableBeluga2"
|
|
# try:
|
|
# response = completion(
|
|
# model=model_name,
|
|
# messages=messages,
|
|
# custom_llm_provider="petals",
|
|
# force_timeout=120,
|
|
# )
|
|
# # Add any assertions here to check the response
|
|
# print(response)
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
|
|
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/RqgAEn0", 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}")
|
|
|
|
# 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 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()
|