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* use base_llm_http_handler for clarifai * fix clarifai completion * handle faking streaming base llm http handler * add fake streaming for clarifai * add FakeStreamResponseIterator for base model iterator * fix get_model_response_iterator * fix base model iterator * fix base model iterator * add support for faking sync streams clarfiai * add fake streaming for clarifai * remove unused code * fix import * fix llm http handler * test_async_completion_clarifai * fix clarifai tests * fix linting
109 lines
2.8 KiB
Python
109 lines
2.8 KiB
Python
import sys, os
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import traceback
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from dotenv import load_dotenv
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import asyncio, logging
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load_dotenv()
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import os, io
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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 (
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embedding,
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completion,
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acompletion,
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acreate,
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completion_cost,
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Timeout,
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ModelResponse,
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)
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from litellm import RateLimitError
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# litellm.num_retries = 3
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litellm.cache = None
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litellm.success_callback = []
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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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@pytest.fixture(autouse=True)
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def reset_callbacks():
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print("\npytest fixture - resetting callbacks")
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litellm.success_callback = []
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litellm._async_success_callback = []
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litellm.failure_callback = []
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litellm.callbacks = []
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@pytest.mark.skip(reason="Account rate limited.")
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def test_completion_clarifai_claude_2_1():
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print("calling clarifai claude completion")
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import os
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clarifai_pat = os.environ["CLARIFAI_API_KEY"]
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try:
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response = completion(
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model="clarifai/anthropic.completion.claude-2_1",
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num_retries=3,
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messages=messages,
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max_tokens=10,
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temperature=0.1,
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)
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print(response)
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except RateLimitError:
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pass
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except Exception as e:
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pytest.fail(f"Error occured: {e}")
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@pytest.mark.skip(reason="Account rate limited")
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def test_completion_clarifai_mistral_large():
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try:
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litellm.set_verbose = True
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response: ModelResponse = completion(
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model="clarifai/mistralai.completion.mistral-small",
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messages=messages,
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num_retries=3,
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max_tokens=10,
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temperature=0.78,
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)
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# Add any assertions here to check the response
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assert len(response.choices) > 0
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assert len(response.choices[0].message.content) > 0
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except RateLimitError:
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pass
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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@pytest.mark.skip(reason="Account rate limited")
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@pytest.mark.asyncio
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def test_async_completion_clarifai():
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import asyncio
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litellm.set_verbose = True
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async def test_get_response():
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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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try:
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response = await acompletion(
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model="clarifai/openai.chat-completion.GPT-4",
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messages=messages,
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num_retries=3,
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timeout=10,
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api_key=os.getenv("CLARIFAI_API_KEY"),
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)
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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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asyncio.run(test_get_response())
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