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84 lines
No EOL
2.5 KiB
Python
84 lines
No EOL
2.5 KiB
Python
#### What this tests ####
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# This tests calling batch_completions by running 100 messages together
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import sys, os
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import traceback
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import pytest
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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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from openai.error import Timeout
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import litellm
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from litellm import batch_completion, batch_completion_models, completion, batch_completion_models_all_responses
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# litellm.set_verbose=True
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# def test_batch_completions():
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# messages = [[{"role": "user", "content": "Hey, how's it going"}] for _ in range(5)]
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# model = "gpt-3.5-turbo"
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# try:
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# result = batch_completion(model=model, messages=messages)
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# print(result)
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# print(len(result))
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# except Timeout as e:
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# pass
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# except Exception as e:
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# pytest.fail(f"An error occurred: {e}")
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def test_batch_completions_models():
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try:
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result = batch_completion_models(
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models=["gpt-3.5-turbo", "gpt-3.5-turbo", "gpt-3.5-turbo"],
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messages=[{"role": "user", "content": "Hey, how's it going"}]
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)
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print(result)
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except Exception as e:
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pytest.fail(f"An error occurred: {e}")
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# test_batch_completions_models()
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def test_batch_completion_models_all_responses():
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responses = batch_completion_models_all_responses(
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models=["j2-light", "claude-instant-1.2", "command-nightly"],
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messages=[{"role": "user", "content": "write a poem"}],
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max_tokens=500
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)
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print(responses)
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assert(len(responses) == 3)
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# test_batch_completion_models_all_responses()
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# def test_batch_completions():
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# try:
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# result = completion(
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# model=["gpt-3.5-turbo", "claude-instant-1.2", "command-nightly"],
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# messages=[{"role": "user", "content": "Hey, how's it going"}]
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# )
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# print(result)
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# except Exception as e:
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# pytest.fail(f"An error occurred: {e}")
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# test_batch_completions()
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import asyncio
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##### USAGE ################
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jobs = [
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{"model": "gpt-3.5-turbo-16k", "messages": [{"content": "Please provide a summary of the latest scientific discoveries.", "role": "user"}]},
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{"model": "gpt-3.5-turbo-16k", "messages": [{"content": "Please provide a summary of the latest scientific discoveries.", "role": "user"}]},
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]
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from litellm import RateLimitManager
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handler = RateLimitManager(
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max_requests_per_minute = 60,
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max_tokens_per_minute = 20000
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)
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try:
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asyncio.run(
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handler.batch_completion(
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jobs = jobs,
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api_key=os.environ['OPENAI_API_KEY'],
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)
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)
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except Exception as e:
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print(e) |