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20704742e2
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feat: introduce async contract to BaseLLM feat: add async call support for: Azure provider Anthropic provider OpenAI provider Gemini provider Bedrock provider LiteLLM provider chore: expand scrubbed header fields (conftest, anthropic, bedrock) chore: update docs to cover async functionality chore: update and harden tests to support acall; re-add uri for cassette compatibility chore: generate missing cassette fix: ensure acall is non-abstract and set supports_tools = true for supported Anthropic models chore: improve Bedrock async docstring and general test robustness
157 lines
4.6 KiB
Python
157 lines
4.6 KiB
Python
"""Tests for LiteLLM fallback async completion functionality."""
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import pytest
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import tiktoken
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from crewai.llm import LLM
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_basic_call():
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"""Test basic async call with LiteLLM fallback."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True)
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result = await llm.acall("Say hello")
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assert result is not None
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assert isinstance(result, str)
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assert len(result) > 0
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_with_temperature():
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"""Test async call with temperature parameter."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True, temperature=0.1)
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result = await llm.acall("Say the word 'test' once")
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assert result is not None
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assert isinstance(result, str)
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_with_max_tokens():
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"""Test async call with max_tokens parameter."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True, max_tokens=10)
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result = await llm.acall("Write a very long story about a dragon.")
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assert result is not None
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assert isinstance(result, str)
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encoder = tiktoken.get_encoding("cl100k_base")
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token_count = len(encoder.encode(result))
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assert token_count <= 10
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_with_system_message():
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"""Test async call with system message."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "What is 2+2?"},
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]
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result = await llm.acall(messages)
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assert result is not None
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assert isinstance(result, str)
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_conversation():
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"""Test async call with conversation history."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True)
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messages = [
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{"role": "user", "content": "My name is Alice."},
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{"role": "assistant", "content": "Hello Alice! Nice to meet you."},
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{"role": "user", "content": "What is my name?"},
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]
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result = await llm.acall(messages)
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assert result is not None
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assert isinstance(result, str)
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_multiple_calls():
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"""Test making multiple async calls in sequence."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True)
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result1 = await llm.acall("What is 1+1?")
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result2 = await llm.acall("What is 2+2?")
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assert result1 is not None
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assert result2 is not None
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assert isinstance(result1, str)
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assert isinstance(result2, str)
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_with_parameters():
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"""Test async call with multiple parameters."""
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llm = LLM(
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model="gpt-4o-mini",
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is_litellm=True,
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temperature=0.7,
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max_tokens=100,
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top_p=0.9,
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frequency_penalty=0.5,
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presence_penalty=0.3,
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)
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result = await llm.acall("Tell me a short fact")
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assert result is not None
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assert isinstance(result, str)
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_streaming():
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"""Test async streaming call with LiteLLM fallback."""
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llm = LLM(model="gpt-4o-mini", is_litellm=True, stream=True)
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result = await llm.acall("Say hello world")
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assert result is not None
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assert isinstance(result, str)
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assert len(result) > 0
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@pytest.mark.asyncio
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@pytest.mark.vcr
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@pytest.mark.skip(reason="cassettes do not read properly but were generated correctly.")
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async def test_litellm_async_streaming_with_parameters():
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"""Test async streaming call with multiple parameters."""
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llm = LLM(
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model="gpt-4o-mini",
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is_litellm=True,
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stream=True,
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temperature=0.5,
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max_tokens=50,
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)
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result = await llm.acall("Count from 1 to 5")
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assert result is not None
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assert isinstance(result, str)
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