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147 lines
4.1 KiB
Python
147 lines
4.1 KiB
Python
"""Tests for Google (Gemini) async completion functionality."""
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import pytest
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import tiktoken
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from crewai import Agent, Task, Crew
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from crewai.llm import LLM
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from crewai.llms.providers.gemini.completion import GeminiCompletion
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@pytest.mark.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_basic_call():
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"""Test basic async call with Gemini."""
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llm = LLM(model="gemini/gemini-3-pro-preview")
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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.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_with_temperature():
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"""Test async call with temperature parameter."""
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llm = LLM(model="gemini/gemini-3-pro-preview", 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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async def test_gemini_async_with_max_tokens():
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"""Test async call with max_tokens parameter."""
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llm = GeminiCompletion(model="gemini-3-pro-preview", max_output_tokens=1000)
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result = await llm.acall("Write a very short 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 <= 1000
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@pytest.mark.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_with_system_message():
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"""Test async call with system message."""
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llm = LLM(model="gemini/gemini-3-pro-preview")
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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.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_conversation():
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"""Test async call with conversation history."""
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llm = LLM(model="gemini/gemini-3-pro-preview")
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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.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_multiple_calls():
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"""Test making multiple async calls in sequence."""
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llm = LLM(model="gemini/gemini-3-pro-preview")
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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.vcr()
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@pytest.mark.asyncio
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async def test_gemini_async_with_parameters():
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"""Test async call with multiple parameters."""
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llm = LLM(
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model="gemini/gemini-3-pro-preview",
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temperature=0.7,
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max_output_tokens=1000,
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top_p=0.9
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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.vcr()
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@pytest.mark.asyncio
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@pytest.mark.skip(reason="VCR cannot replay SSE streaming responses")
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async def test_google_async_streaming_returns_usage_metrics():
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"""
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Test that Google Gemini async streaming calls return proper token usage metrics.
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"""
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agent = Agent(
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role="Research Assistant",
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goal="Find information about the capital of Canada",
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backstory="You are a helpful research assistant.",
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llm=LLM(model="gemini/gemini-2.0-flash-exp", stream=True),
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verbose=True,
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)
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task = Task(
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description="What is the capital of Canada?",
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expected_output="The capital of Canada",
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agent=agent,
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)
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crew = Crew(agents=[agent], tasks=[task])
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result = await crew.kickoff_async()
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assert result.token_usage is not None
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assert result.token_usage.total_tokens > 0
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assert result.token_usage.prompt_tokens > 0
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assert result.token_usage.completion_tokens > 0
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assert result.token_usage.successful_requests >= 1
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