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crewAI/lib/crewai/tests/llms/anthropic/test_anthropic_async.py
lorenzejay 51c5973033 fix test
2026-01-22 13:52:38 -08:00

201 lines
5.7 KiB
Python

"""Tests for Anthropic async completion functionality."""
import json
import logging
import pytest
import tiktoken
from pydantic import BaseModel
from crewai.llm import LLM
from crewai.llms.providers.anthropic.completion import AnthropicCompletion
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_basic_call():
"""Test basic async call with Anthropic."""
llm = LLM(model="anthropic/claude-sonnet-4-0")
result = await llm.acall("Say hello")
assert result is not None
assert isinstance(result, str)
assert len(result) > 0
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_temperature():
"""Test async call with temperature parameter."""
llm = LLM(model="anthropic/claude-sonnet-4-0", temperature=0.1)
result = await llm.acall("Say the word 'test' once")
assert result is not None
assert isinstance(result, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_max_tokens():
"""Test async call with max_tokens parameter."""
llm = LLM(model="anthropic/claude-sonnet-4-0", max_tokens=10)
result = await llm.acall("Write a very long story about a dragon.")
assert result is not None
assert isinstance(result, str)
encoder = tiktoken.get_encoding("cl100k_base")
token_count = len(encoder.encode(result))
assert token_count <= 10
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_system_message():
"""Test async call with system message."""
llm = LLM(model="anthropic/claude-sonnet-4-0")
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is 2+2?"}
]
result = await llm.acall(messages)
assert result is not None
assert isinstance(result, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_conversation():
"""Test async call with conversation history."""
llm = LLM(model="anthropic/claude-sonnet-4-0")
messages = [
{"role": "user", "content": "My name is Alice."},
{"role": "assistant", "content": "Hello Alice! Nice to meet you."},
{"role": "user", "content": "What is my name?"}
]
result = await llm.acall(messages)
assert result is not None
assert isinstance(result, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_stop_sequences():
"""Test async call with stop sequences."""
llm = LLM(
model="anthropic/claude-sonnet-4-0",
stop_sequences=["END", "STOP"]
)
result = await llm.acall("Count from 1 to 10")
assert result is not None
assert isinstance(result, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_multiple_calls():
"""Test making multiple async calls in sequence."""
llm = LLM(model="anthropic/claude-sonnet-4-0")
result1 = await llm.acall("What is 1+1?")
result2 = await llm.acall("What is 2+2?")
assert result1 is not None
assert result2 is not None
assert isinstance(result1, str)
assert isinstance(result2, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_response_format_none():
"""Test async call with response_format set to None."""
llm = LLM(model="anthropic/claude-sonnet-4-0", response_format=None)
result = await llm.acall("Tell me a short fact")
assert result is not None
assert isinstance(result, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_response_format_json():
"""Test async call with JSON response format."""
llm = LLM(model="anthropic/claude-sonnet-4-0", response_format={"type": "json_object"})
result = await llm.acall("Return a JSON object devoid of ```json{x}```, where x is the json object, with a 'greeting' field")
assert isinstance(result, str)
deserialized_result = json.loads(result)
assert isinstance(deserialized_result, dict)
assert isinstance(deserialized_result["greeting"], str)
class GreetingResponse(BaseModel):
"""Response model for greeting test."""
greeting: str
language: str
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_response_model():
"""Test async call with Pydantic response_model for structured output."""
llm = LLM(model="anthropic/claude-sonnet-4-0")
result = await llm.acall(
"Say hello in French",
response_model=GreetingResponse
)
model = GreetingResponse.model_validate_json(result)
assert isinstance(model, GreetingResponse)
assert isinstance(model.greeting, str)
assert isinstance(model.language, str)
@pytest.mark.vcr()
@pytest.mark.asyncio
async def test_anthropic_async_with_tools():
"""Test async call with tools."""
llm = AnthropicCompletion(model="claude-sonnet-4-0")
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
}
},
"required": ["location"]
}
}
}
]
result = await llm.acall(
"What's the weather in San Francisco?",
tools=tools
)
logging.debug("result: %s", result)
assert result is not None
# Result can be either a string or a list of tool calls (native tool calling)
assert isinstance(result, (str, list))