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53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
import pytest
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import numpy as np
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from unittest.mock import patch, MagicMock
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from crewai.memory.short_term.short_term_memory import ShortTermMemory
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from crewai.agent import Agent
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from crewai.crew import Crew
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from crewai.task import Task
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from crewai.utilities.constants import MEMORY_CHUNK_SIZE
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@pytest.fixture
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def short_term_memory():
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"""Fixture to create a ShortTermMemory instance"""
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agent = Agent(
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role="Researcher",
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goal="Search relevant data and provide results",
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backstory="You are a researcher at a leading tech think tank.",
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tools=[],
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verbose=True,
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)
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task = Task(
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description="Perform a search on specific topics.",
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expected_output="A list of relevant URLs based on the search query.",
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agent=agent,
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)
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return ShortTermMemory(crew=Crew(agents=[agent], tasks=[task]))
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def test_memory_with_large_input(short_term_memory):
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"""Test that memory can handle large inputs without token limit errors"""
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large_input = "test value " * (MEMORY_CHUNK_SIZE + 1000)
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with patch.object(
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short_term_memory.storage, '_chunk_text',
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return_value=["chunk1", "chunk2"]
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) as mock_chunk_text:
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with patch.object(
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short_term_memory.storage.collection, 'add'
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) as mock_add:
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short_term_memory.save(value=large_input, agent="test_agent")
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assert mock_chunk_text.called
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with patch.object(
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short_term_memory.storage, 'search',
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return_value=[{"context": large_input, "metadata": {"agent": "test_agent"}, "score": 0.95}]
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):
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result = short_term_memory.search(large_input[:100], score_threshold=0.01)
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assert result[0]["context"] == large_input
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assert result[0]["metadata"]["agent"] == "test_agent"
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