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596 lines
25 KiB
Python
596 lines
25 KiB
Python
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"""
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Unit tests for conversation state management
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Tests the core business logic for managing conversation state,
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including history tracking, context preservation, and multi-turn
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reasoning support.
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"""
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import pytest
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from unittest.mock import Mock
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from datetime import datetime, timedelta
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import json
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class TestConversationStateLogic:
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"""Test cases for conversation state management business logic"""
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def test_conversation_initialization(self):
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"""Test initialization of new conversation state"""
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# Arrange
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class ConversationState:
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def __init__(self, conversation_id=None, user_id=None):
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self.conversation_id = conversation_id or f"conv_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
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self.user_id = user_id
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self.created_at = datetime.now()
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self.updated_at = datetime.now()
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self.turns = []
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self.context = {}
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self.metadata = {}
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self.is_active = True
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def to_dict(self):
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return {
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"conversation_id": self.conversation_id,
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"user_id": self.user_id,
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"created_at": self.created_at.isoformat(),
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"updated_at": self.updated_at.isoformat(),
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"turns": self.turns,
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"context": self.context,
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"metadata": self.metadata,
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"is_active": self.is_active
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}
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# Act
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conv1 = ConversationState(user_id="user123")
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conv2 = ConversationState(conversation_id="custom_conv_id", user_id="user456")
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# Assert
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assert conv1.conversation_id.startswith("conv_")
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assert conv1.user_id == "user123"
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assert conv1.is_active is True
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assert len(conv1.turns) == 0
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assert isinstance(conv1.created_at, datetime)
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assert conv2.conversation_id == "custom_conv_id"
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assert conv2.user_id == "user456"
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# Test serialization
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conv_dict = conv1.to_dict()
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assert "conversation_id" in conv_dict
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assert "created_at" in conv_dict
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assert isinstance(conv_dict["turns"], list)
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def test_turn_management(self):
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"""Test adding and managing conversation turns"""
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# Arrange
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class ConversationState:
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def __init__(self, conversation_id=None, user_id=None):
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self.conversation_id = conversation_id or f"conv_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
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self.user_id = user_id
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self.created_at = datetime.now()
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self.updated_at = datetime.now()
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self.turns = []
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self.context = {}
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self.metadata = {}
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self.is_active = True
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def to_dict(self):
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return {
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"conversation_id": self.conversation_id,
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"user_id": self.user_id,
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"created_at": self.created_at.isoformat(),
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"updated_at": self.updated_at.isoformat(),
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"turns": self.turns,
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"context": self.context,
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"metadata": self.metadata,
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"is_active": self.is_active
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}
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class ConversationTurn:
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def __init__(self, role, content, timestamp=None, metadata=None):
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self.role = role # "user" or "assistant"
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self.content = content
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self.timestamp = timestamp or datetime.now()
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self.metadata = metadata or {}
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def to_dict(self):
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return {
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"role": self.role,
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"content": self.content,
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"timestamp": self.timestamp.isoformat(),
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"metadata": self.metadata
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}
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class ConversationManager:
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def __init__(self):
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self.conversations = {}
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def add_turn(self, conversation_id, role, content, metadata=None):
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if conversation_id not in self.conversations:
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return False, "Conversation not found"
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turn = ConversationTurn(role, content, metadata=metadata)
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self.conversations[conversation_id].turns.append(turn)
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self.conversations[conversation_id].updated_at = datetime.now()
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return True, turn
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def get_recent_turns(self, conversation_id, limit=10):
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if conversation_id not in self.conversations:
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return []
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turns = self.conversations[conversation_id].turns
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return turns[-limit:] if len(turns) > limit else turns
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def get_turn_count(self, conversation_id):
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if conversation_id not in self.conversations:
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return 0
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return len(self.conversations[conversation_id].turns)
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# Act
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manager = ConversationManager()
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conv_id = "test_conv"
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# Create conversation - use the local ConversationState class
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conv_state = ConversationState(conv_id)
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manager.conversations[conv_id] = conv_state
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# Add turns
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success1, turn1 = manager.add_turn(conv_id, "user", "Hello, what is 2+2?")
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success2, turn2 = manager.add_turn(conv_id, "assistant", "2+2 equals 4.")
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success3, turn3 = manager.add_turn(conv_id, "user", "What about 3+3?")
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# Assert
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assert success1 is True
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assert turn1.role == "user"
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assert turn1.content == "Hello, what is 2+2?"
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assert manager.get_turn_count(conv_id) == 3
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recent_turns = manager.get_recent_turns(conv_id, limit=2)
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assert len(recent_turns) == 2
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assert recent_turns[0].role == "assistant"
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assert recent_turns[1].role == "user"
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def test_context_preservation(self):
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"""Test preservation and retrieval of conversation context"""
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# Arrange
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class ContextManager:
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def __init__(self):
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self.contexts = {}
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def set_context(self, conversation_id, key, value, ttl_minutes=None):
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"""Set context value with optional TTL"""
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if conversation_id not in self.contexts:
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self.contexts[conversation_id] = {}
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context_entry = {
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"value": value,
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"created_at": datetime.now(),
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"ttl_minutes": ttl_minutes
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}
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self.contexts[conversation_id][key] = context_entry
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def get_context(self, conversation_id, key, default=None):
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"""Get context value, respecting TTL"""
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if conversation_id not in self.contexts:
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return default
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if key not in self.contexts[conversation_id]:
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return default
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entry = self.contexts[conversation_id][key]
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# Check TTL
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if entry["ttl_minutes"]:
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age = datetime.now() - entry["created_at"]
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if age > timedelta(minutes=entry["ttl_minutes"]):
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# Expired
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del self.contexts[conversation_id][key]
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return default
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return entry["value"]
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def update_context(self, conversation_id, updates):
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"""Update multiple context values"""
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for key, value in updates.items():
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self.set_context(conversation_id, key, value)
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def clear_context(self, conversation_id, keys=None):
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"""Clear specific keys or entire context"""
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if conversation_id not in self.contexts:
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return
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if keys is None:
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# Clear all context
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self.contexts[conversation_id] = {}
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else:
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# Clear specific keys
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for key in keys:
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self.contexts[conversation_id].pop(key, None)
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def get_all_context(self, conversation_id):
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"""Get all context for conversation"""
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if conversation_id not in self.contexts:
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return {}
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# Filter out expired entries
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valid_context = {}
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for key, entry in self.contexts[conversation_id].items():
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if entry["ttl_minutes"]:
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age = datetime.now() - entry["created_at"]
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if age <= timedelta(minutes=entry["ttl_minutes"]):
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valid_context[key] = entry["value"]
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else:
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valid_context[key] = entry["value"]
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return valid_context
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# Act
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context_manager = ContextManager()
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conv_id = "test_conv"
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# Set various context values
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context_manager.set_context(conv_id, "user_name", "Alice")
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context_manager.set_context(conv_id, "topic", "mathematics")
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context_manager.set_context(conv_id, "temp_calculation", "2+2=4", ttl_minutes=1)
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# Assert
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assert context_manager.get_context(conv_id, "user_name") == "Alice"
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assert context_manager.get_context(conv_id, "topic") == "mathematics"
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assert context_manager.get_context(conv_id, "temp_calculation") == "2+2=4"
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assert context_manager.get_context(conv_id, "nonexistent", "default") == "default"
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# Test bulk updates
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context_manager.update_context(conv_id, {
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"calculation_count": 1,
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"last_operation": "addition"
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})
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all_context = context_manager.get_all_context(conv_id)
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assert "calculation_count" in all_context
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assert "last_operation" in all_context
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assert len(all_context) == 5
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# Test clearing specific keys
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context_manager.clear_context(conv_id, ["temp_calculation"])
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assert context_manager.get_context(conv_id, "temp_calculation") is None
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assert context_manager.get_context(conv_id, "user_name") == "Alice"
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def test_multi_turn_reasoning_state(self):
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"""Test state management for multi-turn reasoning"""
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# Arrange
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class ReasoningStateManager:
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def __init__(self):
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self.reasoning_states = {}
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def start_reasoning_session(self, conversation_id, question, reasoning_type="sequential"):
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"""Start a new reasoning session"""
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session_id = f"{conversation_id}_reasoning_{datetime.now().strftime('%H%M%S')}"
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self.reasoning_states[session_id] = {
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"conversation_id": conversation_id,
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"original_question": question,
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"reasoning_type": reasoning_type,
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"status": "active",
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"steps": [],
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"intermediate_results": {},
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"final_answer": None,
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"created_at": datetime.now(),
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"updated_at": datetime.now()
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}
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return session_id
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def add_reasoning_step(self, session_id, step_type, content, tool_result=None):
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"""Add a step to reasoning session"""
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if session_id not in self.reasoning_states:
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return False
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step = {
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"step_number": len(self.reasoning_states[session_id]["steps"]) + 1,
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"step_type": step_type, # "think", "act", "observe"
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"content": content,
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"tool_result": tool_result,
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"timestamp": datetime.now()
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}
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self.reasoning_states[session_id]["steps"].append(step)
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self.reasoning_states[session_id]["updated_at"] = datetime.now()
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return True
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def set_intermediate_result(self, session_id, key, value):
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"""Store intermediate result for later use"""
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if session_id not in self.reasoning_states:
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return False
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self.reasoning_states[session_id]["intermediate_results"][key] = value
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return True
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def get_intermediate_result(self, session_id, key):
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"""Retrieve intermediate result"""
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if session_id not in self.reasoning_states:
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return None
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return self.reasoning_states[session_id]["intermediate_results"].get(key)
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def complete_reasoning_session(self, session_id, final_answer):
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"""Mark reasoning session as complete"""
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if session_id not in self.reasoning_states:
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return False
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self.reasoning_states[session_id]["final_answer"] = final_answer
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self.reasoning_states[session_id]["status"] = "completed"
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self.reasoning_states[session_id]["updated_at"] = datetime.now()
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return True
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def get_reasoning_summary(self, session_id):
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"""Get summary of reasoning session"""
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if session_id not in self.reasoning_states:
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return None
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state = self.reasoning_states[session_id]
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return {
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"original_question": state["original_question"],
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"step_count": len(state["steps"]),
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"status": state["status"],
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"final_answer": state["final_answer"],
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"reasoning_chain": [step["content"] for step in state["steps"] if step["step_type"] == "think"]
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}
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# Act
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reasoning_manager = ReasoningStateManager()
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conv_id = "test_conv"
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# Start reasoning session
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session_id = reasoning_manager.start_reasoning_session(
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conv_id,
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"What is the population of the capital of France?"
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)
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# Add reasoning steps
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reasoning_manager.add_reasoning_step(session_id, "think", "I need to find the capital first")
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reasoning_manager.add_reasoning_step(session_id, "act", "search for capital of France", "Paris")
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reasoning_manager.set_intermediate_result(session_id, "capital", "Paris")
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reasoning_manager.add_reasoning_step(session_id, "observe", "Found that Paris is the capital")
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reasoning_manager.add_reasoning_step(session_id, "think", "Now I need to find Paris population")
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reasoning_manager.add_reasoning_step(session_id, "act", "search for Paris population", "2.1 million")
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reasoning_manager.complete_reasoning_session(session_id, "The population of Paris is approximately 2.1 million")
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# Assert
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assert session_id.startswith(f"{conv_id}_reasoning_")
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|
|
capital = reasoning_manager.get_intermediate_result(session_id, "capital")
|
||
|
|
assert capital == "Paris"
|
||
|
|
|
||
|
|
summary = reasoning_manager.get_reasoning_summary(session_id)
|
||
|
|
assert summary["original_question"] == "What is the population of the capital of France?"
|
||
|
|
assert summary["step_count"] == 5
|
||
|
|
assert summary["status"] == "completed"
|
||
|
|
assert "2.1 million" in summary["final_answer"]
|
||
|
|
assert len(summary["reasoning_chain"]) == 2 # Two "think" steps
|
||
|
|
|
||
|
|
def test_conversation_memory_management(self):
|
||
|
|
"""Test memory management for long conversations"""
|
||
|
|
# Arrange
|
||
|
|
class ConversationMemoryManager:
|
||
|
|
def __init__(self, max_turns=100, max_context_age_hours=24):
|
||
|
|
self.max_turns = max_turns
|
||
|
|
self.max_context_age_hours = max_context_age_hours
|
||
|
|
self.conversations = {}
|
||
|
|
|
||
|
|
def add_conversation_turn(self, conversation_id, role, content, metadata=None):
|
||
|
|
"""Add turn with automatic memory management"""
|
||
|
|
if conversation_id not in self.conversations:
|
||
|
|
self.conversations[conversation_id] = {
|
||
|
|
"turns": [],
|
||
|
|
"context": {},
|
||
|
|
"created_at": datetime.now()
|
||
|
|
}
|
||
|
|
|
||
|
|
turn = {
|
||
|
|
"role": role,
|
||
|
|
"content": content,
|
||
|
|
"timestamp": datetime.now(),
|
||
|
|
"metadata": metadata or {}
|
||
|
|
}
|
||
|
|
|
||
|
|
self.conversations[conversation_id]["turns"].append(turn)
|
||
|
|
|
||
|
|
# Apply memory management
|
||
|
|
self._manage_memory(conversation_id)
|
||
|
|
|
||
|
|
def _manage_memory(self, conversation_id):
|
||
|
|
"""Apply memory management policies"""
|
||
|
|
conv = self.conversations[conversation_id]
|
||
|
|
|
||
|
|
# Limit turn count
|
||
|
|
if len(conv["turns"]) > self.max_turns:
|
||
|
|
# Keep recent turns and important summary turns
|
||
|
|
turns_to_keep = self.max_turns // 2
|
||
|
|
important_turns = self._identify_important_turns(conv["turns"])
|
||
|
|
recent_turns = conv["turns"][-turns_to_keep:]
|
||
|
|
|
||
|
|
# Combine important and recent turns, avoiding duplicates
|
||
|
|
kept_turns = []
|
||
|
|
seen_indices = set()
|
||
|
|
|
||
|
|
# Add important turns first
|
||
|
|
for turn_index, turn in important_turns:
|
||
|
|
if turn_index not in seen_indices:
|
||
|
|
kept_turns.append(turn)
|
||
|
|
seen_indices.add(turn_index)
|
||
|
|
|
||
|
|
# Add recent turns
|
||
|
|
for i, turn in enumerate(recent_turns):
|
||
|
|
original_index = len(conv["turns"]) - len(recent_turns) + i
|
||
|
|
if original_index not in seen_indices:
|
||
|
|
kept_turns.append(turn)
|
||
|
|
|
||
|
|
conv["turns"] = kept_turns[-self.max_turns:] # Final limit
|
||
|
|
|
||
|
|
# Clean old context
|
||
|
|
self._clean_old_context(conversation_id)
|
||
|
|
|
||
|
|
def _identify_important_turns(self, turns):
|
||
|
|
"""Identify important turns to preserve"""
|
||
|
|
important = []
|
||
|
|
|
||
|
|
for i, turn in enumerate(turns):
|
||
|
|
# Keep turns with high information content
|
||
|
|
if (len(turn["content"]) > 100 or
|
||
|
|
any(keyword in turn["content"].lower() for keyword in ["calculate", "result", "answer", "conclusion"])):
|
||
|
|
important.append((i, turn))
|
||
|
|
|
||
|
|
return important[:10] # Limit important turns
|
||
|
|
|
||
|
|
def _clean_old_context(self, conversation_id):
|
||
|
|
"""Remove old context entries"""
|
||
|
|
if conversation_id not in self.conversations:
|
||
|
|
return
|
||
|
|
|
||
|
|
cutoff_time = datetime.now() - timedelta(hours=self.max_context_age_hours)
|
||
|
|
context = self.conversations[conversation_id]["context"]
|
||
|
|
|
||
|
|
keys_to_remove = []
|
||
|
|
for key, entry in context.items():
|
||
|
|
if isinstance(entry, dict) and "timestamp" in entry:
|
||
|
|
if entry["timestamp"] < cutoff_time:
|
||
|
|
keys_to_remove.append(key)
|
||
|
|
|
||
|
|
for key in keys_to_remove:
|
||
|
|
del context[key]
|
||
|
|
|
||
|
|
def get_conversation_summary(self, conversation_id):
|
||
|
|
"""Get summary of conversation state"""
|
||
|
|
if conversation_id not in self.conversations:
|
||
|
|
return None
|
||
|
|
|
||
|
|
conv = self.conversations[conversation_id]
|
||
|
|
return {
|
||
|
|
"turn_count": len(conv["turns"]),
|
||
|
|
"context_keys": list(conv["context"].keys()),
|
||
|
|
"age_hours": (datetime.now() - conv["created_at"]).total_seconds() / 3600,
|
||
|
|
"last_activity": conv["turns"][-1]["timestamp"] if conv["turns"] else None
|
||
|
|
}
|
||
|
|
|
||
|
|
# Act
|
||
|
|
memory_manager = ConversationMemoryManager(max_turns=5, max_context_age_hours=1)
|
||
|
|
conv_id = "test_memory_conv"
|
||
|
|
|
||
|
|
# Add many turns to test memory management
|
||
|
|
for i in range(10):
|
||
|
|
memory_manager.add_conversation_turn(
|
||
|
|
conv_id,
|
||
|
|
"user" if i % 2 == 0 else "assistant",
|
||
|
|
f"Turn {i}: {'Important calculation result' if i == 5 else 'Regular content'}"
|
||
|
|
)
|
||
|
|
|
||
|
|
# Assert
|
||
|
|
summary = memory_manager.get_conversation_summary(conv_id)
|
||
|
|
assert summary["turn_count"] <= 5 # Should be limited
|
||
|
|
|
||
|
|
# Check that important turns are preserved
|
||
|
|
turns = memory_manager.conversations[conv_id]["turns"]
|
||
|
|
important_preserved = any("Important calculation" in turn["content"] for turn in turns)
|
||
|
|
assert important_preserved, "Important turns should be preserved"
|
||
|
|
|
||
|
|
def test_conversation_state_persistence(self):
|
||
|
|
"""Test serialization and deserialization of conversation state"""
|
||
|
|
# Arrange
|
||
|
|
class ConversationStatePersistence:
|
||
|
|
def __init__(self):
|
||
|
|
pass
|
||
|
|
|
||
|
|
def serialize_conversation(self, conversation_state):
|
||
|
|
"""Serialize conversation state to JSON-compatible format"""
|
||
|
|
def datetime_serializer(obj):
|
||
|
|
if isinstance(obj, datetime):
|
||
|
|
return obj.isoformat()
|
||
|
|
raise TypeError(f"Object of type {type(obj)} is not JSON serializable")
|
||
|
|
|
||
|
|
return json.dumps(conversation_state, default=datetime_serializer, indent=2)
|
||
|
|
|
||
|
|
def deserialize_conversation(self, serialized_data):
|
||
|
|
"""Deserialize conversation state from JSON"""
|
||
|
|
def datetime_deserializer(data):
|
||
|
|
"""Convert ISO datetime strings back to datetime objects"""
|
||
|
|
if isinstance(data, dict):
|
||
|
|
for key, value in data.items():
|
||
|
|
if isinstance(value, str) and self._is_iso_datetime(value):
|
||
|
|
data[key] = datetime.fromisoformat(value)
|
||
|
|
elif isinstance(value, (dict, list)):
|
||
|
|
data[key] = datetime_deserializer(value)
|
||
|
|
elif isinstance(data, list):
|
||
|
|
for i, item in enumerate(data):
|
||
|
|
data[i] = datetime_deserializer(item)
|
||
|
|
|
||
|
|
return data
|
||
|
|
|
||
|
|
parsed_data = json.loads(serialized_data)
|
||
|
|
return datetime_deserializer(parsed_data)
|
||
|
|
|
||
|
|
def _is_iso_datetime(self, value):
|
||
|
|
"""Check if string is ISO datetime format"""
|
||
|
|
try:
|
||
|
|
datetime.fromisoformat(value.replace('Z', '+00:00'))
|
||
|
|
return True
|
||
|
|
except (ValueError, AttributeError):
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Create sample conversation state
|
||
|
|
conversation_state = {
|
||
|
|
"conversation_id": "test_conv_123",
|
||
|
|
"user_id": "user456",
|
||
|
|
"created_at": datetime.now(),
|
||
|
|
"updated_at": datetime.now(),
|
||
|
|
"turns": [
|
||
|
|
{
|
||
|
|
"role": "user",
|
||
|
|
"content": "Hello",
|
||
|
|
"timestamp": datetime.now(),
|
||
|
|
"metadata": {}
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"role": "assistant",
|
||
|
|
"content": "Hi there!",
|
||
|
|
"timestamp": datetime.now(),
|
||
|
|
"metadata": {"confidence": 0.9}
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"context": {
|
||
|
|
"user_preference": "detailed_answers",
|
||
|
|
"topic": "general"
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"platform": "web",
|
||
|
|
"session_start": datetime.now()
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
# Act
|
||
|
|
persistence = ConversationStatePersistence()
|
||
|
|
|
||
|
|
# Serialize
|
||
|
|
serialized = persistence.serialize_conversation(conversation_state)
|
||
|
|
assert isinstance(serialized, str)
|
||
|
|
assert "test_conv_123" in serialized
|
||
|
|
|
||
|
|
# Deserialize
|
||
|
|
deserialized = persistence.deserialize_conversation(serialized)
|
||
|
|
|
||
|
|
# Assert
|
||
|
|
assert deserialized["conversation_id"] == "test_conv_123"
|
||
|
|
assert deserialized["user_id"] == "user456"
|
||
|
|
assert isinstance(deserialized["created_at"], datetime)
|
||
|
|
assert len(deserialized["turns"]) == 2
|
||
|
|
assert deserialized["turns"][0]["role"] == "user"
|
||
|
|
assert isinstance(deserialized["turns"][0]["timestamp"], datetime)
|
||
|
|
assert deserialized["context"]["topic"] == "general"
|
||
|
|
assert deserialized["metadata"]["platform"] == "web"
|