AI从关键词匹配,到意图演化2
静态名词系统
# 传统方式:关键词触发固定回复
class StaticChatbot:
def respond(self, message):
if "天气" in message:
return "今天天气晴朗"
elif "时间" in message:
return "现在是下午3点"
return "我不明白"
动态动词系统:
# 新方式:对话作为系统的向稳运动
class DynamicDialogSystem:
def __init__(self):
self.conversation_state = {
'user_goal': None,
'system_goal': 'provide_help',
'missing_info': [],
'certainty': 0.5
}
self.dialog_graph = self.build_dialog_graph()
def build_dialog_graph(self):
# 构建对话的状态转换图 - 动词关系网络
return {
'greeting': {'leads_to': ['state_need', 'small_talk'],
'conditions': {'time_since_start': '<10s'}},
'state_need': {'requires': ['clear_intent'],
'actions': ['ask_clarifying_questions']},
'small_talk': {'stabilizes': ['user_engagement'],
'conditions': {'relationship_depth': 'low'}}
}
def process_message(self, message, context):
# 分析输入对对话系统稳定性的影响
impact = self.analyze_impact_on_stability(message)
# 系统向稳运动:选择最能恢复对话平衡的回应
if impact['causes_instability']:
response_strategy = self.select_stabilizing_strategy(impact)
else:
response_strategy = self.select_progress_strategy()
# 更新对话状态(系统演化)
self.update_conversation_state(message, impact)
return self.generate_response(response_strategy)
def analyze_impact_on_stability(self, message):
# 分析消息如何影响对话系统的稳定性
analysis = {
'clarifies_goal': self.detect_goal_clarification(message),
'introduces_confusion': self.detect_confusion_indicators(message),
'advances_dialog': self.measure_progress_potential(message)
}
analysis['causes_instability'] = (analysis['introduces_confusion'] > 0.7)
return analysis
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