diff --git a/AITrain/dual_ai_dialogue_system.py b/AITrain/dual_ai_dialogue_system.py index ff21ee7..9880112 100644 --- a/AITrain/dual_ai_dialogue_system.py +++ b/AITrain/dual_ai_dialogue_system.py @@ -593,24 +593,30 @@ class DualAIDialogueEngine: print(f"上下文设置: 历史{history_context_count}轮, 信息{context_info_count}个") # 使用双模型系统生成对话 - conversation_results = self.llm_generator.run_dual_character_conversation( - topic=topic, - turns=turns, - context=context_str, - temperature=0.8, - max_new_tokens=150 - ) - - # 保存对话到数据库 - for result in conversation_results: - self.conv_mgr.add_dialogue_turn( - session_id, - result['speaker'], - result['dialogue'], - [result.get('context_used', '')], - 0.8 # 默认相关性分数 + for turn in range(turns): + # 获取对话历史 + dialogue_history = self.conv_mgr.get_conversation_history(session_id) + conversation_results = self.llm_generator.run_dual_character_conversation( + topic=topic, + turn_index = turn, + context=context_str, + dialogue_history = dialogue_history, + history_context_count = history_context_count, + temperature=0.8, + max_new_tokens=150 ) + + # 保存对话到数据库 + for result in conversation_results: + self.conv_mgr.add_dialogue_turn( + session_id, + result['speaker'], + result['dialogue'], + [result.get('context_used', '')], + 0.8 # 默认相关性分数 + ) + return conversation_results # def main(): diff --git a/AITrain/npc_dialogue_generator.py b/AITrain/npc_dialogue_generator.py index 380b1e1..b936bf1 100644 --- a/AITrain/npc_dialogue_generator.py +++ b/AITrain/npc_dialogue_generator.py @@ -141,10 +141,11 @@ class NPCDialogueGenerator: self, character_name: str, context: str = "", - user_input: str = "", temperature: float = 0.8, max_new_tokens: int = 150, - top_p: float = 0.9 + top_p: float = 0.9, + dialogue_history: List[Dict] = None, + history_context_count: int = 3 ) -> str: """ 生成指定角色的对话 @@ -156,6 +157,8 @@ class NPCDialogueGenerator: temperature: 采样温度 max_new_tokens: 最大生成token数 top_p: 核采样参数 + dialogue_history: 对话历史记录列表，每个元素包含speaker和content + history_context_count: 使用的历史对话轮数（默认3轮） Returns: 生成的对话内容 @@ -165,12 +168,12 @@ class NPCDialogueGenerator: profile = self.character_profiles[character_name] - # 构建系统提示 - system_prompt = self._build_system_prompt(profile, context) + # 构建系统提示，包含历史对话数据 + system_prompt = self._build_system_prompt(profile, context, dialogue_history, history_context_count) # 构建用户输入 - if not user_input: - user_input = "请说一段符合你角色设定的话。" + user_input = "请说一段符合你角色设定的话。" + # 准备消息 messages = [ @@ -209,8 +212,15 @@ class NPCDialogueGenerator: return dialogue - def _build_system_prompt(self, profile: Dict, context: str = "") -> str: - """构建系统提示""" + def _build_system_prompt(self, profile: Dict, context: str = "", dialogue_history: List[Dict] = None, history_context_count: int = 3) -> str: + """构建系统提示 + + Args: + profile: 角色配置信息 + context: 当前情境 + dialogue_history: 对话历史记录列表，每个元素包含speaker和content + history_context_count: 使用的历史对话轮数（默认3轮） + """ personality_str = "、".join(profile["personality"]) speech_pattern_str = "；".join(profile["speech_patterns"]) @@ -219,9 +229,24 @@ class NPCDialogueGenerator: 性格特点：{personality_str} 说话风格：{speech_pattern_str} 请严格按照这个角色的设定来回应，保持角色的一致性和独特性。""" + + # 添加当前情境 if context: system_prompt += f"\n\n当前情境：{context}" - return system_prompt + + # 添加历史对话数据（参考generate_character_prompt的实现） + if dialogue_history: + system_prompt += "\n\n最近的对话：" + # 使用参数控制历史对话轮数 + history_to_use = dialogue_history[-history_context_count:] if history_context_count > 0 else [] + for turn in history_to_use: + system_prompt += f"{turn.speaker}: {turn.content}" + # speaker = turn.get('speaker', '未知') + # content = turn.get('content', '') + # if content: + # system_prompt += f"\n{speaker}: {content}" + + return system_prompt def generate_dialogue_conversation(self, character1: str, character2: str, topic: str, turns: int = 4) -> List[Dict]: """生成两个角色之间的对话 @@ -327,9 +352,10 @@ class DualModelDialogueGenerator: def generate_dual_character_dialogue(self, character_name: str, context: str = "", - user_input: str = "", temperature: float = 0.8, - max_new_tokens: int = 150) -> str: + max_new_tokens: int = 150, + dialogue_history: str = "", + history_context_count: int = 3) -> str: """ 生成指定角色的对话（使用对应的模型） @@ -345,19 +371,21 @@ class DualModelDialogueGenerator: """ if character_name == self.character1_config['name']: return self.character1_generator.generate_character_dialogue( - character_name, context, user_input, temperature, max_new_tokens + character_name, context, temperature, max_new_tokens, dialogue_history = dialogue_history, history_context_count=history_context_count, ) elif character_name == self.character2_config['name']: return self.character2_generator.generate_character_dialogue( - character_name, context, user_input, temperature, max_new_tokens + character_name, context, temperature, max_new_tokens, dialogue_history = dialogue_history, history_context_count=history_context_count, ) else: raise ValueError(f"Unknown character: {character_name}") def run_dual_character_conversation(self, topic: str = "", - turns: int = 4, + turn_index: int = 4, context: str = "", + dialogue_history: str = "", + history_context_count: int = 3, temperature: float = 0.8, max_new_tokens: int = 150) -> List[Dict]: """ @@ -380,45 +408,43 @@ class DualModelDialogueGenerator: # 构建完整上下文 full_context = f"现在{char1_name}和{char2_name}在讨论关于{topic}的话题。{context}" - print(f"\n=== 开始双角色对话 ===") - print(f"主题: {topic}") - print(f"角色: {char1_name} vs {char2_name}") - print(f"轮数: {turns}") - print("-" * 50) + # print(f"\n=== 开始双角色对话 ===") + # print(f"主题: {topic}") + # print(f"角色: {char1_name} vs {char2_name}") + # print("-" * 50) - for turn in range(turns): - if turn % 2 == 0: - # 角色1说话 - speaker = char1_name - if turn == 0: - user_input = f"开始和{char2_name}讨论{topic}这个话题。" - else: - last_dialogue = conversation[-1]["dialogue"] - user_input = f"{char2_name}刚才说：\"{last_dialogue}\"。请回应。" - else: - # 角色2说话 - speaker = char2_name - last_dialogue = conversation[-1]["dialogue"] - user_input = f"{char1_name}刚才说：\"{last_dialogue}\"。请回应。" - - print(f"\n[第{turn+1}轮] {speaker}正在思考...") - - # 使用对应角色的模型生成对话 - dialogue = self.generate_dual_character_dialogue( - speaker, full_context, user_input, temperature, max_new_tokens - ) - - conversation.append({ - "turn": turn + 1, - "speaker": speaker, - "dialogue": dialogue, - "context_used": full_context[:100] + "..." if len(full_context) > 100 else full_context - }) - - print(f"{speaker}: {dialogue}") + + if turn_index % 2 == 0: + # 角色1说话 + speaker = char1_name + # if turn_index == 0: + # user_input = f"开始和{char2_name}讨论{topic}这个话题。" + # else: + # last_dialogue = conversation[-1]["dialogue"] + # user_input = f"{char2_name}刚才说：\"{last_dialogue}\"。请回应。" + else: + # 角色2说话 + speaker = char2_name + # last_dialogue = conversation[-1]["dialogue"] + # user_input = f"{char1_name}刚才说：\"{last_dialogue}\"。请回应。" - print("-" * 50) - print("✓ 双角色对话完成") + print(f"\n[第{turn_index+1}轮] {speaker}正在思考...") + + # 使用对应角色的模型生成对话 + dialogue = self.generate_dual_character_dialogue( + speaker, full_context, temperature, max_new_tokens, dialogue_history, history_context_count + ) + + conversation.append({ + "turn": turn_index + 1, + "speaker": speaker, + "dialogue": dialogue, + "context_used": full_context[:100] + "..." if len(full_context) > 100 else full_context + }) + + print(f"{speaker}: {dialogue}") + + return conversation