调整双ai对话
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@ -613,232 +613,232 @@ class DualAIDialogueEngine:
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return conversation_results
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def main():
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"""主函数 - 演示系统使用"""
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print("=== RAG增强双AI角色对话系统 ===")
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# def main():
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# """主函数 - 演示系统使用"""
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# print("=== RAG增强双AI角色对话系统 ===")
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# 设置路径
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knowledge_dir = "./knowledge_base" # 包含世界观和角色文档的目录
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# # 设置路径
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# knowledge_dir = "./knowledge_base" # 包含世界观和角色文档的目录
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# 检查必要文件
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required_dirs = [knowledge_dir]
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for dir_path in required_dirs:
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if not os.path.exists(dir_path):
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print(f"✗ 目录不存在: {dir_path}")
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print("请确保以下文件存在：")
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print("- ./knowledge_base/worldview_template_coc.json")
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print("- ./knowledge_base/character_template_detective.json")
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print("- ./knowledge_base/character_template_professor.json")
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return
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# # 检查必要文件
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# required_dirs = [knowledge_dir]
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# for dir_path in required_dirs:
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# if not os.path.exists(dir_path):
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# print(f"✗ 目录不存在: {dir_path}")
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# print("请确保以下文件存在：")
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# print("- ./knowledge_base/worldview_template_coc.json")
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# print("- ./knowledge_base/character_template_detective.json")
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# print("- ./knowledge_base/character_template_professor.json")
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# return
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try:
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# 初始化系统组件
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print("\n初始化系统...")
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kb = RAGKnowledgeBase(knowledge_dir)
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conv_mgr = ConversationManager()
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# try:
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# # 初始化系统组件
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# print("\n初始化系统...")
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# kb = RAGKnowledgeBase(knowledge_dir)
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# conv_mgr = ConversationManager()
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# 这里需要你的LLM生成器，使用新的双模型对话系统
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from npc_dialogue_generator import DualModelDialogueGenerator
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base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-4B' # 根据你的路径调整
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lora_model_path = './output/NPC_Dialogue_LoRA/final_model'
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# # 这里需要你的LLM生成器，使用新的双模型对话系统
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# from npc_dialogue_generator import DualModelDialogueGenerator
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# base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-4B' # 根据你的路径调整
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# lora_model_path = './output/NPC_Dialogue_LoRA/final_model'
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if not os.path.exists(lora_model_path):
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lora_model_path = None
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# if not os.path.exists(lora_model_path):
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# lora_model_path = None
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# 创建双模型对话生成器
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if hasattr(kb, 'character_data') and len(kb.character_data) >= 2:
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print("✓ 使用knowledge_base角色数据创建双模型对话系统")
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# 获取前两个角色
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character_names = list(kb.character_data.keys())[:2]
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char1_name = character_names[0]
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char2_name = character_names[1]
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# # 创建双模型对话生成器
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# if hasattr(kb, 'character_data') and len(kb.character_data) >= 2:
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# print("✓ 使用knowledge_base角色数据创建双模型对话系统")
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# # 获取前两个角色
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# character_names = list(kb.character_data.keys())[:2]
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# char1_name = character_names[0]
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# char2_name = character_names[1]
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# 配置两个角色的模型
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character1_config = {
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"name": char1_name,
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"lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA
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"character_data": kb.character_data[char1_name]
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}
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# # 配置两个角色的模型
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# character1_config = {
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# "name": char1_name,
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# "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA
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# "character_data": kb.character_data[char1_name]
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# }
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character2_config = {
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"name": char2_name,
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"lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA
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"character_data": kb.character_data[char2_name]
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}
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# character2_config = {
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# "name": char2_name,
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# "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA
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# "character_data": kb.character_data[char2_name]
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# }
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llm_generator = DualModelDialogueGenerator(
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base_model_path,
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character1_config,
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character2_config
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)
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else:
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print("⚠ 角色数据不足，无法创建双模型对话系统")
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return
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# llm_generator = DualModelDialogueGenerator(
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# base_model_path,
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# character1_config,
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# character2_config
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# )
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# else:
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# print("⚠ 角色数据不足，无法创建双模型对话系统")
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# return
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# 创建对话引擎
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dialogue_engine = DualAIDialogueEngine(kb, conv_mgr, llm_generator)
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# # 创建对话引擎
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# dialogue_engine = DualAIDialogueEngine(kb, conv_mgr, llm_generator)
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print("✓ 系统初始化完成")
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# print("✓ 系统初始化完成")
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# 交互式菜单
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while True:
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print("\n" + "="*50)
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print("双AI角色对话系统")
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print("1. 创建新对话")
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print("2. 继续已有对话")
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print("3. 查看对话历史")
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print("4. 列出所有会话")
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print("0. 退出")
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print("="*50)
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# # 交互式菜单
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# while True:
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# print("\n" + "="*50)
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# print("双AI角色对话系统")
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# print("1. 创建新对话")
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# print("2. 继续已有对话")
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# print("3. 查看对话历史")
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# print("4. 列出所有会话")
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# print("0. 退出")
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# print("="*50)
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choice = input("请选择操作: ").strip()
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# choice = input("请选择操作: ").strip()
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if choice == '0':
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break
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# if choice == '0':
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# break
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elif choice == '1':
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# 创建新对话
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print(f"可用角色: {list(kb.character_data.keys())}")
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characters = input("请输入两个角色名称（用空格分隔）: ").strip().split()
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# elif choice == '1':
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# # 创建新对话
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# print(f"可用角色: {list(kb.character_data.keys())}")
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# characters = input("请输入两个角色名称（用空格分隔）: ").strip().split()
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if len(characters) != 2:
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print("❌ 请输入正好两个角色名称")
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continue
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# if len(characters) != 2:
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# print("❌ 请输入正好两个角色名称")
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# continue
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worldview = kb.worldview_data.get('worldview_name', '未知世界观') if kb.worldview_data else '未知世界观'
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session_id = conv_mgr.create_session(characters, worldview)
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# worldview = kb.worldview_data.get('worldview_name', '未知世界观') if kb.worldview_data else '未知世界观'
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# session_id = conv_mgr.create_session(characters, worldview)
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topic = input("请输入对话主题（可选）: ").strip()
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turns = int(input("请输入对话轮次数量（默认2）: ").strip() or "2")
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# topic = input("请输入对话主题（可选）: ").strip()
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# turns = int(input("请输入对话轮次数量（默认2）: ").strip() or "2")
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# 历史上下文控制选项
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print("\n历史上下文设置:")
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history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip()
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history_count = int(history_count) if history_count.isdigit() else 3
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# # 历史上下文控制选项
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# print("\n历史上下文设置:")
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# history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip()
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# history_count = int(history_count) if history_count.isdigit() else 3
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context_info_count = input("使用上下文信息数量（默认2）: ").strip()
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context_info_count = int(context_info_count) if context_info_count.isdigit() else 2
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# context_info_count = input("使用上下文信息数量（默认2）: ").strip()
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# context_info_count = int(context_info_count) if context_info_count.isdigit() else 2
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print(f"\n开始对话 - 会话ID: {session_id}")
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print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个")
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# print(f"\n开始对话 - 会话ID: {session_id}")
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# print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个")
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# 询问是否使用双模型对话
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use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower()
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if use_dual_model != 'n':
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print("使用双模型对话系统...")
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dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count)
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else:
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print("使用传统对话系统...")
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dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count)
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# # 询问是否使用双模型对话
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# use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower()
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# if use_dual_model != 'n':
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# print("使用双模型对话系统...")
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# dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count)
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# else:
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# print("使用传统对话系统...")
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# dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count)
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elif choice == '2':
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# 继续已有对话
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sessions = conv_mgr.list_sessions()
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if not sessions:
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print("❌ 没有已有对话")
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continue
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# elif choice == '2':
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# # 继续已有对话
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# sessions = conv_mgr.list_sessions()
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# if not sessions:
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# print("❌ 没有已有对话")
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# continue
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print("已有会话:")
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for i, session in enumerate(sessions[:5]):
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chars = ", ".join(session['characters'])
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print(f"{i+1}. {session['session_id'][:8]}... ({chars}) - {session['last_update'][:16]}")
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# print("已有会话:")
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# for i, session in enumerate(sessions[:5]):
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# chars = ", ".join(session['characters'])
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# print(f"{i+1}. {session['session_id'][:8]}... ({chars}) - {session['last_update'][:16]}")
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try:
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idx = int(input("请选择会话编号: ").strip()) - 1
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if 0 <= idx < len(sessions):
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session = sessions[idx]
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session_id = session['session_id']
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characters = session['characters']
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# try:
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# idx = int(input("请选择会话编号: ").strip()) - 1
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# if 0 <= idx < len(sessions):
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# session = sessions[idx]
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# session_id = session['session_id']
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# characters = session['characters']
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# 显示最近的对话
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history = conv_mgr.get_conversation_history(session_id, 4)
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if history:
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print("\n最近的对话:")
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for turn in history:
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print(f"{turn.speaker}: {turn.content}")
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# # 显示最近的对话
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# history = conv_mgr.get_conversation_history(session_id, 4)
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# if history:
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# print("\n最近的对话:")
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# for turn in history:
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# print(f"{turn.speaker}: {turn.content}")
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topic = input("请输入对话主题（可选）: ").strip()
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turns = int(input("请输入对话轮次数量（默认1）: ").strip() or "1")
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# topic = input("请输入对话主题（可选）: ").strip()
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# turns = int(input("请输入对话轮次数量（默认1）: ").strip() or "1")
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# 历史上下文控制选项
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print("\n历史上下文设置:")
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history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip()
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history_count = int(history_count) if history_count.isdigit() else 3
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# # 历史上下文控制选项
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# print("\n历史上下文设置:")
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# history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip()
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# history_count = int(history_count) if history_count.isdigit() else 3
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context_info_count = input("使用上下文信息数量（默认2）: ").strip()
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context_info_count = int(context_info_count) if context_info_count.isdigit() else 2
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# context_info_count = input("使用上下文信息数量（默认2）: ").strip()
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# context_info_count = int(context_info_count) if context_info_count.isdigit() else 2
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print(f"\n继续对话 - 会话ID: {session_id}")
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print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个")
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# print(f"\n继续对话 - 会话ID: {session_id}")
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# print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个")
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# 询问是否使用双模型对话
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use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower()
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if use_dual_model != 'n':
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print("使用双模型对话系统...")
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dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count)
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else:
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print("使用传统对话系统...")
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dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count)
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else:
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print("❌ 无效的会话编号")
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except ValueError:
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print("❌ 请输入有效的数字")
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# # 询问是否使用双模型对话
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# use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower()
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# if use_dual_model != 'n':
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# print("使用双模型对话系统...")
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# dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count)
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# else:
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# print("使用传统对话系统...")
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# dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count)
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# else:
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# print("❌ 无效的会话编号")
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# except ValueError:
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# print("❌ 请输入有效的数字")
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elif choice == '3':
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# 查看对话历史
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session_id = input("请输入会话ID（前8位即可）: ").strip()
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# elif choice == '3':
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# # 查看对话历史
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# session_id = input("请输入会话ID（前8位即可）: ").strip()
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# 查找匹配的会话
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sessions = conv_mgr.list_sessions()
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matching_session = None
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for session in sessions:
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if session['session_id'].startswith(session_id):
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matching_session = session
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break
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# # 查找匹配的会话
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# sessions = conv_mgr.list_sessions()
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# matching_session = None
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# for session in sessions:
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# if session['session_id'].startswith(session_id):
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# matching_session = session
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# break
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if matching_session:
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full_session_id = matching_session['session_id']
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history = conv_mgr.get_conversation_history(full_session_id, 20)
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# if matching_session:
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# full_session_id = matching_session['session_id']
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# history = conv_mgr.get_conversation_history(full_session_id, 20)
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if history:
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print(f"\n对话历史 - {full_session_id}")
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print(f"角色: {', '.join(matching_session['characters'])}")
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print(f"世界观: {matching_session['worldview']}")
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print("-" * 50)
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# if history:
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# print(f"\n对话历史 - {full_session_id}")
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# print(f"角色: {', '.join(matching_session['characters'])}")
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# print(f"世界观: {matching_session['worldview']}")
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# print("-" * 50)
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for turn in history:
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print(f"[{turn.timestamp[:16]}] {turn.speaker}:")
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print(f" {turn.content}")
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if turn.context_used:
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print(f" 使用上下文: {', '.join(turn.context_used)}")
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print()
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else:
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print("该会话暂无对话历史")
|
||||
else:
|
||||
print("❌ 未找到匹配的会话")
|
||||
# for turn in history:
|
||||
# print(f"[{turn.timestamp[:16]}] {turn.speaker}:")
|
||||
# print(f" {turn.content}")
|
||||
# if turn.context_used:
|
||||
# print(f" 使用上下文: {', '.join(turn.context_used)}")
|
||||
# print()
|
||||
# else:
|
||||
# print("该会话暂无对话历史")
|
||||
# else:
|
||||
# print("❌ 未找到匹配的会话")
|
||||
|
||||
elif choice == '4':
|
||||
# 列出所有会话
|
||||
sessions = conv_mgr.list_sessions()
|
||||
if sessions:
|
||||
print(f"\n共有 {len(sessions)} 个对话会话:")
|
||||
for session in sessions:
|
||||
chars = ", ".join(session['characters'])
|
||||
print(f"ID: {session['session_id']}")
|
||||
print(f" 角色: {chars}")
|
||||
print(f" 世界观: {session['worldview']}")
|
||||
print(f" 最后更新: {session['last_update']}")
|
||||
print()
|
||||
else:
|
||||
print("暂无对话会话")
|
||||
# elif choice == '4':
|
||||
# # 列出所有会话
|
||||
# sessions = conv_mgr.list_sessions()
|
||||
# if sessions:
|
||||
# print(f"\n共有 {len(sessions)} 个对话会话:")
|
||||
# for session in sessions:
|
||||
# chars = ", ".join(session['characters'])
|
||||
# print(f"ID: {session['session_id']}")
|
||||
# print(f" 角色: {chars}")
|
||||
# print(f" 世界观: {session['worldview']}")
|
||||
# print(f" 最后更新: {session['last_update']}")
|
||||
# print()
|
||||
# else:
|
||||
# print("暂无对话会话")
|
||||
|
||||
else:
|
||||
print("❌ 无效选择")
|
||||
# else:
|
||||
# print("❌ 无效选择")
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ 系统运行出错: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
# except Exception as e:
|
||||
# print(f"✗ 系统运行出错: {e}")
|
||||
# import traceback
|
||||
# traceback.print_exc()
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
# if __name__ == '__main__':
|
||||
# main()
|
||||
@ -224,8 +224,8 @@ def run_dialogue_system():
|
||||
history_input = input("使用历史对话轮数 (默认3): ").strip()
|
||||
history_count = int(history_input) if history_input.isdigit() else 3
|
||||
|
||||
context_input = input("使用上下文信息数量 (默认2): ").strip()
|
||||
context_info_count = int(context_input) if context_input.isdigit() else 2
|
||||
context_input = input("使用上下文信息数量 (默认10): ").strip()
|
||||
context_info_count = int(context_input) if context_input.isdigit() else 10
|
||||
|
||||
print(f"\n开始对话 - 主题: {user_input}")
|
||||
print(f"轮数: {turns}, 历史: {history_count}, 上下文: {context_info_count}")
|
||||
|
||||
@ -435,101 +435,101 @@ class DualModelDialogueGenerator:
|
||||
"""列出两个角色名称"""
|
||||
return [self.character1_config['name'], self.character2_config['name']]
|
||||
|
||||
def main():
|
||||
"""测试对话生成器"""
|
||||
# 配置路径
|
||||
base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-8B-AWQ'
|
||||
lora_model_path = './output/NPC_Dialogue_LoRA/final_model' # 如果没有训练LoRA，设为None
|
||||
# def main():
|
||||
# """测试对话生成器"""
|
||||
# # 配置路径
|
||||
# base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-8B-AWQ'
|
||||
# lora_model_path = './output/NPC_Dialogue_LoRA/final_model' # 如果没有训练LoRA，设为None
|
||||
|
||||
# 检查LoRA模型是否存在
|
||||
if not os.path.exists(lora_model_path):
|
||||
print("LoRA模型不存在，使用基础模型")
|
||||
lora_model_path = None
|
||||
# # 检查LoRA模型是否存在
|
||||
# if not os.path.exists(lora_model_path):
|
||||
# print("LoRA模型不存在，使用基础模型")
|
||||
# lora_model_path = None
|
||||
|
||||
# 创建对话生成器
|
||||
generator = NPCDialogueGenerator(base_model_path, lora_model_path)
|
||||
# # 创建对话生成器
|
||||
# generator = NPCDialogueGenerator(base_model_path, lora_model_path)
|
||||
|
||||
print("=== 游戏NPC角色对话生成器 ===")
|
||||
print(f"可用角色：{', '.join(generator.list_available_characters())}")
|
||||
# print("=== 游戏NPC角色对话生成器 ===")
|
||||
# print(f"可用角色：{', '.join(generator.list_available_characters())}")
|
||||
|
||||
# 测试单个角色对话生成
|
||||
print("\n=== 单角色对话测试 ===")
|
||||
test_scenarios = [
|
||||
{
|
||||
"character": "克莱恩",
|
||||
"context": "玩家向你咨询神秘学知识",
|
||||
"input": "请告诉我一些关于灵界的注意事项。"
|
||||
},
|
||||
{
|
||||
"character": "阿兹克",
|
||||
"context": "学生遇到了修炼瓶颈",
|
||||
"input": "导师，我在修炼中遇到了困难。"
|
||||
},
|
||||
{
|
||||
"character": "塔利姆",
|
||||
"context": "在俱乐部偶遇老朋友",
|
||||
"input": "好久不见，最近怎么样？"
|
||||
}
|
||||
]
|
||||
# # 测试单个角色对话生成
|
||||
# print("\n=== 单角色对话测试 ===")
|
||||
# test_scenarios = [
|
||||
# {
|
||||
# "character": "克莱恩",
|
||||
# "context": "玩家向你咨询神秘学知识",
|
||||
# "input": "请告诉我一些关于灵界的注意事项。"
|
||||
# },
|
||||
# {
|
||||
# "character": "阿兹克",
|
||||
# "context": "学生遇到了修炼瓶颈",
|
||||
# "input": "导师，我在修炼中遇到了困难。"
|
||||
# },
|
||||
# {
|
||||
# "character": "塔利姆",
|
||||
# "context": "在俱乐部偶遇老朋友",
|
||||
# "input": "好久不见，最近怎么样？"
|
||||
# }
|
||||
# ]
|
||||
|
||||
for scenario in test_scenarios:
|
||||
print(f"\n--- {scenario['character']} ---")
|
||||
print(f"情境：{scenario['context']}")
|
||||
print(f"输入：{scenario['input']}")
|
||||
# for scenario in test_scenarios:
|
||||
# print(f"\n--- {scenario['character']} ---")
|
||||
# print(f"情境：{scenario['context']}")
|
||||
# print(f"输入：{scenario['input']}")
|
||||
|
||||
dialogue = generator.generate_character_dialogue(
|
||||
scenario["character"],
|
||||
scenario["context"],
|
||||
scenario["input"]
|
||||
)
|
||||
print(f"回复：{dialogue}")
|
||||
# dialogue = generator.generate_character_dialogue(
|
||||
# scenario["character"],
|
||||
# scenario["context"],
|
||||
# scenario["input"]
|
||||
# )
|
||||
# print(f"回复：{dialogue}")
|
||||
|
||||
# 测试角色间对话
|
||||
print("\n=== 角色间对话测试 ===")
|
||||
conversation = generator.generate_dialogue_conversation(
|
||||
"克莱恩", "塔利姆", "最近遇到的神秘事件", turns=4
|
||||
)
|
||||
# # 测试角色间对话
|
||||
# print("\n=== 角色间对话测试 ===")
|
||||
# conversation = generator.generate_dialogue_conversation(
|
||||
# "克莱恩", "塔利姆", "最近遇到的神秘事件", turns=4
|
||||
# )
|
||||
|
||||
for turn in conversation:
|
||||
print(f"{turn['speaker']}：{turn['dialogue']}")
|
||||
# for turn in conversation:
|
||||
# print(f"{turn['speaker']}：{turn['dialogue']}")
|
||||
|
||||
# 交互式对话模式
|
||||
print("\n=== 交互式对话模式 ===")
|
||||
print("输入格式：角色名 上下文 用户输入")
|
||||
print("例如：克莱恩 在俱乐部 请给我一些建议")
|
||||
print("输入'quit'退出")
|
||||
# # 交互式对话模式
|
||||
# print("\n=== 交互式对话模式 ===")
|
||||
# print("输入格式：角色名 上下文 用户输入")
|
||||
# print("例如：克莱恩 在俱乐部 请给我一些建议")
|
||||
# print("输入'quit'退出")
|
||||
|
||||
while True:
|
||||
try:
|
||||
user_command = input("\n请输入指令: ").strip()
|
||||
if user_command.lower() == 'quit':
|
||||
break
|
||||
# while True:
|
||||
# try:
|
||||
# user_command = input("\n请输入指令: ").strip()
|
||||
# if user_command.lower() == 'quit':
|
||||
# break
|
||||
|
||||
parts = user_command.split(' ', 2)
|
||||
if len(parts) < 2:
|
||||
print("格式错误，请使用：角色名 上下文 [用户输入]")
|
||||
continue
|
||||
# parts = user_command.split(' ', 2)
|
||||
# if len(parts) < 2:
|
||||
# print("格式错误，请使用：角色名 上下文 [用户输入]")
|
||||
# continue
|
||||
|
||||
character = parts[0]
|
||||
context = parts[1]
|
||||
user_input = parts[2] if len(parts) > 2 else ""
|
||||
# character = parts[0]
|
||||
# context = parts[1]
|
||||
# user_input = parts[2] if len(parts) > 2 else ""
|
||||
|
||||
if character not in generator.list_available_characters():
|
||||
print(f"未知角色：{character}")
|
||||
print(f"可用角色：{', '.join(generator.list_available_characters())}")
|
||||
continue
|
||||
# if character not in generator.list_available_characters():
|
||||
# print(f"未知角色：{character}")
|
||||
# print(f"可用角色：{', '.join(generator.list_available_characters())}")
|
||||
# continue
|
||||
|
||||
dialogue = generator.generate_character_dialogue(
|
||||
character, context, user_input
|
||||
)
|
||||
print(f"\n{character}：{dialogue}")
|
||||
# dialogue = generator.generate_character_dialogue(
|
||||
# character, context, user_input
|
||||
# )
|
||||
# print(f"\n{character}：{dialogue}")
|
||||
|
||||
except KeyboardInterrupt:
|
||||
break
|
||||
except Exception as e:
|
||||
print(f"生成对话时出错：{e}")
|
||||
# except KeyboardInterrupt:
|
||||
# break
|
||||
# except Exception as e:
|
||||
# print(f"生成对话时出错：{e}")
|
||||
|
||||
print("\n对话生成器已退出")
|
||||
# print("\n对话生成器已退出")
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
# if __name__ == '__main__':
|
||||
# main()
|
||||
Loading…
x
Reference in New Issue
Block a user