From c5b81be7fdd525026776cf4a4a41c375c3fa6d4b Mon Sep 17 00:00:00 2001 From: 997146918 <997146918@qq.com> Date: Mon, 18 Aug 2025 09:55:18 +0800 Subject: [PATCH] =?UTF-8?q?=E8=B0=83=E6=95=B4=E5=8F=8Cai=E5=AF=B9=E8=AF=9D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- AITrain/dual_ai_dialogue_system.py | 378 ++++++++++++++--------------- AITrain/main_controller.py | 4 +- AITrain/npc_dialogue_generator.py | 162 ++++++------- 3 files changed, 272 insertions(+), 272 deletions(-) diff --git a/AITrain/dual_ai_dialogue_system.py b/AITrain/dual_ai_dialogue_system.py index 2e9e43c..ff21ee7 100644 --- a/AITrain/dual_ai_dialogue_system.py +++ b/AITrain/dual_ai_dialogue_system.py @@ -613,232 +613,232 @@ class DualAIDialogueEngine: return conversation_results -def main(): - """主函数 - 演示系统使用""" - print("=== RAG增强双AI角色对话系统 ===") +# def main(): +# """主函数 - 演示系统使用""" +# print("=== RAG增强双AI角色对话系统 ===") - # 设置路径 - knowledge_dir = "./knowledge_base" # 包含世界观和角色文档的目录 +# # 设置路径 +# knowledge_dir = "./knowledge_base" # 包含世界观和角色文档的目录 - # 检查必要文件 - required_dirs = [knowledge_dir] - for dir_path in required_dirs: - if not os.path.exists(dir_path): - print(f"✗ 目录不存在: {dir_path}") - print("请确保以下文件存在：") - print("- ./knowledge_base/worldview_template_coc.json") - print("- ./knowledge_base/character_template_detective.json") - print("- ./knowledge_base/character_template_professor.json") - return +# # 检查必要文件 +# required_dirs = [knowledge_dir] +# for dir_path in required_dirs: +# if not os.path.exists(dir_path): +# print(f"✗ 目录不存在: {dir_path}") +# print("请确保以下文件存在：") +# print("- ./knowledge_base/worldview_template_coc.json") +# print("- ./knowledge_base/character_template_detective.json") +# print("- ./knowledge_base/character_template_professor.json") +# return - try: - # 初始化系统组件 - print("\n初始化系统...") - kb = RAGKnowledgeBase(knowledge_dir) - conv_mgr = ConversationManager() +# try: +# # 初始化系统组件 +# print("\n初始化系统...") +# kb = RAGKnowledgeBase(knowledge_dir) +# conv_mgr = ConversationManager() - # 这里需要你的LLM生成器，使用新的双模型对话系统 - from npc_dialogue_generator import DualModelDialogueGenerator - base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-4B' # 根据你的路径调整 - lora_model_path = './output/NPC_Dialogue_LoRA/final_model' +# # 这里需要你的LLM生成器，使用新的双模型对话系统 +# from npc_dialogue_generator import DualModelDialogueGenerator +# base_model_path = '/mnt/g/Project02/AITrain/Qwen/Qwen3-4B' # 根据你的路径调整 +# lora_model_path = './output/NPC_Dialogue_LoRA/final_model' - if not os.path.exists(lora_model_path): - lora_model_path = None +# if not os.path.exists(lora_model_path): +# lora_model_path = None - # 创建双模型对话生成器 - if hasattr(kb, 'character_data') and len(kb.character_data) >= 2: - print("✓ 使用knowledge_base角色数据创建双模型对话系统") - # 获取前两个角色 - character_names = list(kb.character_data.keys())[:2] - char1_name = character_names[0] - char2_name = character_names[1] +# # 创建双模型对话生成器 +# if hasattr(kb, 'character_data') and len(kb.character_data) >= 2: +# print("✓ 使用knowledge_base角色数据创建双模型对话系统") +# # 获取前两个角色 +# character_names = list(kb.character_data.keys())[:2] +# char1_name = character_names[0] +# char2_name = character_names[1] - # 配置两个角色的模型 - character1_config = { - "name": char1_name, - "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA - "character_data": kb.character_data[char1_name] - } +# # 配置两个角色的模型 +# character1_config = { +# "name": char1_name, +# "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA +# "character_data": kb.character_data[char1_name] +# } - character2_config = { - "name": char2_name, - "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA - "character_data": kb.character_data[char2_name] - } +# character2_config = { +# "name": char2_name, +# "lora_path": lora_model_path, # 可以为每个角色设置不同的LoRA +# "character_data": kb.character_data[char2_name] +# } - llm_generator = DualModelDialogueGenerator( - base_model_path, - character1_config, - character2_config - ) - else: - print("⚠ 角色数据不足，无法创建双模型对话系统") - return +# llm_generator = DualModelDialogueGenerator( +# base_model_path, +# character1_config, +# character2_config +# ) +# else: +# print("⚠ 角色数据不足，无法创建双模型对话系统") +# return - # 创建对话引擎 - dialogue_engine = DualAIDialogueEngine(kb, conv_mgr, llm_generator) +# # 创建对话引擎 +# dialogue_engine = DualAIDialogueEngine(kb, conv_mgr, llm_generator) - print("✓ 系统初始化完成") +# print("✓ 系统初始化完成") - # 交互式菜单 - while True: - print("\n" + "="*50) - print("双AI角色对话系统") - print("1. 创建新对话") - print("2. 继续已有对话") - print("3. 查看对话历史") - print("4. 列出所有会话") - print("0. 退出") - print("="*50) +# # 交互式菜单 +# while True: +# print("\n" + "="*50) +# print("双AI角色对话系统") +# print("1. 创建新对话") +# print("2. 继续已有对话") +# print("3. 查看对话历史") +# print("4. 列出所有会话") +# print("0. 退出") +# print("="*50) - choice = input("请选择操作: ").strip() +# choice = input("请选择操作: ").strip() - if choice == '0': - break +# if choice == '0': +# break - elif choice == '1': - # 创建新对话 - print(f"可用角色: {list(kb.character_data.keys())}") - characters = input("请输入两个角色名称（用空格分隔）: ").strip().split() +# elif choice == '1': +# # 创建新对话 +# print(f"可用角色: {list(kb.character_data.keys())}") +# characters = input("请输入两个角色名称（用空格分隔）: ").strip().split() - if len(characters) != 2: - print("❌ 请输入正好两个角色名称") - continue +# if len(characters) != 2: +# print("❌ 请输入正好两个角色名称") +# continue - worldview = kb.worldview_data.get('worldview_name', '未知世界观') if kb.worldview_data else '未知世界观' - session_id = conv_mgr.create_session(characters, worldview) +# worldview = kb.worldview_data.get('worldview_name', '未知世界观') if kb.worldview_data else '未知世界观' +# session_id = conv_mgr.create_session(characters, worldview) - topic = input("请输入对话主题（可选）: ").strip() - turns = int(input("请输入对话轮次数量（默认2）: ").strip() or "2") +# topic = input("请输入对话主题（可选）: ").strip() +# turns = int(input("请输入对话轮次数量（默认2）: ").strip() or "2") - # 历史上下文控制选项 - print("\n历史上下文设置:") - history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip() - history_count = int(history_count) if history_count.isdigit() else 3 +# # 历史上下文控制选项 +# print("\n历史上下文设置:") +# history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip() +# history_count = int(history_count) if history_count.isdigit() else 3 - context_info_count = input("使用上下文信息数量（默认2）: ").strip() - context_info_count = int(context_info_count) if context_info_count.isdigit() else 2 +# context_info_count = input("使用上下文信息数量（默认2）: ").strip() +# context_info_count = int(context_info_count) if context_info_count.isdigit() else 2 - print(f"\n开始对话 - 会话ID: {session_id}") - print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个") +# print(f"\n开始对话 - 会话ID: {session_id}") +# print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个") - # 询问是否使用双模型对话 - use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower() - if use_dual_model != 'n': - print("使用双模型对话系统...") - dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count) - else: - print("使用传统对话系统...") - dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count) +# # 询问是否使用双模型对话 +# use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower() +# if use_dual_model != 'n': +# print("使用双模型对话系统...") +# dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count) +# else: +# print("使用传统对话系统...") +# dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count) - elif choice == '2': - # 继续已有对话 - sessions = conv_mgr.list_sessions() - if not sessions: - print("❌ 没有已有对话") - continue +# elif choice == '2': +# # 继续已有对话 +# sessions = conv_mgr.list_sessions() +# if not sessions: +# print("❌ 没有已有对话") +# continue - print("已有会话:") - for i, session in enumerate(sessions[:5]): - chars = ", ".join(session['characters']) - print(f"{i+1}. {session['session_id'][:8]}... ({chars}) - {session['last_update'][:16]}") +# print("已有会话:") +# for i, session in enumerate(sessions[:5]): +# chars = ", ".join(session['characters']) +# print(f"{i+1}. {session['session_id'][:8]}... ({chars}) - {session['last_update'][:16]}") - try: - idx = int(input("请选择会话编号: ").strip()) - 1 - if 0 <= idx < len(sessions): - session = sessions[idx] - session_id = session['session_id'] - characters = session['characters'] +# try: +# idx = int(input("请选择会话编号: ").strip()) - 1 +# if 0 <= idx < len(sessions): +# session = sessions[idx] +# session_id = session['session_id'] +# characters = session['characters'] - # 显示最近的对话 - history = conv_mgr.get_conversation_history(session_id, 4) - if history: - print("\n最近的对话:") - for turn in history: - print(f"{turn.speaker}: {turn.content}") +# # 显示最近的对话 +# history = conv_mgr.get_conversation_history(session_id, 4) +# if history: +# print("\n最近的对话:") +# for turn in history: +# print(f"{turn.speaker}: {turn.content}") - topic = input("请输入对话主题（可选）: ").strip() - turns = int(input("请输入对话轮次数量（默认1）: ").strip() or "1") +# topic = input("请输入对话主题（可选）: ").strip() +# turns = int(input("请输入对话轮次数量（默认1）: ").strip() or "1") - # 历史上下文控制选项 - print("\n历史上下文设置:") - history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip() - history_count = int(history_count) if history_count.isdigit() else 3 +# # 历史上下文控制选项 +# print("\n历史上下文设置:") +# history_count = input("使用历史对话轮数（默认3，0表示不使用）: ").strip() +# history_count = int(history_count) if history_count.isdigit() else 3 - context_info_count = input("使用上下文信息数量（默认2）: ").strip() - context_info_count = int(context_info_count) if context_info_count.isdigit() else 2 +# context_info_count = input("使用上下文信息数量（默认2）: ").strip() +# context_info_count = int(context_info_count) if context_info_count.isdigit() else 2 - print(f"\n继续对话 - 会话ID: {session_id}") - print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个") +# print(f"\n继续对话 - 会话ID: {session_id}") +# print(f"上下文设置: 历史{history_count}轮, 信息{context_info_count}个") - # 询问是否使用双模型对话 - use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower() - if use_dual_model != 'n': - print("使用双模型对话系统...") - dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count) - else: - print("使用传统对话系统...") - dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count) - else: - print("❌ 无效的会话编号") - except ValueError: - print("❌ 请输入有效的数字") +# # 询问是否使用双模型对话 +# use_dual_model = input("是否使用双模型对话系统？(y/n，默认y): ").strip().lower() +# if use_dual_model != 'n': +# print("使用双模型对话系统...") +# dialogue_engine.run_dual_model_conversation(session_id, topic, turns, history_count, context_info_count) +# else: +# print("使用传统对话系统...") +# dialogue_engine.run_conversation_turn(session_id, characters, turns, topic, history_count, context_info_count) +# else: +# print("❌ 无效的会话编号") +# except ValueError: +# print("❌ 请输入有效的数字") - elif choice == '3': - # 查看对话历史 - session_id = input("请输入会话ID（前8位即可）: ").strip() +# elif choice == '3': +# # 查看对话历史 +# session_id = input("请输入会话ID（前8位即可）: ").strip() - # 查找匹配的会话 - sessions = conv_mgr.list_sessions() - matching_session = None - for session in sessions: - if session['session_id'].startswith(session_id): - matching_session = session - break +# # 查找匹配的会话 +# sessions = conv_mgr.list_sessions() +# matching_session = None +# for session in sessions: +# if session['session_id'].startswith(session_id): +# matching_session = session +# break - if matching_session: - full_session_id = matching_session['session_id'] - history = conv_mgr.get_conversation_history(full_session_id, 20) +# if matching_session: +# full_session_id = matching_session['session_id'] +# history = conv_mgr.get_conversation_history(full_session_id, 20) - if history: - print(f"\n对话历史 - {full_session_id}") - print(f"角色: {', '.join(matching_session['characters'])}") - print(f"世界观: {matching_session['worldview']}") - print("-" * 50) +# if history: +# print(f"\n对话历史 - {full_session_id}") +# print(f"角色: {', '.join(matching_session['characters'])}") +# print(f"世界观: {matching_session['worldview']}") +# print("-" * 50) - 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") +# 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() \ No newline at end of file +# if __name__ == '__main__': +# main() \ No newline at end of file diff --git a/AITrain/main_controller.py b/AITrain/main_controller.py index e0b697b..717f6a9 100644 --- a/AITrain/main_controller.py +++ b/AITrain/main_controller.py @@ -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}") diff --git a/AITrain/npc_dialogue_generator.py b/AITrain/npc_dialogue_generator.py index fe08db9..380b1e1 100644 --- a/AITrain/npc_dialogue_generator.py +++ b/AITrain/npc_dialogue_generator.py @@ -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() \ No newline at end of file +# if __name__ == '__main__': +# main() \ No newline at end of file