ruff reformatted
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春河晴
@@ -17,9 +17,9 @@ with open(config_path, "r", encoding="utf-8") as f:
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config = toml.load(f)
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# 现在可以导入src模块
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from src.individuality.scene import get_scene_by_factor, PERSONALITY_SCENES #noqa E402
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from src.individuality.questionnaire import FACTOR_DESCRIPTIONS #noqa E402
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from src.individuality.offline_llm import LLM_request_off #noqa E402
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from src.individuality.scene import get_scene_by_factor, PERSONALITY_SCENES # noqa E402
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from src.individuality.questionnaire import FACTOR_DESCRIPTIONS # noqa E402
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from src.individuality.offline_llm import LLM_request_off # noqa E402
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# 加载环境变量
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env_path = os.path.join(root_path, ".env")
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@@ -32,13 +32,12 @@ else:
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def adapt_scene(scene: str) -> str:
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personality_core = config['personality']['personality_core']
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personality_sides = config['personality']['personality_sides']
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personality_core = config["personality"]["personality_core"]
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personality_sides = config["personality"]["personality_sides"]
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personality_side = random.choice(personality_sides)
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identity_details = config['identity']['identity_detail']
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identity_details = config["identity"]["identity_detail"]
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identity_detail = random.choice(identity_details)
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"""
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根据config中的属性，改编场景使其更适合当前角色
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@@ -51,10 +50,10 @@ def adapt_scene(scene: str) -> str:
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try:
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prompt = f"""
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这是一个参与人格测评的角色形象:
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- 昵称: {config['bot']['nickname']}
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- 性别: {config['identity']['gender']}
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- 年龄: {config['identity']['age']}岁
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- 外貌: {config['identity']['appearance']}
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- 昵称: {config["bot"]["nickname"]}
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- 性别: {config["identity"]["gender"]}
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- 年龄: {config["identity"]["age"]}岁
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- 外貌: {config["identity"]["appearance"]}
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- 性格核心: {personality_core}
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- 性格侧面: {personality_side}
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- 身份细节: {identity_detail}
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@@ -62,18 +61,18 @@ def adapt_scene(scene: str) -> str:
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请根据上述形象，改编以下场景，在测评中，用户将根据该场景给出上述角色形象的反应:
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{scene}
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保持场景的本质不变，但最好贴近生活且具体，并且让它更适合这个角色。
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改编后的场景应该自然、连贯，并考虑角色的年龄、身份和性格特点。只返回改编后的场景描述，不要包含其他说明。注意{config['bot']['nickname']}是面对这个场景的人，而不是场景的其他人。场景中不会有其描述，
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改编后的场景应该自然、连贯，并考虑角色的年龄、身份和性格特点。只返回改编后的场景描述，不要包含其他说明。注意{config["bot"]["nickname"]}是面对这个场景的人，而不是场景的其他人。场景中不会有其描述，
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现在，请你给出改编后的场景描述
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"""
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llm = LLM_request_off(model_name=config['model']['llm_normal']['name'])
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llm = LLM_request_off(model_name=config["model"]["llm_normal"]["name"])
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adapted_scene, _ = llm.generate_response(prompt)
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# 检查返回的场景是否为空或错误信息
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if not adapted_scene or "错误" in adapted_scene or "失败" in adapted_scene:
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print("场景改编失败，将使用原始场景")
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return scene
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return adapted_scene
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except Exception as e:
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print(f"场景改编过程出错：{str(e)}，将使用原始场景")
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@@ -169,7 +168,7 @@ class PersonalityEvaluator_direct:
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except Exception as e:
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print(f"评估过程出错：{str(e)}")
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return {dim: 3.5 for dim in dimensions}
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def run_evaluation(self):
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"""
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运行整个评估过程
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@@ -185,18 +184,23 @@ class PersonalityEvaluator_direct:
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print(f"- 身份细节：{config['identity']['identity_detail']}")
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print("\n准备好了吗？按回车键开始...")
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input()
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total_scenarios = len(self.scenarios)
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progress_bar = tqdm(total=total_scenarios, desc="场景进度", ncols=100, bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}]')
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progress_bar = tqdm(
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total=total_scenarios,
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desc="场景进度",
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ncols=100,
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bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}]",
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)
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for _i, scenario_data in enumerate(self.scenarios, 1):
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# print(f"\n{'-' * 20} 场景 {i}/{total_scenarios} - {scenario_data['场景编号']} {'-' * 20}")
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# 改编场景，使其更适合当前角色
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print(f"{config['bot']['nickname']}祈祷中...")
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adapted_scene = adapt_scene(scenario_data["场景"])
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scenario_data["改编场景"] = adapted_scene
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print(adapted_scene)
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print(f"\n请描述{config['bot']['nickname']}在这种情况下会如何反应：")
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response = input().strip()
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@@ -220,13 +224,13 @@ class PersonalityEvaluator_direct:
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# 更新进度条
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progress_bar.update(1)
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# if i < total_scenarios:
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# print("\n按回车键继续下一个场景...")
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# input()
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# print("\n按回车键继续下一个场景...")
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# input()
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progress_bar.close()
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# 计算平均分
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for dimension in self.final_scores:
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if self.dimension_counts[dimension] > 0:
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@@ -241,26 +245,26 @@ class PersonalityEvaluator_direct:
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# 返回评估结果
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return self.get_result()
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def get_result(self):
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"""
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获取评估结果
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"""
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return {
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"final_scores": self.final_scores,
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"dimension_counts": self.dimension_counts,
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"final_scores": self.final_scores,
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"dimension_counts": self.dimension_counts,
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"scenarios": self.scenarios,
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"bot_info": {
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"nickname": config['bot']['nickname'],
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"gender": config['identity']['gender'],
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"age": config['identity']['age'],
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"height": config['identity']['height'],
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"weight": config['identity']['weight'],
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"appearance": config['identity']['appearance'],
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"personality_core": config['personality']['personality_core'],
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"personality_sides": config['personality']['personality_sides'],
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"identity_detail": config['identity']['identity_detail']
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}
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"nickname": config["bot"]["nickname"],
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"gender": config["identity"]["gender"],
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"age": config["identity"]["age"],
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"height": config["identity"]["height"],
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"weight": config["identity"]["weight"],
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"appearance": config["identity"]["appearance"],
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"personality_core": config["personality"]["personality_core"],
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"personality_sides": config["personality"]["personality_sides"],
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"identity_detail": config["identity"]["identity_detail"],
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},
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}
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@@ -275,28 +279,28 @@ def main():
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"extraversion": round(result["final_scores"]["外向性"] / 6, 1),
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"agreeableness": round(result["final_scores"]["宜人性"] / 6, 1),
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"neuroticism": round(result["final_scores"]["神经质"] / 6, 1),
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"bot_nickname": config['bot']['nickname']
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"bot_nickname": config["bot"]["nickname"],
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}
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# 确保目录存在
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save_dir = os.path.join(root_path, "data", "personality")
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os.makedirs(save_dir, exist_ok=True)
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# 创建文件名，替换可能的非法字符
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bot_name = config['bot']['nickname']
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bot_name = config["bot"]["nickname"]
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# 替换Windows文件名中不允许的字符
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for char in ['\\', '/', ':', '*', '?', '"', '<', '>', '|']:
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bot_name = bot_name.replace(char, '_')
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for char in ["\\", "/", ":", "*", "?", '"', "<", ">", "|"]:
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bot_name = bot_name.replace(char, "_")
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file_name = f"{bot_name}_personality.per"
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save_path = os.path.join(save_dir, file_name)
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# 保存简化的结果
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with open(save_path, "w", encoding="utf-8") as f:
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json.dump(simplified_result, f, ensure_ascii=False, indent=4)
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print(f"\n结果已保存到 {save_path}")
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# 同时保存完整结果到results目录
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os.makedirs("results", exist_ok=True)
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with open("results/personality_result.json", "w", encoding="utf-8") as f:
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