feat：新的人格结构，完成20%
This commit is contained in:
SengokuCola
95
src/individuality/identity.py
Normal file
95
src/individuality/identity.py
Normal file
@@ -0,0 +1,95 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import List
|
||||
|
||||
@dataclass
|
||||
class Identity:
|
||||
"""身份特征类"""
|
||||
identity_detail: List[str] # 身份细节描述
|
||||
height: int # 身高（厘米）
|
||||
weight: int # 体重（千克）
|
||||
age: int # 年龄
|
||||
gender: str # 性别
|
||||
appearance: str # 外貌特征
|
||||
|
||||
_instance = None
|
||||
|
||||
def __new__(cls, *args, **kwargs):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
return cls._instance
|
||||
|
||||
def __init__(self, identity_detail: List[str] = None, height: int = 0, weight: int = 0,
|
||||
age: int = 0, gender: str = "", appearance: str = ""):
|
||||
"""初始化身份特征
|
||||
|
||||
Args:
|
||||
identity_detail: 身份细节描述列表
|
||||
height: 身高（厘米）
|
||||
weight: 体重（千克）
|
||||
age: 年龄
|
||||
gender: 性别
|
||||
appearance: 外貌特征
|
||||
"""
|
||||
if identity_detail is None:
|
||||
identity_detail = []
|
||||
self.identity_detail = identity_detail
|
||||
self.height = height
|
||||
self.weight = weight
|
||||
self.age = age
|
||||
self.gender = gender
|
||||
self.appearance = appearance
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls) -> 'Identity':
|
||||
"""获取Identity单例实例
|
||||
|
||||
Returns:
|
||||
Identity: 单例实例
|
||||
"""
|
||||
if cls._instance is None:
|
||||
cls._instance = cls()
|
||||
return cls._instance
|
||||
|
||||
@classmethod
|
||||
def initialize(cls, identity_detail: List[str], height: int, weight: int,
|
||||
age: int, gender: str, appearance: str) -> 'Identity':
|
||||
"""初始化身份特征
|
||||
|
||||
Args:
|
||||
identity_detail: 身份细节描述列表
|
||||
height: 身高（厘米）
|
||||
weight: 体重（千克）
|
||||
age: 年龄
|
||||
gender: 性别
|
||||
appearance: 外貌特征
|
||||
|
||||
Returns:
|
||||
Identity: 初始化后的身份特征实例
|
||||
"""
|
||||
instance = cls.get_instance()
|
||||
instance.identity_detail = identity_detail
|
||||
instance.height = height
|
||||
instance.weight = weight
|
||||
instance.age = age
|
||||
instance.gender = gender
|
||||
instance.appearance = appearance
|
||||
return instance
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将身份特征转换为字典格式"""
|
||||
return {
|
||||
"identity_detail": self.identity_detail,
|
||||
"height": self.height,
|
||||
"weight": self.weight,
|
||||
"age": self.age,
|
||||
"gender": self.gender,
|
||||
"appearance": self.appearance
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: dict) -> 'Identity':
|
||||
"""从字典创建身份特征实例"""
|
||||
instance = cls.get_instance()
|
||||
for key, value in data.items():
|
||||
setattr(instance, key, value)
|
||||
return instance
|
||||
77
src/individuality/individuality.py
Normal file
77
src/individuality/individuality.py
Normal file
@@ -0,0 +1,77 @@
|
||||
from typing import Optional
|
||||
from .personality import Personality
|
||||
from .identity import Identity
|
||||
|
||||
class Individuality:
|
||||
"""个体特征管理类"""
|
||||
_instance = None
|
||||
|
||||
def __new__(cls, *args, **kwargs):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
return cls._instance
|
||||
|
||||
def __init__(self):
|
||||
self.personality: Optional[Personality] = None
|
||||
self.identity: Optional[Identity] = None
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls) -> 'Individuality':
|
||||
"""获取Individuality单例实例
|
||||
|
||||
Returns:
|
||||
Individuality: 单例实例
|
||||
"""
|
||||
if cls._instance is None:
|
||||
cls._instance = cls()
|
||||
return cls._instance
|
||||
|
||||
def initialize(self, bot_nickname: str, personality_core: str, personality_sides: list,
|
||||
identity_detail: list, height: int, weight: int, age: int,
|
||||
gender: str, appearance: str) -> None:
|
||||
"""初始化个体特征
|
||||
|
||||
Args:
|
||||
bot_nickname: 机器人昵称
|
||||
personality_core: 人格核心特点
|
||||
personality_sides: 人格侧面描述
|
||||
identity_detail: 身份细节描述
|
||||
height: 身高（厘米）
|
||||
weight: 体重（千克）
|
||||
age: 年龄
|
||||
gender: 性别
|
||||
appearance: 外貌特征
|
||||
"""
|
||||
# 初始化人格
|
||||
self.personality = Personality.initialize(
|
||||
bot_nickname=bot_nickname,
|
||||
personality_core=personality_core,
|
||||
personality_sides=personality_sides
|
||||
)
|
||||
|
||||
# 初始化身份
|
||||
self.identity = Identity.initialize(
|
||||
identity_detail=identity_detail,
|
||||
height=height,
|
||||
weight=weight,
|
||||
age=age,
|
||||
gender=gender,
|
||||
appearance=appearance
|
||||
)
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将个体特征转换为字典格式"""
|
||||
return {
|
||||
"personality": self.personality.to_dict() if self.personality else None,
|
||||
"identity": self.identity.to_dict() if self.identity else None
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: dict) -> 'Individuality':
|
||||
"""从字典创建个体特征实例"""
|
||||
instance = cls.get_instance()
|
||||
if data.get("personality"):
|
||||
instance.personality = Personality.from_dict(data["personality"])
|
||||
if data.get("identity"):
|
||||
instance.identity = Identity.from_dict(data["identity"])
|
||||
return instance
|
||||
123
src/individuality/offline_llm.py
Normal file
123
src/individuality/offline_llm.py
Normal file
@@ -0,0 +1,123 @@
|
||||
import asyncio
|
||||
import os
|
||||
import time
|
||||
from typing import Tuple, Union
|
||||
|
||||
import aiohttp
|
||||
import requests
|
||||
from src.common.logger import get_module_logger
|
||||
|
||||
logger = get_module_logger("offline_llm")
|
||||
|
||||
|
||||
class LLM_request_off:
|
||||
def __init__(self, model_name="Pro/deepseek-ai/DeepSeek-V3", **kwargs):
|
||||
self.model_name = model_name
|
||||
self.params = kwargs
|
||||
self.api_key = os.getenv("SILICONFLOW_KEY")
|
||||
self.base_url = os.getenv("SILICONFLOW_BASE_URL")
|
||||
|
||||
if not self.api_key or not self.base_url:
|
||||
raise ValueError("环境变量未正确加载：SILICONFLOW_KEY 或 SILICONFLOW_BASE_URL 未设置")
|
||||
|
||||
logger.info(f"API URL: {self.base_url}") # 使用 logger 记录 base_url
|
||||
|
||||
def generate_response(self, prompt: str) -> Union[str, Tuple[str, str]]:
|
||||
"""根据输入的提示生成模型的响应"""
|
||||
headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}
|
||||
|
||||
# 构建请求体
|
||||
data = {
|
||||
"model": self.model_name,
|
||||
"messages": [{"role": "user", "content": prompt}],
|
||||
"temperature": 0.5,
|
||||
**self.params,
|
||||
}
|
||||
|
||||
# 发送请求到完整的 chat/completions 端点
|
||||
api_url = f"{self.base_url.rstrip('/')}/chat/completions"
|
||||
logger.info(f"Request URL: {api_url}") # 记录请求的 URL
|
||||
|
||||
max_retries = 3
|
||||
base_wait_time = 15 # 基础等待时间（秒）
|
||||
|
||||
for retry in range(max_retries):
|
||||
try:
|
||||
response = requests.post(api_url, headers=headers, json=data)
|
||||
|
||||
if response.status_code == 429:
|
||||
wait_time = base_wait_time * (2**retry) # 指数退避
|
||||
logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...")
|
||||
time.sleep(wait_time)
|
||||
continue
|
||||
|
||||
response.raise_for_status() # 检查其他响应状态
|
||||
|
||||
result = response.json()
|
||||
if "choices" in result and len(result["choices"]) > 0:
|
||||
content = result["choices"][0]["message"]["content"]
|
||||
reasoning_content = result["choices"][0]["message"].get("reasoning_content", "")
|
||||
return content, reasoning_content
|
||||
return "没有返回结果", ""
|
||||
|
||||
except Exception as e:
|
||||
if retry < max_retries - 1: # 如果还有重试机会
|
||||
wait_time = base_wait_time * (2**retry)
|
||||
logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}")
|
||||
time.sleep(wait_time)
|
||||
else:
|
||||
logger.error(f"请求失败: {str(e)}")
|
||||
return f"请求失败: {str(e)}", ""
|
||||
|
||||
logger.error("达到最大重试次数，请求仍然失败")
|
||||
return "达到最大重试次数，请求仍然失败", ""
|
||||
|
||||
async def generate_response_async(self, prompt: str) -> Union[str, Tuple[str, str]]:
|
||||
"""异步方式根据输入的提示生成模型的响应"""
|
||||
headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}
|
||||
|
||||
# 构建请求体
|
||||
data = {
|
||||
"model": self.model_name,
|
||||
"messages": [{"role": "user", "content": prompt}],
|
||||
"temperature": 0.5,
|
||||
**self.params,
|
||||
}
|
||||
|
||||
# 发送请求到完整的 chat/completions 端点
|
||||
api_url = f"{self.base_url.rstrip('/')}/chat/completions"
|
||||
logger.info(f"Request URL: {api_url}") # 记录请求的 URL
|
||||
|
||||
max_retries = 3
|
||||
base_wait_time = 15
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for retry in range(max_retries):
|
||||
try:
|
||||
async with session.post(api_url, headers=headers, json=data) as response:
|
||||
if response.status == 429:
|
||||
wait_time = base_wait_time * (2**retry) # 指数退避
|
||||
logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...")
|
||||
await asyncio.sleep(wait_time)
|
||||
continue
|
||||
|
||||
response.raise_for_status() # 检查其他响应状态
|
||||
|
||||
result = await response.json()
|
||||
if "choices" in result and len(result["choices"]) > 0:
|
||||
content = result["choices"][0]["message"]["content"]
|
||||
reasoning_content = result["choices"][0]["message"].get("reasoning_content", "")
|
||||
return content, reasoning_content
|
||||
return "没有返回结果", ""
|
||||
|
||||
except Exception as e:
|
||||
if retry < max_retries - 1: # 如果还有重试机会
|
||||
wait_time = base_wait_time * (2**retry)
|
||||
logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}")
|
||||
await asyncio.sleep(wait_time)
|
||||
else:
|
||||
logger.error(f"请求失败: {str(e)}")
|
||||
return f"请求失败: {str(e)}", ""
|
||||
|
||||
logger.error("达到最大重试次数，请求仍然失败")
|
||||
return "达到最大重试次数，请求仍然失败", ""
|
||||
119
src/individuality/personality.py
Normal file
119
src/individuality/personality.py
Normal file
@@ -0,0 +1,119 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import Dict, List
|
||||
import os
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
@dataclass
|
||||
class Personality:
|
||||
"""人格特质类"""
|
||||
openness: float # 开放性
|
||||
conscientiousness: float # 尽责性
|
||||
extraversion: float # 外向性
|
||||
agreeableness: float # 宜人性
|
||||
neuroticism: float # 神经质
|
||||
bot_nickname: str # 机器人昵称
|
||||
personality_core: str # 人格核心特点
|
||||
personality_sides: List[str] # 人格侧面描述
|
||||
|
||||
_instance = None
|
||||
|
||||
def __new__(cls, *args, **kwargs):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
return cls._instance
|
||||
|
||||
def __init__(self, personality_core: str = "", personality_sides: List[str] = None):
|
||||
if personality_sides is None:
|
||||
personality_sides = []
|
||||
self.personality_core = personality_core
|
||||
self.personality_sides = personality_sides
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls) -> 'Personality':
|
||||
"""获取Personality单例实例
|
||||
|
||||
Returns:
|
||||
Personality: 单例实例
|
||||
"""
|
||||
if cls._instance is None:
|
||||
cls._instance = cls()
|
||||
return cls._instance
|
||||
|
||||
def _init_big_five_personality(self):
|
||||
"""初始化大五人格特质"""
|
||||
# 构建文件路径
|
||||
personality_file = Path("data/personality") / f"{self.bot_nickname}_personality.per"
|
||||
|
||||
# 如果文件存在，读取文件
|
||||
if personality_file.exists():
|
||||
with open(personality_file, 'r', encoding='utf-8') as f:
|
||||
personality_data = json.load(f)
|
||||
self.openness = personality_data.get('openness', 0.5)
|
||||
self.conscientiousness = personality_data.get('conscientiousness', 0.5)
|
||||
self.extraversion = personality_data.get('extraversion', 0.5)
|
||||
self.agreeableness = personality_data.get('agreeableness', 0.5)
|
||||
self.neuroticism = personality_data.get('neuroticism', 0.5)
|
||||
else:
|
||||
# 如果文件不存在，根据personality_core和personality_core来设置大五人格特质
|
||||
if "活泼" in self.personality_core or "开朗" in self.personality_sides:
|
||||
self.extraversion = 0.8
|
||||
self.neuroticism = 0.2
|
||||
else:
|
||||
self.extraversion = 0.3
|
||||
self.neuroticism = 0.5
|
||||
|
||||
if "认真" in self.personality_core or "负责" in self.personality_sides:
|
||||
self.conscientiousness = 0.9
|
||||
else:
|
||||
self.conscientiousness = 0.5
|
||||
|
||||
if "友善" in self.personality_core or "温柔" in self.personality_sides:
|
||||
self.agreeableness = 0.9
|
||||
else:
|
||||
self.agreeableness = 0.5
|
||||
|
||||
if "创新" in self.personality_core or "开放" in self.personality_sides:
|
||||
self.openness = 0.8
|
||||
else:
|
||||
self.openness = 0.5
|
||||
|
||||
@classmethod
|
||||
def initialize(cls, bot_nickname: str, personality_core: str, personality_sides: List[str]) -> 'Personality':
|
||||
"""初始化人格特质
|
||||
|
||||
Args:
|
||||
bot_nickname: 机器人昵称
|
||||
personality_core: 人格核心特点
|
||||
personality_sides: 人格侧面描述
|
||||
|
||||
Returns:
|
||||
Personality: 初始化后的人格特质实例
|
||||
"""
|
||||
instance = cls.get_instance()
|
||||
instance.bot_nickname = bot_nickname
|
||||
instance.personality_core = personality_core
|
||||
instance.personality_sides = personality_sides
|
||||
instance._init_big_five_personality()
|
||||
return instance
|
||||
|
||||
def to_dict(self) -> Dict:
|
||||
"""将人格特质转换为字典格式"""
|
||||
return {
|
||||
"openness": self.openness,
|
||||
"conscientiousness": self.conscientiousness,
|
||||
"extraversion": self.extraversion,
|
||||
"agreeableness": self.agreeableness,
|
||||
"neuroticism": self.neuroticism,
|
||||
"bot_nickname": self.bot_nickname,
|
||||
"personality_core": self.personality_core,
|
||||
"personality_sides": self.personality_sides
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: Dict) -> 'Personality':
|
||||
"""从字典创建人格特质实例"""
|
||||
instance = cls.get_instance()
|
||||
for key, value in data.items():
|
||||
setattr(instance, key, value)
|
||||
return instance
|
||||
195
src/individuality/renqingziji_with_mymy.py
Normal file
195
src/individuality/renqingziji_with_mymy.py
Normal file
@@ -0,0 +1,195 @@
|
||||
"""
|
||||
The definition of artificial personality in this paper follows the dispositional para-digm and adapts a definition of
|
||||
personality developed for humans [17]:
|
||||
Personality for a human is the "whole and organisation of relatively stable tendencies and patterns of experience and
|
||||
behaviour within one person (distinguishing it from other persons)". This definition is modified for artificial
|
||||
personality:
|
||||
Artificial personality describes the relatively stable tendencies and patterns of behav-iour of an AI-based machine that
|
||||
can be designed by developers and designers via different modalities, such as language, creating the impression
|
||||
of individuality of a humanized social agent when users interact with the machine."""
|
||||
|
||||
from typing import Dict, List
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
from dotenv import load_dotenv
|
||||
import sys
|
||||
|
||||
"""
|
||||
第一种方案：基于情景评估的人格测定
|
||||
"""
|
||||
current_dir = Path(__file__).resolve().parent
|
||||
project_root = current_dir.parent.parent.parent
|
||||
env_path = project_root / ".env"
|
||||
|
||||
root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
|
||||
sys.path.append(root_path)
|
||||
|
||||
from src.plugins.personality.scene import get_scene_by_factor, PERSONALITY_SCENES # noqa: E402
|
||||
from src.plugins.personality.questionnaire import FACTOR_DESCRIPTIONS # noqa: E402
|
||||
from src.plugins.personality.offline_llm import LLMModel # noqa: E402
|
||||
|
||||
# 加载环境变量
|
||||
if env_path.exists():
|
||||
print(f"从 {env_path} 加载环境变量")
|
||||
load_dotenv(env_path)
|
||||
else:
|
||||
print(f"未找到环境变量文件: {env_path}")
|
||||
print("将使用默认配置")
|
||||
|
||||
|
||||
class PersonalityEvaluator_direct:
|
||||
def __init__(self):
|
||||
self.personality_traits = {"开放性": 0, "严谨性": 0, "外向性": 0, "宜人性": 0, "神经质": 0}
|
||||
self.scenarios = []
|
||||
|
||||
# 为每个人格特质获取对应的场景
|
||||
for trait in PERSONALITY_SCENES:
|
||||
scenes = get_scene_by_factor(trait)
|
||||
if not scenes:
|
||||
continue
|
||||
|
||||
# 从每个维度选择3个场景
|
||||
import random
|
||||
|
||||
scene_keys = list(scenes.keys())
|
||||
selected_scenes = random.sample(scene_keys, min(3, len(scene_keys)))
|
||||
|
||||
for scene_key in selected_scenes:
|
||||
scene = scenes[scene_key]
|
||||
|
||||
# 为每个场景添加评估维度
|
||||
# 主维度是当前特质，次维度随机选择一个其他特质
|
||||
other_traits = [t for t in PERSONALITY_SCENES if t != trait]
|
||||
secondary_trait = random.choice(other_traits)
|
||||
|
||||
self.scenarios.append(
|
||||
{"场景": scene["scenario"], "评估维度": [trait, secondary_trait], "场景编号": scene_key}
|
||||
)
|
||||
|
||||
self.llm = LLMModel()
|
||||
|
||||
def evaluate_response(self, scenario: str, response: str, dimensions: List[str]) -> Dict[str, float]:
|
||||
"""
|
||||
使用 DeepSeek AI 评估用户对特定场景的反应
|
||||
"""
|
||||
# 构建维度描述
|
||||
dimension_descriptions = []
|
||||
for dim in dimensions:
|
||||
desc = FACTOR_DESCRIPTIONS.get(dim, "")
|
||||
if desc:
|
||||
dimension_descriptions.append(f"- {dim}：{desc}")
|
||||
|
||||
dimensions_text = "\n".join(dimension_descriptions)
|
||||
|
||||
prompt = f"""请根据以下场景和用户描述，评估用户在大五人格模型中的相关维度得分（1-6分）。
|
||||
|
||||
场景描述：
|
||||
{scenario}
|
||||
|
||||
用户回应：
|
||||
{response}
|
||||
|
||||
需要评估的维度说明：
|
||||
{dimensions_text}
|
||||
|
||||
请按照以下格式输出评估结果（仅输出JSON格式）：
|
||||
{{
|
||||
"{dimensions[0]}": 分数,
|
||||
"{dimensions[1]}": 分数
|
||||
}}
|
||||
|
||||
评分标准：
|
||||
1 = 非常不符合该维度特征
|
||||
2 = 比较不符合该维度特征
|
||||
3 = 有点不符合该维度特征
|
||||
4 = 有点符合该维度特征
|
||||
5 = 比较符合该维度特征
|
||||
6 = 非常符合该维度特征
|
||||
|
||||
请根据用户的回应，结合场景和维度说明进行评分。确保分数在1-6之间，并给出合理的评估。"""
|
||||
|
||||
try:
|
||||
ai_response, _ = self.llm.generate_response(prompt)
|
||||
# 尝试从AI响应中提取JSON部分
|
||||
start_idx = ai_response.find("{")
|
||||
end_idx = ai_response.rfind("}") + 1
|
||||
if start_idx != -1 and end_idx != 0:
|
||||
json_str = ai_response[start_idx:end_idx]
|
||||
scores = json.loads(json_str)
|
||||
# 确保所有分数在1-6之间
|
||||
return {k: max(1, min(6, float(v))) for k, v in scores.items()}
|
||||
else:
|
||||
print("AI响应格式不正确，使用默认评分")
|
||||
return {dim: 3.5 for dim in dimensions}
|
||||
except Exception as e:
|
||||
print(f"评估过程出错：{str(e)}")
|
||||
return {dim: 3.5 for dim in dimensions}
|
||||
|
||||
|
||||
def main():
|
||||
print("欢迎使用人格形象创建程序！")
|
||||
print("接下来，您将面对一系列场景（共15个）。请根据您想要创建的角色形象，描述在该场景下可能的反应。")
|
||||
print("每个场景都会评估不同的人格维度，最终得出完整的人格特征评估。")
|
||||
print("评分标准：1=非常不符合，2=比较不符合，3=有点不符合，4=有点符合，5=比较符合，6=非常符合")
|
||||
print("\n准备好了吗？按回车键开始...")
|
||||
input()
|
||||
|
||||
evaluator = PersonalityEvaluator_direct()
|
||||
final_scores = {"开放性": 0, "严谨性": 0, "外向性": 0, "宜人性": 0, "神经质": 0}
|
||||
dimension_counts = {trait: 0 for trait in final_scores.keys()}
|
||||
|
||||
for i, scenario_data in enumerate(evaluator.scenarios, 1):
|
||||
print(f"\n场景 {i}/{len(evaluator.scenarios)} - {scenario_data['场景编号']}:")
|
||||
print("-" * 50)
|
||||
print(scenario_data["场景"])
|
||||
print("\n请描述您的角色在这种情况下会如何反应：")
|
||||
response = input().strip()
|
||||
|
||||
if not response:
|
||||
print("反应描述不能为空！")
|
||||
continue
|
||||
|
||||
print("\n正在评估您的描述...")
|
||||
scores = evaluator.evaluate_response(scenario_data["场景"], response, scenario_data["评估维度"])
|
||||
|
||||
# 更新最终分数
|
||||
for dimension, score in scores.items():
|
||||
final_scores[dimension] += score
|
||||
dimension_counts[dimension] += 1
|
||||
|
||||
print("\n当前评估结果：")
|
||||
print("-" * 30)
|
||||
for dimension, score in scores.items():
|
||||
print(f"{dimension}: {score}/6")
|
||||
|
||||
if i < len(evaluator.scenarios):
|
||||
print("\n按回车键继续下一个场景...")
|
||||
input()
|
||||
|
||||
# 计算平均分
|
||||
for dimension in final_scores:
|
||||
if dimension_counts[dimension] > 0:
|
||||
final_scores[dimension] = round(final_scores[dimension] / dimension_counts[dimension], 2)
|
||||
|
||||
print("\n最终人格特征评估结果：")
|
||||
print("-" * 30)
|
||||
for trait, score in final_scores.items():
|
||||
print(f"{trait}: {score}/6")
|
||||
print(f"测试场景数：{dimension_counts[trait]}")
|
||||
|
||||
# 保存结果
|
||||
result = {"final_scores": final_scores, "dimension_counts": dimension_counts, "scenarios": evaluator.scenarios}
|
||||
|
||||
# 确保目录存在
|
||||
os.makedirs("results", exist_ok=True)
|
||||
|
||||
# 保存到文件
|
||||
with open("results/personality_result.json", "w", encoding="utf-8") as f:
|
||||
json.dump(result, f, ensure_ascii=False, indent=2)
|
||||
|
||||
print("\n结果已保存到 results/personality_result.json")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
40
src/individuality/scene.py
Normal file
40
src/individuality/scene.py
Normal file
@@ -0,0 +1,40 @@
|
||||
import json
|
||||
from typing import Dict
|
||||
import os
|
||||
|
||||
def load_scenes() -> Dict:
|
||||
"""
|
||||
从JSON文件加载场景数据
|
||||
|
||||
Returns:
|
||||
Dict: 包含所有场景的字典
|
||||
"""
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
json_path = os.path.join(current_dir, 'template_scene.json')
|
||||
|
||||
with open(json_path, 'r', encoding='utf-8') as f:
|
||||
return json.load(f)
|
||||
|
||||
PERSONALITY_SCENES = load_scenes()
|
||||
|
||||
def get_scene_by_factor(factor: str) -> Dict:
|
||||
"""
|
||||
根据人格因子获取对应的情景测试
|
||||
|
||||
Args:
|
||||
factor (str): 人格因子名称
|
||||
|
||||
Returns:
|
||||
Dict: 包含情景描述的字典
|
||||
"""
|
||||
return PERSONALITY_SCENES.get(factor, None)
|
||||
|
||||
|
||||
def get_all_scenes() -> Dict:
|
||||
"""
|
||||
获取所有情景测试
|
||||
|
||||
Returns:
|
||||
Dict: 所有情景测试的字典
|
||||
"""
|
||||
return PERSONALITY_SCENES
|
||||
112
src/individuality/template_scene.json
Normal file
112
src/individuality/template_scene.json
Normal file
@@ -0,0 +1,112 @@
|
||||
{
|
||||
"外向性": {
|
||||
"场景1": {
|
||||
"scenario": "你刚刚搬到一个新的城市工作。今天是你入职的第一天，在公司的电梯里，一位同事微笑着和你打招呼：\n\n同事：「嗨！你是新来的同事吧？我是市场部的小林。」\n\n同事看起来很友善，还主动介绍说：「待会午饭时间，我们部门有几个人准备一起去楼下新开的餐厅，你要一起来吗？可以认识一下其他同事。」",
|
||||
"explanation": "这个场景通过职场社交情境，观察个体对于新环境、新社交圈的态度和反应倾向。"
|
||||
},
|
||||
"场景2": {
|
||||
"scenario": "在大学班级群里，班长发起了一个组织班级联谊活动的投票：\n\n班长：「大家好！下周末我们准备举办一次班级联谊活动，地点在学校附近的KTV。想请大家报名参加，也欢迎大家邀请其他班级的同学！」\n\n已经有几个同学在群里积极响应，有人@你问你要不要一起参加。",
|
||||
"explanation": "通过班级活动场景，观察个体对群体社交活动的参与意愿。"
|
||||
},
|
||||
"场景3": {
|
||||
"scenario": "你在社交平台上发布了一条动态，收到了很多陌生网友的评论和私信：\n\n网友A：「你说的这个观点很有意思！想和你多交流一下。」\n\n网友B：「我也对这个话题很感兴趣，要不要建个群一起讨论？」",
|
||||
"explanation": "通过网络社交场景，观察个体对线上社交的态度。"
|
||||
},
|
||||
"场景4": {
|
||||
"scenario": "你暗恋的对象今天主动来找你：\n\n对方：「那个...我最近在准备一个演讲比赛，听说你口才很好。能不能请你帮我看看演讲稿，顺便给我一些建议？如果你有时间的话，可以一起吃个饭聊聊。」",
|
||||
"explanation": "通过恋爱情境，观察个体在面对心仪对象时的社交表现。"
|
||||
},
|
||||
"场景5": {
|
||||
"scenario": "在一次线下读书会上，主持人突然点名让你分享读后感：\n\n主持人：「听说你对这本书很有见解，能不能和大家分享一下你的想法？」\n\n现场有二十多个陌生的读书爱好者，都期待地看着你。",
|
||||
"explanation": "通过即兴发言场景，观察个体的社交表现欲和公众表达能力。"
|
||||
}
|
||||
},
|
||||
"神经质": {
|
||||
"场景1": {
|
||||
"scenario": "你正在准备一个重要的项目演示，这关系到你的晋升机会。就在演示前30分钟，你收到了主管发来的消息：\n\n主管：「临时有个变动，CEO也会来听你的演示。他对这个项目特别感兴趣。」\n\n正当你准备回复时，主管又发来一条：「对了，能不能把演示时间压缩到15分钟？CEO下午还有其他安排。你之前准备的是30分钟的版本对吧？」",
|
||||
"explanation": "这个场景通过突发的压力情境，观察个体在面对计划外变化时的情绪反应和调节能力。"
|
||||
},
|
||||
"场景2": {
|
||||
"scenario": "期末考试前一天晚上，你收到了好朋友发来的消息：\n\n好朋友：「不好意思这么晚打扰你...我看你平时成绩很好，能不能帮我解答几个问题？我真的很担心明天的考试。」\n\n你看了看时间，已经是晚上11点，而你原本计划的复习还没完成。",
|
||||
"explanation": "通过考试压力场景，观察个体在时间紧张时的情绪管理。"
|
||||
},
|
||||
"场景3": {
|
||||
"scenario": "你在社交媒体上发表的一个观点引发了争议，有不少人开始批评你：\n\n网友A：「这种观点也好意思说出来，真是无知。」\n\n网友B：「建议楼主先去补补课再来发言。」\n\n评论区里的负面评论越来越多，还有人开始人身攻击。",
|
||||
"explanation": "通过网络争议场景，观察个体面对批评时的心理承受能力。"
|
||||
},
|
||||
"场景4": {
|
||||
"scenario": "你和恋人约好今天一起看电影，但在约定时间前半小时，对方发来消息：\n\n恋人：「对不起，我临时有点事，可能要迟到一会儿。」\n\n二十分钟后，对方又发来消息：「可能要再等等，抱歉！」\n\n电影快要开始了，但对方还是没有出现。",
|
||||
"explanation": "通过恋爱情境，观察个体对不确定性的忍耐程度。"
|
||||
},
|
||||
"场景5": {
|
||||
"scenario": "在一次重要的小组展示中，你的组员在演示途中突然卡壳了：\n\n组员小声对你说：「我忘词了，接下来的部分是什么来着...」\n\n台下的老师和同学都在等待，气氛有些尴尬。",
|
||||
"explanation": "通过公开场合的突发状况，观察个体的应急反应和压力处理能力。"
|
||||
}
|
||||
},
|
||||
"严谨性": {
|
||||
"场景1": {
|
||||
"scenario": "你是团队的项目负责人，刚刚接手了一个为期两个月的重要项目。在第一次团队会议上：\n\n小王：「老大，我觉得两个月时间很充裕，我们先做着看吧，遇到问题再解决。」\n\n小张：「要不要先列个时间表？不过感觉太详细的计划也没必要，点到为止就行。」\n\n小李：「客户那边说如果能提前完成有奖励，我觉得我们可以先做快一点的部分。」",
|
||||
"explanation": "这个场景通过项目管理情境，体现个体在工作方法、计划性和责任心方面的特征。"
|
||||
},
|
||||
"场景2": {
|
||||
"scenario": "期末小组作业，组长让大家分工完成一份研究报告。在截止日期前三天：\n\n组员A：「我的部分大概写完了，感觉还行。」\n\n组员B：「我这边可能还要一天才能完成，最近太忙了。」\n\n组员C发来一份没有任何引用出处、可能存在抄袭的内容：「我写完了，你们看看怎么样？」",
|
||||
"explanation": "通过学习场景，观察个体对学术规范和质量要求的重视程度。"
|
||||
},
|
||||
"场景3": {
|
||||
"scenario": "你在一个兴趣小组的群聊中，大家正在讨论举办一次线下活动：\n\n成员A：「到时候见面就知道具体怎么玩了！」\n\n成员B：「对啊，随意一点挺好的。」\n\n成员C：「人来了自然就热闹了。」",
|
||||
"explanation": "通过活动组织场景，观察个体对活动计划的态度。"
|
||||
},
|
||||
"场景4": {
|
||||
"scenario": "你和恋人计划一起去旅游，对方说：\n\n恋人：「我们就随心而行吧！订个目的地，其他的到了再说，这样更有意思。」\n\n距离出发还有一周时间，但机票、住宿和具体行程都还没有确定。",
|
||||
"explanation": "通过旅行规划场景，观察个体的计划性和对不确定性的接受程度。"
|
||||
},
|
||||
"场景5": {
|
||||
"scenario": "在一个重要的团队项目中，你发现一个同事的工作存在明显错误：\n\n同事：「差不多就行了，反正领导也看不出来。」\n\n这个错误可能不会立即造成问题，但长期来看可能会影响项目质量。",
|
||||
"explanation": "通过工作质量场景，观察个体对细节和标准的坚持程度。"
|
||||
}
|
||||
},
|
||||
"开放性": {
|
||||
"场景1": {
|
||||
"scenario": "周末下午，你的好友小美兴致勃勃地给你打电话：\n\n小美：「我刚发现一个特别有意思的沉浸式艺术展！不是传统那种挂画的展览，而是把整个空间都变成了艺术品。观众要穿特制的服装，还要带上VR眼镜，好像还有AI实时互动！」\n\n小美继续说：「虽然票价不便宜，但听说体验很独特。网上评价两极分化，有人说是前所未有的艺术革新，也有人说是哗众取宠。要不要周末一起去体验一下？」",
|
||||
"explanation": "这个场景通过新型艺术体验，反映个体对创新事物的接受程度和尝试意愿。"
|
||||
},
|
||||
"场景2": {
|
||||
"scenario": "在一节创意写作课上，老师提出了一个特别的作业：\n\n老师：「下周的作业是用AI写作工具协助创作一篇小说。你们可以自由探索如何与AI合作，打破传统写作方式。」\n\n班上随即展开了激烈讨论，有人认为这是对创作的亵渎，也有人对这种新形式感到兴奋。",
|
||||
"explanation": "通过新技术应用场景，观察个体对创新学习方式的态度。"
|
||||
},
|
||||
"场景3": {
|
||||
"scenario": "在社交媒体上，你看到一个朋友分享了一种新的生活方式：\n\n「最近我在尝试'数字游牧'生活，就是一边远程工作一边环游世界。没有固定住所，住青旅或短租，认识来自世界各地的朋友。虽然有时会很不稳定，但这种自由的生活方式真的很棒！」\n\n评论区里争论不断，有人向往这种生活，也有人觉得太冒险。",
|
||||
"explanation": "通过另类生活方式，观察个体对非传统选择的态度。"
|
||||
},
|
||||
"场景4": {
|
||||
"scenario": "你的恋人突然提出了一个想法：\n\n恋人：「我们要不要尝试一下开放式关系？就是在保持彼此关系的同时，也允许和其他人发展感情。现在国外很多年轻人都这样。」\n\n这个提议让你感到意外，你之前从未考虑过这种可能性。",
|
||||
"explanation": "通过感情观念场景，观察个体对非传统关系模式的接受度。"
|
||||
},
|
||||
"场景5": {
|
||||
"scenario": "在一次朋友聚会上，大家正在讨论未来职业规划：\n\n朋友A：「我准备辞职去做自媒体，专门介绍一些小众的文化和艺术。」\n\n朋友B：「我想去学习生物科技，准备转行做人造肉研发。」\n\n朋友C：「我在考虑加入一个区块链创业项目，虽然风险很大。」",
|
||||
"explanation": "通过职业选择场景，观察个体对新兴领域的探索意愿。"
|
||||
}
|
||||
},
|
||||
"宜人性": {
|
||||
"场景1": {
|
||||
"scenario": "在回家的公交车上，你遇到这样一幕：\n\n一位老奶奶颤颤巍巍地上了车，车上座位已经坐满了。她站在你旁边，看起来很疲惫。这时你听到前排两个年轻人的对话：\n\n年轻人A：「那个老太太好像站不稳，看起来挺累的。」\n\n年轻人B：「现在的老年人真是...我看她包里还有菜，肯定是去菜市场买完菜回来的，这么多人都不知道叫子女开车接送。」\n\n就在这时，老奶奶一个趔趄，差点摔倒。她扶住了扶手，但包里的东西洒了一些出来。",
|
||||
"explanation": "这个场景通过公共场合的助人情境，体现个体的同理心和对他人需求的关注程度。"
|
||||
},
|
||||
"场景2": {
|
||||
"scenario": "在班级群里，有同学发起为生病住院的同学捐款：\n\n同学A：「大家好，小林最近得了重病住院，医药费很贵，家里负担很重。我们要不要一起帮帮他？」\n\n同学B：「我觉得这是他家里的事，我们不方便参与吧。」\n\n同学C：「但是都是同学一场，帮帮忙也是应该的。」",
|
||||
"explanation": "通过同学互助场景，观察个体的助人意愿和同理心。"
|
||||
},
|
||||
"场景3": {
|
||||
"scenario": "在一个网络讨论组里，有人发布了求助信息：\n\n求助者：「最近心情很低落，感觉生活很压抑，不知道该怎么办...」\n\n评论区里已经有一些回复：\n「生活本来就是这样，想开点！」\n「你这样子太消极了，要积极面对。」\n「谁还没点烦心事啊，过段时间就好了。」",
|
||||
"explanation": "通过网络互助场景，观察个体的共情能力和安慰方式。"
|
||||
},
|
||||
"场景4": {
|
||||
"scenario": "你的恋人向你倾诉工作压力：\n\n恋人：「最近工作真的好累，感觉快坚持不下去了...」\n\n但今天你也遇到了很多烦心事，心情也不太好。",
|
||||
"explanation": "通过感情关系场景，观察个体在自身状态不佳时的关怀能力。"
|
||||
},
|
||||
"场景5": {
|
||||
"scenario": "在一次团队项目中，新来的同事小王因为经验不足，造成了一个严重的错误。在部门会议上：\n\n主管：「这个错误造成了很大的损失，是谁负责的这部分？」\n\n小王看起来很紧张，欲言又止。你知道是他造成的错误，同时你也是这个项目的共同负责人。",
|
||||
"explanation": "通过职场情境，观察个体在面对他人过错时的态度和处理方式。"
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user