AI-Scientist Edu：2025年AI科研教育的革命性突破

# 科研项目管理层核心代码示例
class ProjectManager:
    def __init__(self):
        self.project_designer = ProjectDesigner()
        self.resource_manager = ResourceManager()
        self.team_manager = TeamManager()
        self.progress_tracker = ProgressTracker()
    
    def create_project(self, project_info):
        # 创建科研项目
        # 1. 验证项目信息
        if not self._validate_project_info(project_info):
            raise ValueError("Invalid project information")
        
        # 2. 设计项目结构
        project = self.project_designer.design_project(project_info)
        
        # 3. 分配资源
        project = self.resource_manager.allocate_resources(project, project_info.get("resources", []))
        
        return project
    
    def add_team_member(self, project_id, member_info):
        # 添加团队成员
        # 1. 获取项目
        project = self._get_project(project_id)
        
        # 2. 添加成员
        updated_project = self.team_manager.add_member(project, member_info)
        
        return updated_project
    
    def track_progress(self, project_id, updates):
        # 跟踪项目进度
        # 1. 获取项目
        project = self._get_project(project_id)
        
        # 2. 更新进度
        updated_project = self.progress_tracker.update(project, updates)
        
        return updated_project
    
    def _validate_project_info(self, project_info):
        # 验证项目信息
        required_fields = ["title", "description", "domain", "duration"]
        return all(field in project_info for field in required_fields)
    
    def _get_project(self, project_id):
        # 获取项目
        pass

# AI辅助科研层核心代码示例
class AIAssistedResearch:
    def __init__(self):
        self.topic_assistant = TopicAssistant()
        self.experiment_designer = ExperimentDesigner()
        self.data_analyzer = DataAnalyzer()
        self.literature_assistant = LiteratureAssistant()
    
    def suggest_topics(self, domain, interests=None):
        # 建议科研选题
        return self.topic_assistant.suggest(domain, interests)
    
    def design_experiment(self, topic, constraints=None):
        # 设计实验
        return self.experiment_designer.design(topic, constraints)
    
    def analyze_data(self, data, analysis_type=None):
        # 数据分析
        return self.data_analyzer.analyze(data, analysis_type)
    
    def search_literature(self, query, filters=None):
        # 文献搜索
        return self.literature_assistant.search(query, filters)
    
    def generate_literature_review(self, topic, papers=None):
        # 生成文献综述
        if papers is None:
            papers = self.literature_assistant.search(topic, {"limit": 50})
        
        return self.literature_assistant.generate_review(topic, papers)

# 虚拟科研环境层核心代码示例
class VirtualResearchEnvironment:
    def __init__(self):
        self.virtual_lab = VirtualLab()
        self.simulation_environment = SimulationEnvironment()
        self.remote_device = RemoteExperimentDevice()
        self.data_sharing = DataSharingPlatform()
    
    def create_virtual_lab(self, lab_type, params=None):
        # 创建虚拟实验室
        return self.virtual_lab.create(lab_type, params)
    
    def run_simulation(self, simulation_type, parameters):
        # 运行仿真
        return self.simulation_environment.run(simulation_type, parameters)
    
    def access_remote_device(self, device_id, command):
        # 访问远程实验设备
        return self.remote_device.execute(device_id, command)
    
    def share_data(self, project_id, data, access_level="team"):
        # 共享数据
        return self.data_sharing.share(project_id, data, access_level)
    
    def get_shared_data(self, project_id):
        # 获取共享数据
        return self.data_sharing.get(project_id)

# 评估反馈层核心代码示例
class AssessmentFeedback:
    def __init__(self):
        self.ai_evaluator = AIEvaluator()
        self.feedback_generator = FeedbackGenerator()
        self成果展示 = AchievementShowcase()
        self.certification_manager = CertificationManager()
    
    def evaluate_project(self, project_id, project_data):
        # 评估科研项目
        # 1. AI评估
        evaluation = self.ai_evaluator.evaluate(project_id, project_data)
        
        # 2. 生成反馈
        feedback = self.feedback_generator.generate(evaluation, project_data)
        
        return {
            "evaluation": evaluation,
            "feedback": feedback
        }
    
    def showcase_achievement(self, project_id, achievement_data):
        # 展示科研成果
        return self.achievement_showcase.create(project_id, achievement_data)
    
    def generate_certificate(self, student_id, project_id):
        # 生成技能认证
        # 1. 验证科研成果
        if not self._verify_achievement(student_id, project_id):
            return None
        
        # 2. 生成证书
        certificate = self.certification_manager.generate(student_id, project_id)
        
        return certificate
    
    def _verify_achievement(self, student_id, project_id):
        # 验证科研成果
        pass

# 克隆仓库
git clone https://github.com/AI-Scientist-Edu/AI-Scientist-Edu.git
cd AI-Scientist-Edu

# 创建虚拟环境
python -m venv venv
source venv/bin/activate  # Linux/macOS
venv\Scripts\activate  # Windows

# 安装依赖
pip install -r requirements.txt

# 配置环境变量
export AISCIENTIST_CONFIG="./config.yaml"
export AISCIENTIST_API_KEY="your-api-key"
export AISCIENTIST_LOG_LEVEL="INFO"
export AISCIENTIST_DATABASE_URL="postgresql://user:password@localhost:5432/aiscientist"

# 初始化数据库
python -m aiscientist init-db

# 启动AI-Scientist Edu服务
python -m aiscientist serve

# 导入AI-Scientist Edu
from aiscientist import AIScientistEdu

# 初始化AI-Scientist Edu
aiscientist = AIScientistEdu()

# 1. 获取选题建议
topics = aiscientist.suggest_topics(
    domain="人工智能",
    interests=["机器学习", "计算机视觉"]
)

print("选题建议：")
for i, topic in enumerate(topics[:5]):  # 只显示前5个选题
    print(f"{i+1}. {topic['title']}")
    print(f"   描述：{topic['description'][:100]}...")
    print(f"   创新性：{topic['novelty']}")
    print(f"   可行性：{topic['feasibility']}")
    print()

# 2. 创建科研项目
selected_topic = topics[0]
project = aiscientist.create_project({
    "title": selected_topic["title"],
    "description": selected_topic["description"],
    "domain": "人工智能",
    "duration": 12,
    "team_members": ["user1", "user2", "user3"]
})

print(f"科研项目创建成功！项目ID：{project['id']}")
print(f"项目名称：{project['title']}")
print(f"团队成员：{[member['name'] for member in project['team_members']]}")

# 3. 获取实验设计
experiment_design = aiscientist.design_experiment(selected_topic["title"])
print("\n实验设计：")
print(f"实验名称：{experiment_design['title']}")
print(f"实验目的：{experiment_design['objective']}")
print(f"实验步骤：")
for step in experiment_design['steps'][:3]:  # 只显示前3个步骤
    print(f"   - {step}")

# 4. 运行虚拟实验
# virtual_lab = aiscientist.create_virtual_lab(
#     lab_type="computer_vision",
#     params={"dataset": "coco", "model": "yolov8"}
# )
# 
# print("\n虚拟实验室创建成功！")
# print(f"实验室ID：{virtual_lab['id']}")
# print(f"实验室类型：{virtual_lab['type']}")

# 5. 生成文献综述
# literature_review = aiscientist.generate_literature_review(selected_topic["title"])
# print("\n文献综述生成成功！")
# print(f"引用文献数量：{literature_review['citation_count']}")
# print(f"综述摘要：{literature_review['abstract'][:200]}...")