锦中融合门户系统

# 智能体基础框架

class SmartAgent:

def __init__(self):

self.memory = {}

def process_request(self, request):

if "教室" in request:

return self.book_classroom(request)

elif "课程" in request:

return self.query_course(request)

else:

return "无法识别请求，请重新输入。"

def book_classroom(self, request):

# 简单逻辑：根据时间判断是否可预订

time = request.split(" ")[1]

if time not in self.memory:

self.memory[time] = True

return f"成功预约时间 {time} 的教室！"

else:

return f"时间 {time} 已被占用，无法预约。"

def query_course(self, request):

course_name = request.split(" ")[1]

# 假设我们有一个课程数据库

courses = {"数学": "王老师", "物理": "李教授", "计算机": "张博士"}

if course_name in courses:

return f"课程 {course_name} 的讲师是 {courses[course_name]}。"

else:

return f"没有找到课程 {course_name} 的信息。"

# 使用示例

agent = SmartAgent()

print(agent.process_request("预约教室 10:00"))

print(agent.process_request("查询课程 数学"))

import nltk

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.metrics.pairwise import cosine_similarity

# 示例训练数据

training_data = [

("预约教室 10点", "book_classroom"),

("查询课程 数学", "query_course"),

("查看今天课程表", "show_schedule"),

("帮我找一下计算机课", "query_course")

]

# 提取特征

texts = [data[0] for data in training_data]

labels = [data[1] for data in training_data]

vectorizer = TfidfVectorizer()

X = vectorizer.fit_transform(texts)

# 与新请求匹配

def predict_intent(text):

new_text = [text]

X_new = vectorizer.transform(new_text)

similarities = cosine_similarity(X_new, X)

best_match_index = similarities.argmax()

return labels[best_match_index]

# 智能体增强版

class EnhancedSmartAgent:

def __init__(self):

self.memory = {}

def process_request(self, request):

intent = predict_intent(request)

if intent == "book_classroom":

return self.book_classroom(request)

elif intent == "query_course":

return self.query_course(request)

elif intent == "show_schedule":

return self.show_schedule()

else:

return "无法识别请求，请重新输入。"

def book_classroom(self, request):

time = request.split(" ")[1]

if time not in self.memory:

self.memory[time] = True

return f"成功预约时间 {time} 的教室！"

else:

return f"时间 {time} 已被占用，无法预约。"

def query_course(self, request):

course_name = request.split(" ")[1]

courses = {"数学": "王老师", "物理": "李教授", "计算机": "张博士"}

if course_name in courses:

return f"课程 {course_name} 的讲师是 {courses[course_name]}。"

else:

return f"没有找到课程 {course_name} 的信息。"

def show_schedule(self):

return "今日课程表：\n- 数学 9:00\n- 物理 14:00\n- 计算机 16:00"

# 使用示例

agent = EnhancedSmartAgent()

print(agent.process_request("帮我找一下计算机课"))

print(agent.process_request("预约教室 15点"))

print(agent.process_request("查看今天课程表"))