锦中人工智能助手

# 安装必要的库

# pip install transformers torch

from transformers import pipeline

# 加载预训练的问答模型

qa_pipeline = pipeline("question-answering")

# 示例问题和上下文

question = "什么是人工智能？"

context = "人工智能（Artificial Intelligence，简称AI）是指由人创造的能够执行需要人类智能的任务的系统或机器。"

# 运行问答模型

result = qa_pipeline(question=question, context=context)

print(f"问题：{question}")

print(f"答案：{result['answer']}")

print(f"得分：{result['score']}")

from flask import Flask, request, jsonify

from transformers import pipeline

app = Flask(__name__)

# 初始化问答模型

qa_pipeline = pipeline("question-answering")

@app.route('/ask', methods=['POST'])

def ask():

data = request.get_json()

question = data.get('question')

context = data.get('context')

if not question or not context:

return jsonify({"error": "缺少问题或上下文"}), 400

result = qa_pipeline(question=question, context=context)

return jsonify({

"answer": result["answer"],

"score": result["score"]

})

if __name__ == '__main__':

app.run(debug=True)

import sqlite3

# 创建数据库连接

conn = sqlite3.connect('school_qa.db')

cursor = conn.cursor()

# 创建表

cursor.execute('''

CREATE TABLE IF NOT EXISTS questions (

id INTEGER PRIMARY KEY AUTOINCREMENT,

question TEXT NOT NULL,

answer TEXT NOT NULL,

score REAL NOT NULL,

timestamp DATETIME DEFAULT CURRENT_TIMESTAMP

)

''')

# 插入数据

def insert_question(question, answer, score):

cursor.execute('''

INSERT INTO questions (question, answer, score)

VALUES (?, ?, ?)

''', (question, answer, score))

conn.commit()

# 查询所有问题

def get_all_questions():

cursor.execute('SELECT * FROM questions')

return cursor.fetchall()

# 关闭连接

conn.close()