st2411020202
3bdbf1f462
添加.python-version文件指定Python版本 将依赖从requirements.txt迁移至pyproject.toml 添加python-dotenv依赖用于环境变量管理 新增.env-example作为环境变量配置模板 生成uv.lock锁定依赖版本 添加example.py作为功能示例
64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""
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AI面试助手示例文件
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展示如何使用AI面试助手的核心功能
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"""
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import streamlit as st
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import os
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from dotenv import load_dotenv
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# 加载环境变量
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load_dotenv()
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def main():
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"""示例主函数"""
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st.title("AI面试助手 - 使用示例")
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# 展示环境变量配置
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st.subheader("环境变量配置")
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st.write("请确保已配置以下环境变量（在.env文件中）：")
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st.code("""
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# Streamlit配置
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STREAMLIT_SERVER_PORT=8501
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STREAMLIT_SERVER_ADDRESS=localhost
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# 应用配置
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APP_NAME=AI面试助手
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APP_VERSION=1.0.0
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# 历史记录目录
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HISTORY_DIR=interview_history
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""")
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# 功能演示
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st.subheader("功能演示")
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# 1. 面试者信息收集
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st.write("## 1. 面试者信息收集")
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with st.form("candidate_info_form"):
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name = st.text_input("姓名")
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email = st.text_input("邮箱")
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education = st.text_input("学历")
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experience = st.text_input("工作经验")
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submitted = st.form_submit_button("提交信息")
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if submitted:
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st.success(f"信息已提交：{name} - {email}")
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# 2. 职位选择
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st.write("## 2. 职位选择")
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job_options = ["Python开发", "产品经理", "前端开发", "后端开发", "UI/UX设计"]
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selected_job = st.selectbox("选择目标职位", job_options)
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st.write(f"您选择的职位：{selected_job}")
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# 3. 面试官类型选择
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st.write("## 3. 面试官类型选择")
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interviewer_types = ["严谨型", "亲和型", "压力型", "技术型", "管理型"]
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selected_interviewer = st.selectbox("选择面试官类型", interviewer_types)
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st.write(f"您选择的面试官类型：{selected_interviewer}")
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st.success("示例功能演示完成！")
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if __name__ == "__main__":
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main() |