import streamlit as st import logging import requests import json from typing import Optional # 配置日志 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') def generate_email_with_vveai( profile1: str, profile2: str, style: str = "friendly", temperature: float = 0.7, api_key: Optional[str] = None ) -> str: """ 使用VVEAI API基于两个LinkedIn简介生成个性化咖啡聊天邀请邮件。 参数: profile1 (str): 发件人的LinkedIn简介文本 profile2 (str): 收件人的LinkedIn简介文本 style (str): 邮件风格，可选项为 "formal", "friendly", "humorous" temperature (float): 生成文本的创造性程度 (0.0-1.0) api_key (str, optional): VVEAI API密钥 返回: str: 生成的个性化咖啡聊天邮件 """ try: # 验证输入 if not profile1 or not profile2: raise ValueError("两个简介都不能为空") valid_styles = ["formal", "friendly", "humorous"] if style not in valid_styles: logging.warning(f"不支持的风格 '{style}'，使用默认的 'friendly'") style = "friendly" if temperature < 0.0 or temperature > 1.0: logging.warning(f"温度 {temperature} 超出范围，调整至 0.7") temperature = 0.7 # 验证API密钥 if not api_key: raise ValueError("请提供VVEAI API密钥") # 构建提示词 prompt = f""" I need to write a personalized coffee chat invitation email based on two LinkedIn profiles. MY PROFILE: {profile1} TARGET PERSON'S PROFILE: {profile2} TASK: 1. Analyze both profiles to identify meaningful common points or connections (universities, companies, industries, skills, interests, etc.) 2. Write a personalized coffee chat invitation email from me to the target person 3. The email should: - Start with a brief introduction of myself - Mention 2-3 specific commonalities or interesting points from our profiles - Express genuine interest in their work/experience - Include a clear but polite request for a 15-30 minute coffee chat - Suggest flexibility for their schedule - End with a professional closing STYLE: The tone should be {style}. If formal: professional and respectful; if friendly: warm and conversational; if humorous: light and engaging but still professional. IMPORTANT GUIDELINES: - Keep the email concise (150-250 words) - Make it feel authentic and human, not templated - Focus on creating a genuine connection - Avoid generic flattery - Be specific about shared connections or interests - Don't be pushy or demanding Format the response as a complete, ready-to-send email without explanations. """ # 准备API请求 system_message = "You are an expert email writer who helps professionals create personalized networking messages." # VVEAI API端点 url = "https://api.vveai.com/v1/chat/completions" # 构建请求 headers = { "Content-Type": "application/json", "Authorization": f"Bearer {api_key}" } payload = { "model": "gpt-4", # 可能需要根据VVEAI支持的模型调整 "messages": [ {"role": "system", "content": system_message}, {"role": "user", "content": prompt} ], "temperature": temperature, "max_tokens": 1000 } # 发送请求 response = requests.post(url, headers=headers, data=json.dumps(payload), timeout=60) # 添加详细日志便于调试 logging.info(f"API响应状态码: {response.status_code}") logging.info(f"API响应头: {response.headers}") # 处理响应 if response.status_code == 200: result = response.json() # 记录完整响应便于调试 logging.info(f"API响应内容: {result}") try: email_text = result["choices"][0]["message"]["content"].strip() return email_text except KeyError as e: logging.error(f"响应格式错误: {e}. 完整响应: {result}") return f"API响应格式错误: {e}。请联系VVEAI支持获取帮助。" else: error_message = f"API请求失败: {response.status_code} - {response.text}" logging.error(error_message) return f"API错误: {response.status_code}。请检查您的API密钥是否正确。详细信息: {response.text}" except ValueError as e: logging.error(f"输入错误: {str(e)}") return f"发生错误: {str(e)}" except requests.RequestException as e: logging.error(f"请求错误: {str(e)}") return f"网络请求错误: {str(e)}" except Exception as e: logging.error(f"意外错误: {str(e)}") return f"发生未预期的错误: {str(e)}" # 页面配置 st.set_page_config( page_title="个性化咖啡聊天邮件生成器", page_icon="☕", layout="wide" ) # 标题和说明 st.title("☕ 个性化咖啡聊天邮件生成器") st.markdown(""" 此应用可以帮助求职者生成个性化的咖啡聊天邀请邮件。 只需输入您的简介和目标联系人的简介，系统将分析共同点并生成一封真诚的邀请邮件。 **注意：此应用使用 VVEAI API 服务，请确保输入正确的 API 密钥。** """) # 侧边栏 - API设置 with st.sidebar: st.header("API设置") api_key = st.text_input("VVEAI API密钥", type="password", key="api_key", help="输入以 sk- 开头的 VVEAI API 密钥") # 添加API状态检测按钮 if st.button("测试API连接"): if not api_key: st.error("请先输入API密钥") else: try: # 简单的API测试请求 test_url = "https://api.vveai.com/v1/chat/completions" test_headers = { "Content-Type": "application/json", "Authorization": f"Bearer {api_key}" } test_payload = { "model": "gpt-4", "messages": [ {"role": "user", "content": "Hello"} ], "max_tokens": 5 } test_response = requests.post( test_url, headers=test_headers, data=json.dumps(test_payload), timeout=10 ) if test_response.status_code == 200: st.success("API连接成功！") else: st.error(f"API连接失败: {test_response.status_code} - {test_response.text}") except Exception as e: st.error(f"测试API时出错: {str(e)}") st.subheader("邮件风格") style = st.radio( "选择风格:", ["formal", "friendly", "humorous"], index=1, format_func=lambda x: { "formal": "正式专业", "friendly": "友好温暖", "humorous": "幽默轻松" }[x] ) temperature = st.slider("创造性程度", min_value=0.0, max_value=1.0, value=0.7, step=0.1, help="较低的值使输出更可预测，较高的值使输出更创意") # 主界面 - 两栏布局 col1, col2 = st.columns(2) with col1: st.header("您的简介") profile1 = st.text_area( "粘贴您的LinkedIn简介或专业背景", height=300, placeholder="例如：\n我是一名拥有5年经验的金融分析师，毕业于北京大学金融学专业。我在摩根士丹利工作了3年，专注于投资银行业务..." ) with col2: st.header("目标联系人的简介") profile2 = st.text_area( "粘贴目标联系人的LinkedIn简介或专业背景", height=300, placeholder="例如：\n高级投资银行家，现任高盛副总裁。清华大学MBA毕业，擅长并购交易，在科技行业有丰富经验..." ) # 生成按钮和结果显示 submit_disabled = not api_key or not profile1 or not profile2 if submit_disabled: if not api_key: reason = "请先输入VVEAI API密钥" else: reason = "请填写两个简介" st.warning(reason) if st.button("生成邮件", type="primary", disabled=submit_disabled): with st.spinner("正在分析简介并创建个性化邮件..."): email = generate_email_with_vveai( profile1=profile1, profile2=profile2, style=style, temperature=temperature, api_key=api_key ) # 检查是否发生错误 if email.startswith("发生错误") or email.startswith("API错误") or email.startswith("网络请求错误"): st.error(email) else: st.success("邮件已生成！") # 显示结果 st.header("您的个性化咖啡聊天邮件") st.text_area("可复制的邮件内容", email, height=400) st.download_button( label="下载邮件", data=email, file_name="咖啡聊天邀请.txt", mime="text/plain" ) # 调试信息（可选，帮助解决API问题） if st.checkbox("显示调试信息"): st.subheader("API信息") st.markdown(""" - API端点: `https://api.vveai.com/v1/chat/completions` - 请求方法: POST - 内容类型: application/json - 授权方式: Bearer Token 如果遇到持续的API问题，请联系VVEAI支持团队并提供以上信息。 """) # 使用提示 st.markdown("---") st.subheader("💡 使用提示") st.markdown(""" - **简介内容越详细**，生成的邮件就越个性化和有针对性 - **尝试不同风格**以适应不同的行业和联系人 - 生成后可以**微调邮件内容**，添加您认为合适的个人细节 - 适合用于**金融、咨询和科技行业**的专业人士 - 如果API连接测试失败，请确认您的**VVEAI API密钥**是否正确 """)