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| import os | |
| import streamlit as st | |
| from PIL import Image | |
| import pytesseract | |
| import openai | |
| from openai import OpenAI | |
| import subprocess | |
| # ========== ✅ 设置 GPT Key ========== | |
| client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) | |
| # ========== ✅ 页面设置 ========== | |
| st.set_page_config(page_title="AI Cold Email Generator", layout="centered") | |
| st.title("📬 AI Cold Email Generator") | |
| st.write("上传两位 LinkedIn 截图（每人可多张），系统将识别并生成 Coffee Chat 邀请邮件") | |
| # ========== ✅ 函数区 ========== | |
| def extract_text_from_images(uploaded_files): | |
| """从多张图片中提取文本""" | |
| all_text = "" | |
| for uploaded_file in uploaded_files: | |
| image = Image.open(uploaded_file).convert("RGB") | |
| text = pytesseract.image_to_string(image) | |
| all_text += text + "\n" | |
| return all_text.strip() | |
| def generate_email(profile1_text, profile2_text): | |
| """调用 GPT 生成邮件""" | |
| prompt = f""" | |
| 根据以下两人的 LinkedIn Profile，提取共同点，并生成一封自然、有温度的 Coffee Chat 邀请邮件（避免模板化）： | |
| 📌 Profile 1: | |
| {profile1_text} | |
| 📌 Profile 2: | |
| {profile2_text} | |
| ✉️ 邮件内容如下： | |
| """ | |
| response = client.chat.completions.create( | |
| model="gpt-4", | |
| messages=[ | |
| {"role": "system", "content": "你是一位 AI Networking 邮件助手，擅长生成 Coffee Chat 邮件"}, | |
| {"role": "user", "content": prompt} | |
| ], | |
| temperature=0.7, | |
| max_tokens=600 | |
| ) | |
| return response.choices[0].message.content.strip() | |
| def check_tesseract(): | |
| """调试用：查看 OCR 是否安装成功""" | |
| try: | |
| version = subprocess.check_output(["tesseract", "--version"]) | |
| return version.decode() | |
| except Exception as e: | |
| return str(e) | |
| # ========== ✅ 页面上传区 ========== | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| files1 = st.file_uploader("上传你的 LinkedIn 截图（支持多张）", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key="profile1") | |
| with col2: | |
| files2 = st.file_uploader("上传目标联系人的截图（支持多张）", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key="profile2") | |
| if st.button("🚀 生成邮件"): | |
| if files1 and files2: | |
| with st.spinner("正在识别图像并生成邮件..."): | |
| profile1_text = extract_text_from_images(files1) | |
| profile2_text = extract_text_from_images(files2) | |
| email = generate_email(profile1_text, profile2_text) | |
| st.success("✅ 邮件生成成功") | |
| st.text_area("📨 Coffee Chat 邮件内容", email, height=300) | |
| else: | |
| st.warning("请上传双方的截图") | |
| # ========== ✅ OCR 安装测试区 ========== | |
| with st.expander("🛠️ 查看 Tesseract 安装状态（调试用）"): | |
| result = check_tesseract() | |
| if "tesseract" in result.lower(): | |
| st.success("✅ Tesseract 安装成功") | |
| st.code(result, language="bash") | |
| else: | |
| st.error("❌ Tesseract 未安装") | |
| st.text(result) | |