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🚀 Streamlit Cloud Deployment Guide

Quick Deploy Steps

1. Repository Setup

# Initialize repository (if needed)
git init

# Add all files
git add .
git commit -m "LinkedIn Sourcing Agent - Ready for deployment"

# Push to GitHub
git remote add origin https://github.com/YOUR_USERNAME/linkedin-sourcing-agent.git
git push -u origin main

2. Deploy to Streamlit Cloud

  1. Visit: share.streamlit.io
  2. Sign in with GitHub
  3. Click "New app"
  4. Select your repository
  5. Set main file: app_streamlit_cloud.py
  6. Deploy!

Alternative: Direct Deployment Link

Open in Streamlit

Files Configured for Deployment

✅ app_streamlit_cloud.py - Streamlit Cloud optimized version
✅ requirements_streamlit.txt - Minimal dependencies
✅ .streamlit/config.toml - Streamlit configuration
✅ packages.txt - System packages (if needed)

Features in Deployed Version

🎯 Candidate Search - Job description-based matching
📊 AI Scoring - Intelligent candidate fit scoring
💌 Outreach Generation - Personalized message creation
📈 Analytics - Search history and insights
📥 Export Options - Excel and JSON downloads
🎨 Professional UI - Modern, responsive design

Demo Data

The deployed version uses realistic demo data, making it perfect for:

  • Portfolio demonstrations
  • Feature showcases
  • Interface testing
  • Client presentations

Environment Variables (Optional)

Add these in Streamlit Cloud settings for enhanced features:

  • OPENAI_API_KEY - For AI-powered enhancements
  • GEMINI_API_KEY - Alternative AI provider
  • LINKEDIN_API_KEY - For real LinkedIn data

Support

Ready to deploy? Your LinkedIn Sourcing Agent will be live in minutes! 🎉