wehub-resource-sync
148 lines
3.4 KiB
Markdown
148 lines
3.4 KiB
Markdown
# Deploying the Agent to Railway
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This guide covers deploying the LangGraph agent to Railway.
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## Prerequisites
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- [Railway account](https://railway.app/) (free tier available)
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- Railway CLI (optional but recommended): `npm install -g @railway/cli`
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- Google AI API key from [Google AI Studio](https://makersuite.google.com/app/apikey)
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## Method 1: Deploy via Railway CLI (Recommended)
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1. **Install Railway CLI** (if not already installed):
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```bash
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npm install -g @railway/cli
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```
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2. **Login to Railway**:
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```bash
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railway login
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```
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3. **Initialize Railway project** (from the agent directory):
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```bash
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cd agent
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railway init
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```
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4. **Set environment variables**:
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```bash
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railway variables set GOOGLE_API_KEY=your-google-ai-api-key-here
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```
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5. **Deploy**:
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```bash
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railway up
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```
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6. **Get the deployment URL**:
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```bash
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railway domain
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```
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## Method 2: Deploy via Railway Dashboard
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1. **Go to [Railway Dashboard](https://railway.app/dashboard)**
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2. **Create New Project**:
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- Click "New Project"
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- Select "Deploy from GitHub repo"
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- Connect your GitHub account if not already connected
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- Select this repository
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3. **Configure the service**:
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- Railway will auto-detect the Dockerfile
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- Root directory: `/agent`
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- Port: 8000 (automatically detected)
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4. **Set Environment Variables**:
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- Go to the "Variables" tab
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- Add: `GOOGLE_API_KEY` = your Google AI API key
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- (Optional) Add LangSmith variables for tracing
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5. **Deploy**:
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- Railway will automatically build and deploy
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- Wait for the build to complete (usually 2-3 minutes)
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6. **Get the URL**:
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- Go to "Settings" > "Networking"
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- Click "Generate Domain"
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- Your agent will be available at: `https://your-project.up.railway.app`
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## Method 3: Deploy via Railway Button
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Add this to your repository README:
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```markdown
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[](https://railway.app/template/your-template-id)
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```
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## Updating the Frontend
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After deploying the agent, update your Next.js frontend to use the Railway URL:
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1. Open `src/app/api/copilotkit/route.ts`
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2. Update the agent URL:
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```typescript
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const agent = new LangGraphAgent({
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agentUrl: process.env.AGENT_URL || "https://your-project.up.railway.app",
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});
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```
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3. Add to your `.env.local`:
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```
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AGENT_URL=https://your-project.up.railway.app
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```
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## Health Check
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Once deployed, verify the agent is running:
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```bash
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curl https://your-project.up.railway.app/health
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```
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## Monitoring
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- View logs: `railway logs`
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- View metrics: Railway Dashboard > Metrics tab
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- Add LangSmith for tracing: Set `LANGCHAIN_TRACING_V2=true` and `LANGCHAIN_API_KEY`
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## Troubleshooting
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### Build fails with "No space left on device"
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- Railway free tier has limited build space
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- Try removing unused dependencies from requirements.txt
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### Agent timeout errors
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- Railway free tier has request timeouts
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- For production, upgrade to Railway Pro
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### Environment variables not working
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- Ensure variables are set in Railway dashboard or via CLI
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- Restart the deployment after adding variables
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## Cost Optimization
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Railway pricing:
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- Free tier: $5 credit/month
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- Pro: $20/month + usage-based pricing
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- Image generation with Gemini uses Google AI quota, not Railway resources
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For production deployment, consider:
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- Monitoring image generation usage
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- Implementing rate limiting
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- Caching generated images
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