b56d469648
- Fix Docker cache mount issues that caused Railway build failures - Add port argument support to MCP server for Railway compatibility - Create Railway-optimized Dockerfile without cache mounts - Add railway.json configuration for proper deployment - Create comprehensive deployment and ChatGPT integration guides - Add environment variable templates for Railway deployment - Support Railway's PORT environment variable handling - Ready for ChatGPT MCP SSE integration 🚀 Generated with Claude Code (https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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789 B
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28 lines
No EOL
789 B
Text
# Railway Environment Variables Template
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# Copy these to your Railway project environment variables
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# Required: OpenAI API Configuration
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OPENAI_API_KEY=sk-proj-your-openai-api-key-here
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MODEL_NAME=gpt-4.1-mini
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SMALL_MODEL_NAME=gpt-4.1-nano
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# Neo4j Database Configuration
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# Option 1: Neo4j Aura Cloud (Recommended for production)
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NEO4J_URI=neo4j+s://your-instance.databases.neo4j.io
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NEO4J_USER=neo4j
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NEO4J_PASSWORD=your-aura-password
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# Option 2: Local Neo4j (Development only)
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# NEO4J_URI=bolt://localhost:7687
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# NEO4J_USER=neo4j
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# NEO4J_PASSWORD=password
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# Optional Configuration
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LLM_TEMPERATURE=0.0
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SEMAPHORE_LIMIT=10
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GRAPHITI_TELEMETRY_ENABLED=false
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# Railway automatically sets PORT and HOST
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# These are handled by the application automatically
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# PORT=8000
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# MCP_SERVER_HOST=0.0.0.0 |