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README.md

Deployment Documentation

Comprehensive deployment guides for the Multi-Modal Academic Research System.

Quick Links

Documentation Overview

1. Local Deployment Guide (local.md)

Complete guide for setting up and running the application on your local machine.

Contents:

  • Prerequisites and system requirements
  • Virtual environment setup
  • Environment configuration
  • Running the application
  • Running multiple instances
  • Port configuration
  • Development workflow
  • Comprehensive troubleshooting (10+ common issues)

Best for:

  • Local development
  • Testing and debugging
  • Learning the system
  • Quick prototyping

File size: ~800 lines | 15KB


2. Docker Deployment (docker.md)

Containerization guide using Docker and Docker Compose.

Contents:

  • Dockerfile creation with best practices
  • Multi-service Docker Compose setup
  • Volume management and data persistence
  • Container orchestration and lifecycle
  • Networking configuration
  • Health checks and monitoring
  • Performance optimization
  • Troubleshooting containerized deployments

Best for:

  • Consistent environments
  • CI/CD pipelines
  • Easy deployment across teams
  • Isolated testing

File size: ~850 lines | 18KB


3. OpenSearch Setup (opensearch.md)

Deep dive into OpenSearch installation, configuration, and optimization.

Contents:

  • Installation methods (Docker, native, Homebrew)
  • Configuration for development and production
  • Index management and optimization
  • Security configuration (SSL/TLS, authentication)
  • Performance tuning
  • Single-node and multi-node cluster setup
  • Backup and restore strategies
  • Monitoring and maintenance
  • Troubleshooting and debugging

Best for:

  • Understanding search infrastructure
  • Optimizing search performance
  • Setting up production search clusters
  • Data backup and recovery

File size: ~1,250 lines | 28KB


4. Production Considerations (production.md)

Production-ready deployment strategies and best practices.

Contents:

  • Production architecture (multi-tier, multi-region)
  • Scaling strategies (vertical and horizontal)
  • Performance optimization (caching, connection pooling, async)
  • Security hardening (authentication, network security, secrets management)
  • Comprehensive monitoring and logging (ELK, Prometheus, Grafana)
  • Backup strategies and disaster recovery
  • High availability setup
  • Load balancing (Nginx, HAProxy)
  • Cost optimization
  • Complete deployment checklist

Best for:

  • Production deployments
  • High-traffic applications
  • Enterprise environments
  • Mission-critical systems

File size: ~1,300 lines | 30KB


Deployment Path Recommendations

For Developers

  1. Start with Local Deployment to understand the system
  2. Move to Docker Deployment for consistent environments
  3. Review OpenSearch Setup for search optimization

For DevOps Engineers

  1. Review Docker Deployment for containerization
  2. Study OpenSearch Setup for infrastructure
  3. Implement Production Considerations for deployment

For System Architects

  1. Read Production Considerations for architecture
  2. Reference OpenSearch Setup for cluster design
  3. Use Docker Deployment for orchestration

For Quick Start

  1. Follow Local Deployment to get running in 10 minutes
  2. Use Docker commands from Docker Deployment for single-command deployment

Key Features Across Documentation

Configuration Examples

All guides include:

  • Complete configuration files
  • Environment variable setups
  • Command-line examples
  • Code snippets

Troubleshooting

Comprehensive troubleshooting sections with:

  • Common issues and solutions
  • Debug commands
  • Error explanations
  • Performance tips

Security

Security guidance including:

  • SSL/TLS configuration
  • Authentication and authorization
  • Network security
  • Secrets management
  • Best practices

Monitoring

Monitoring setup with:

  • Health checks
  • Metrics collection
  • Logging configuration
  • Alerting setup

Quick Start Commands

Local Development

# Setup
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
# Edit .env with your GEMINI_API_KEY

# Start OpenSearch
docker run -d -p 9200:9200 -e "discovery.type=single-node" opensearchproject/opensearch:latest

# Run application
python main.py

Docker Deployment

# Start everything with Docker Compose
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

Production Deployment

See Production Considerations for complete production setup.


System Requirements

Minimum (Development)

  • CPU: 2 cores
  • RAM: 4GB
  • Disk: 10GB
  • OS: macOS, Linux, or Windows

Recommended (Production)

  • CPU: 4+ cores
  • RAM: 8GB+
  • Disk: 50GB+ SSD
  • OS: Linux (Ubuntu/CentOS)

Additional Resources

External Documentation

Project Documentation

  • Main README: ../../README.md
  • Project Guidelines: ../../CLAUDE.md
  • API Documentation: Coming soon
  • Architecture Diagrams: Coming soon

Support and Contribution

Getting Help

  1. Check the relevant guide's troubleshooting section
  2. Review logs: logs/research_assistant.log
  3. Search GitHub issues
  4. Create a new issue with:
    • Deployment method (local/docker/production)
    • Error messages
    • Configuration details
    • Steps to reproduce

Contributing

Contributions to improve deployment documentation are welcome:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

Documentation Updates

If you find:

  • Missing information
  • Outdated commands
  • Errors or typos
  • Opportunities for improvement

Please create an issue or submit a PR.


Version History

  • v1.0.0 (2025-10-02) - Initial comprehensive deployment documentation
    • Local deployment guide
    • Docker deployment guide
    • OpenSearch setup guide
    • Production considerations guide

License

This documentation is part of the Multi-Modal Academic Research System project.


Summary

Total documentation: 4,185 lines across 4 comprehensive guides covering every aspect of deploying the Multi-Modal Academic Research System from local development to enterprise-scale production.