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Development Guide

Deployment Options

Export Process

  1. Navigate to File > Export As > Python Code

  2. Select export location

  3. Configure export settings

interface ExportConfig {
    format: 'python' | 'notebook';
    includeComments: boolean;
    environmentSetup: boolean;
}

Deployment Methods

Cloud Deployment

Enterprise-grade deployment with managed infrastructure.

# Contact enterprise@dotbase.ai for:
FEATURES = {
    "managed_infrastructure": True,
    "auto_scaling": True,
    "monitoring": True,
    "enterprise_support": True
}

Local Deployment

Prerequisites

# Using pip
pip install pyautogen==0.2.7

# Using conda
conda install pyautogen==0.2.7

# Using poetry
poetry add pyautogen==0.2.7

Environment Setup

# requirements.txt
pyautogen==0.2.7
python-dotenv>=0.19.0

Replit Deployment

Setup Steps

  1. Create Python project

  2. Import source code

  3. Configure dependencies:

# pyproject.toml
[tool.poetry.dependencies]
python = "^3.9"
pyautogen = "0.2.7"

Execution Configuration

execution_config = {
    "environment": {
        "API_KEY": "your_api_key",
        "PYTHONPATH": "${workspaceFolder}"
    },
    "runtime": {
        "memory_limit": "4G",
        "timeout": 3600
    }
}

Best Practices

Local Development

  • Use virtual environments

  • Maintain API key security

  • Enable error logging

  • Monitor resource usage

Production Deployment

  • Implement error handling

  • Set up monitoring

  • Configure auto-scaling

  • Manage API rate limits

Troubleshooting

Issue
Resolution

Import Errors

Verify package installation

API Key Issues

Check environment variables

Memory Errors

Adjust resource limits

Timeout Issues

Configure execution timeouts

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