# Development Guide
## Deployment Options
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## 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 |