dspy-skills

# DSPy Script for [COMPANY] Workflow Automation

```python
from dspy import DSPy

# Initialize DSPy with company-specific parameters
company_dspy = DSPy(
    company_name="[COMPANY]",
    industry="[INDUSTRY]",
    data_type="[DATA]",
    api_key="your_api_key_here"
)

# Define the workflow automation function
def automate_workflow(process_data):
    """
    Automates the [PROCESS] for [COMPANY]
    
    Args:
        process_data (dict): Dictionary containing the data to be processed
    
    Returns:
        dict: Processed data with additional insights
    """
    try:
        # Connect to existing Python workflows
        python_workflow = connect_to_python_workflow(process_data)
        
        # Optimize the workflow using DSPy
        optimized_workflow = company_dspy.optimize_workflow(python_workflow)
        
        # Log the process
        log_process("Workflow optimization completed", optimized_workflow)
        
        return optimized_workflow
    except Exception as e:
        log_process("Error in workflow automation", str(e))
        raise

# Example usage
example_data = {
    "input_data": ["sample1", "sample2", "sample3"]
}

result = automate_workflow(example_data)
print(result)
```

## Key Features
- **Automated Workflow**: Connects seamlessly with existing Python-based systems
- **Error Handling**: Includes robust error handling and logging
- **Optimization**: Uses DSPy to optimize the workflow for better performance
- **Industry-Specific**: Tailored for the [INDUSTRY] sector and [COMPANY]