Function execute_with_client 

pub async fn execute_with_client(
    args: MatchArgs,
    ai_client: Box<dyn AIProvider>,
    config: &Config,
) -> Result<()>

Execute the matching workflow with dependency-injected AI client.

This function implements the core matching logic while accepting an AI client as a parameter, enabling dependency injection for testing and allowing different AI provider implementations to be used.

Architecture Benefits

• Testability: Mock AI clients can be injected for unit testing
• Flexibility: Different AI providers can be used without code changes
• Isolation: Core logic is independent of AI client implementation
• Reusability: Function can be called with custom AI configurations

Matching Process

1. Configuration Setup: Load matching parameters and thresholds
2. Engine Initialization: Create matching engine with AI client
3. File Discovery: Scan for video and subtitle files
4. Content Analysis: Extract and analyze subtitle content
5. AI Matching: Send content to AI service for correlation analysis
6. Result Processing: Evaluate confidence and generate operations
7. Operation Execution: Apply file changes or save dry-run results

Dry-run vs Live Mode

Dry-run Mode (args.dry_run = true)

• No actual file modifications are performed
• Results are cached for potential later application
• Operations are displayed for user review
• Safe for testing and verification

Live Mode (args.dry_run = false)

• File operations are actually executed
• Backups are created if enabled
• Changes are applied atomically where possible
• Progress is tracked and displayed

Arguments

• args - Command-line arguments with matching configuration
• ai_client - AI provider implementation for content analysis

Returns

Returns Ok(()) on successful completion or an error describing the failure point in the matching workflow.

Error Handling

The function provides comprehensive error handling:

• Early Validation: Configuration and argument validation
• Graceful Degradation: Partial completion when possible
• Clear Messaging: Descriptive error messages for user guidance
• State Preservation: No partial file modifications on errors

Caching Strategy

• AI Results: Cached to reduce API costs and improve performance
• Content Analysis: Subtitle parsing results cached per file
• Match Results: Dry-run results saved for later application
• Configuration: Processed configuration cached for efficiency

Examples

use subx_cli::commands::match_command;
use subx_cli::cli::MatchArgs;
use subx_cli::services::ai::MockAIClient;
use std::path::PathBuf;

// Testing with mock AI client
let mock_client = Box::new(MockAIClient::new());
let args = MatchArgs {
    path: PathBuf::from("./test_data"),
    recursive: false,
    dry_run: true,
    confidence: 90,
    backup: false,
};

match_command::execute_with_client(args, mock_client, &config).await?;