rustchain-community 1.0.0

// Agent Reinforcement Training - Training Pipeline Module
use crate::core::Result;

#[derive(Debug, Clone)]
pub struct TrainingConfig {
    pub batch_size: usize,
    pub learning_rate: f32,
    pub epochs: usize,
}

impl Default for TrainingConfig {
    fn default() -> Self {
        Self {
            batch_size: 32,
            learning_rate: 0.001,
            epochs: 10,
        }
    }
}

pub fn add_trajectory(_config: &TrainingConfig) -> Result<()> {
    // Placeholder implementation for enterprise feature
    Ok(())
}

pub fn start_training_run(_config: &TrainingConfig) -> Result<()> {
    // Placeholder implementation for enterprise feature
    Ok(())
}

pub fn trajectory_to_training_example(_config: &TrainingConfig) -> Result<String> {
    // Placeholder implementation for enterprise feature
    Ok("training_example".to_string())
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_add_trajectory() {
        let config = TrainingConfig::default();
        let result = add_trajectory(&config);
        assert!(result.is_ok());
    }

    #[test]
    fn test_start_training_run() {
        let config = TrainingConfig::default();
        let result = start_training_run(&config);
        assert!(result.is_ok());
    }

    #[test]
    fn test_trajectory_to_training_example() {
        let config = TrainingConfig::default();
        let result = trajectory_to_training_example(&config);
        assert!(result.is_ok());
        assert_eq!(result.unwrap(), "training_example");
    }

    #[test]
    fn test_training_config_default() {
        let config = TrainingConfig::default();
        assert_eq!(config.batch_size, 32);
        assert_eq!(config.learning_rate, 0.001);
        assert_eq!(config.epochs, 10);
    }
}