//! Built-in seed examples for DADOES smoke tests and domain augmentation.

use crate::{
    LinearMoodModel, ModelError, Mood, OwnedTrainingExample, TrainConfig, TrainingExample,
};

/// Returns the seed examples used by the first DADOES baseline.
#[must_use]
pub fn seed_training_examples() -> &'static [TrainingExample<'static>] {
    &SEED_TRAINING_EXAMPLES
}

/// Trains the built-in seed model.
pub fn train_seed_model() -> Result<LinearMoodModel, ModelError> {
    LinearMoodModel::train(seed_training_examples(), TrainConfig::default())
}

/// Returns owned seed examples with full DADOES label supervision.
pub fn owned_seed_training_examples() -> Result<Vec<OwnedTrainingExample>, ModelError> {
    seed_training_examples()
        .iter()
        .map(|example| OwnedTrainingExample::new(example.text.to_owned(), example.labels.to_vec()))
        .collect()
}

const SEED_TRAINING_EXAMPLES: [TrainingExample<'static>; 32] = [
    TrainingExample {
        text: "I finished the shelter and felt happy with the quiet progress.",
        labels: &[Mood::Happy, Mood::Satisfied],
    },
    TrainingExample {
        text: "The plan worked exactly as I hoped, and I feel satisfied tonight.",
        labels: &[Mood::Satisfied],
    },
    TrainingExample {
        text: "I found a bright new cave and I am excited to explore it tomorrow.",
        labels: &[Mood::Excited, Mood::Curious],
    },
    TrainingExample {
        text: "The strange signal beyond the ridge made me curious.",
        labels: &[Mood::Curious],
    },
    TrainingExample {
        text: "The storm trapped me outside and I felt anxious until I reached camp.",
        labels: &[Mood::Anxious],
    },
    TrainingExample {
        text: "I kept failing to craft the tool, and the repeated mistake was frustrating.",
        labels: &[Mood::Frustrated],
    },
    TrainingExample {
        text: "I lost the garden today and felt sad watching the work disappear.",
        labels: &[Mood::Sad],
    },
    TrainingExample {
        text: "The broken promise made me angry for the rest of the evening.",
        labels: &[Mood::Angry],
    },
    TrainingExample {
        text: "No one visited the camp, and I felt lonely after sunset.",
        labels: &[Mood::Lonely],
    },
    TrainingExample {
        text: "Sorting the same stones all day left me bored and restless.",
        labels: &[Mood::Bored],
    },
    TrainingExample {
        text: "My legs ached after hauling timber, and I am tired now.",
        labels: &[Mood::Tired],
    },
    TrainingExample {
        text: "The first green shoots appeared, so I feel hopeful about the harvest.",
        labels: &[Mood::Hopeful],
    },
    TrainingExample {
        text: "I repaired the fence, counted supplies, and ended the day neutral.",
        labels: &[Mood::Neutral],
    },
    TrainingExample {
        text: "I was not happy with the failed bridge repair.",
        labels: &[Mood::Frustrated, Mood::Sad],
    },
    TrainingExample {
        text: "A narrow escape from the wolves left me anxious and tired.",
        labels: &[Mood::Anxious, Mood::Tired],
    },
    TrainingExample {
        text: "I finally solved the lock, and the success made me excited and satisfied.",
        labels: &[Mood::Excited, Mood::Satisfied],
    },
    TrainingExample {
        text: "The empty road made the world feel lonely and quiet.",
        labels: &[Mood::Lonely, Mood::Sad],
    },
    TrainingExample {
        text: "Another day of waiting with no news made me bored.",
        labels: &[Mood::Bored],
    },
    TrainingExample {
        text: "I still believe the missing map can be found, and that feels hopeful.",
        labels: &[Mood::Hopeful],
    },
    TrainingExample {
        text: "The new footprints near the river made me curious and a little anxious.",
        labels: &[Mood::Curious, Mood::Anxious],
    },
    TrainingExample {
        text: "I argued with the trader and walked away angry.",
        labels: &[Mood::Angry],
    },
    TrainingExample {
        text: "The meal was warm, the roof held, and I felt happy.",
        labels: &[Mood::Happy, Mood::Satisfied],
    },
    TrainingExample {
        text: "I tried the same route again and again until I felt frustrated.",
        labels: &[Mood::Frustrated, Mood::Tired],
    },
    TrainingExample {
        text: "The day passed without danger or surprise.",
        labels: &[Mood::Neutral],
    },
    TrainingExample {
        text: "I am exhausted after digging, carrying, and repairing since dawn.",
        labels: &[Mood::Tired],
    },
    TrainingExample {
        text: "I discovered a hidden room and cannot wait to return.",
        labels: &[Mood::Excited, Mood::Curious],
    },
    TrainingExample {
        text: "The ruined notebook reminded me of everything I lost.",
        labels: &[Mood::Sad],
    },
    TrainingExample {
        text: "The path is difficult, but tomorrow still looks possible.",
        labels: &[Mood::Hopeful],
    },
    TrainingExample {
        text: "I failed at the bridge again and felt frustrated and exhausted tonight.",
        labels: &[Mood::Frustrated, Mood::Tired],
    },
    TrainingExample {
        text: "Another failed repair left me exhausted, blocked, and frustrated.",
        labels: &[Mood::Frustrated, Mood::Tired],
    },
    TrainingExample {
        text: "The work succeeded, and I felt satisfied instead of frustrated.",
        labels: &[Mood::Satisfied],
    },
    TrainingExample {
        text: "Nothing went wrong today, but nothing felt especially meaningful either.",
        labels: &[Mood::Neutral],
    },
];

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

    #[test]
    fn seed_model_detects_frustrated_report() {
        let model = train_seed_model();
        assert!(model.is_ok());

        if let Ok(model) = model {
            let analysis = model.classify(
                "I failed at the bridge again and felt frustrated and exhausted tonight.",
            );
            let active: Vec<Mood> = analysis
                .active_moods(0.35)
                .map(|score| score.mood)
                .collect();
            assert!(active.contains(&Mood::Frustrated));
        }
    }

    #[test]
    fn seed_model_detects_curious_report() {
        let model = train_seed_model();
        assert!(model.is_ok());

        if let Ok(model) = model {
            let analysis =
                model.classify("The strange footprints made me curious about the river path.");
            let primary = analysis.primary_mood();
            assert!(primary.is_some());

            if let Some(primary) = primary {
                assert_eq!(primary.mood, Mood::Curious);
            }
        }
    }
}