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DependencyGraphLearnModel

Struct DependencyGraphLearnModel 

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pub struct DependencyGraphLearnModel {
    pub system_prompt: String,
}
Expand description

DependencyGraph 推論の学習モデル

DependencyGraph 推論の prompt/response を評価し、TrainingData に変換する。

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§system_prompt: String

システムプロンプト

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impl DependencyGraphLearnModel

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pub fn new() -> Self

新しい DependencyGraphLearnModel を作成

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pub fn with_system_prompt(self, prompt: impl Into<String>) -> Self

システムプロンプトを設定

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pub fn default_system_prompt() -> &'static str

デフォルトのシステムプロンプト

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pub fn extractor() -> impl Fn(&Episode) -> Option<(String, String)>

Episode から (prompt, response) を抽出する extractor

DpoLearnModel と組み合わせて使用する。

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impl Default for DependencyGraphLearnModel

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fn default() -> Self

Returns the “default value” for a type. Read more
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impl LearnModel for DependencyGraphLearnModel

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fn build_episodes(&self, records: &[Record]) -> Vec<Episode>

DependencyGraphRecord から Episode を生成

§旧 runner.rs のロジック(参考)
// runner.rs:680-738 で行っていた処理:

let scenario_key = self.scenario.meta.id.learning_key();
let ticks = result.total_ticks as u32;
let max_ticks = self.scenario.app_config.max_ticks as u32;

// Outcome 計算
let outcome = if environment_done {
    let score = 1.0 - (ticks as f64 / max_ticks as f64).min(1.0);
    Outcome::success(score.max(0.01))
} else if timed_out {
    let partial_score = (ticks as f64 / max_ticks as f64).min(0.99);
    Outcome::timeout(Some(partial_score))
} else {
    Outcome::failure(format!("Task not completed at tick {}", ticks))
};

// Episode 構築
let context = EpisodeContext::new().with_record(record);
let episode = Episode::builder()
    .learn_model("dependency_graph")
    .context(context)
    .outcome(outcome)
    .scenario(&scenario_key)
    .build();

// JSONL 保存
let path = store.storage().base_dir().join(format!(
    "scenarios/{}/dep_graph_episodes.jsonl", scenario_key
));
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fn name(&self) -> &str

名前
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fn objective(&self) -> &str

目的を表す説明
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fn evaluate(&self, context: &EpisodeContext) -> Outcome

Records から Success/Failure を判定 Read more
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fn convert(&self, episode: &Episode) -> Result<TrainingData, LearnError>

Episode を TrainingData に変換
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fn convert_batch(&self, episodes: &[Episode]) -> Vec<TrainingData>

複数 Episode を一括変換(デフォルト実装)
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fn build_episodes_from_actions(&self, actions: &[ActionEvent]) -> Vec<Episode>

便利メソッド: ActionEvent[] から直接変換

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