use crate::{    PredictArgs, PredictionProvider,    example::{ActualCursor, Example, ExampleScore},    format_prompt::TeacherPrompt,    headless::EpAppState,    metrics,    parse_output::parse_prediction_output,    predict::run_prediction,    progress::{ExampleProgress, Step},    reversal_tracking,};use anyhow::Context as _;use gpui::AsyncApp;use serde::Serialize;use std::fs::File;use std::io::BufWriter;use std::path::Path;use std::sync::Arc;use zeta_prompt::udiff::{apply_diff_to_string, apply_diff_to_string_with_hunk_offset}; pub async fn run_scoring(    example: &mut Example,    args: &PredictArgs,    app_state: Arc<EpAppState>,    example_progress: &ExampleProgress,    cx: AsyncApp,) -> anyhow::Result<()> {    run_prediction(example, args, app_state, example_progress, cx).await?;     let progress = example_progress.start(Step::Score);     progress.set_substatus("applying patches");    let prompt_inputs = example        .prompt_inputs        .as_ref()        .context("prompt_inputs is required for scoring - run prediction first or ensure JSON includes prompt_inputs")?;    let original_text: &str = prompt_inputs.cursor_excerpt.as_ref();    let expected_patches_with_cursors = example.spec.expected_patches_with_cursor_positions();     let expected_texts: Vec<String> = expected_patches_with_cursors        .iter()        .map(|(patch, _)| {            apply_diff_to_string(patch, original_text)                .with_context(|| format!("Expected patch did not apply for {}", example.spec.name))        })        .collect::<Result<Vec<_>, _>>()?;     // For Teacher prompts, we need to extract the editable region to properly compute cursor offsets.    // The actual_cursor_offset from Teacher is relative to the editable region, while the expected    // cursor from the patch is relative to the hunk. We need to apply the patch to the editable    // region to find where the hunk matched, then compute the expected cursor position.    let old_editable_region = if let Some(p) = example.prompt.as_ref() {        if matches!(            p.provider,            PredictionProvider::Teacher(_) | PredictionProvider::TeacherNonBatching(_)        ) {            Some(                TeacherPrompt::extract_editable_region(&p.input)?                    .replace(TeacherPrompt::USER_CURSOR_MARKER, ""),            )        } else {            None        }    } else {        None    };     let zero_scores = ExampleScore {        delta_chr_f: 0.0,        delta_chr_f_true_positives: 0,        delta_chr_f_false_positives: 0,        delta_chr_f_false_negatives: 0,        delta_chr_f_precision: 0.0,        delta_chr_f_recall: 0.0,        delta_chr_f_beta: metrics::delta_chr_f_beta(),        braces_disbalance: 0,        exact_lines_tp: 0,        exact_lines_fp: 0,        exact_lines_fn: 0,        reversal_ratio: 0.0,        cursor_distance: None,        cursor_exact_match: None,        wrong_editable_region: None,        has_isolated_whitespace_changes: false,        inserted_tokens: 0,        deleted_tokens: 0,        kept_rate: None,        cumulative_logprob: None,        avg_logprob: None,    };     let cursor_path = example.spec.cursor_path.as_ref();     progress.set_substatus("computing metrics");    let mut scores = vec![];    for prediction in &example.predictions {        let actual_patch = prediction.actual_patch.clone().or_else(|| {            parse_prediction_output(example, &prediction.actual_output, prediction.provider)                .ok()                .map(|(patch, _)| patch)        });         let Some(actual_patch) = actual_patch else {            scores.push(zero_scores.clone());            continue;        };         let token_changes = metrics::count_patch_token_changes(&actual_patch);         let actual_text = match apply_diff_to_string(&actual_patch, original_text) {            Ok(text) => text,            Err(_) => {                let mut s = zero_scores.clone();                s.inserted_tokens = token_changes.inserted_tokens;                s.deleted_tokens = token_changes.deleted_tokens;                scores.push(s);                continue;            }        };         let mut best_delta_chr_f_metrics = metrics::DeltaChrFMetrics::default();        let mut best_expected_cursor: Option<usize> = None;        let mut best_patch_idx: Option<usize> = None;        let mut best_expected_text: Option<&str> = None;         for (idx, expected) in expected_texts.iter().enumerate() {            let delta_chr_f_metrics = metrics::delta_chr_f(original_text, expected, &actual_text);            if delta_chr_f_metrics.score > best_delta_chr_f_metrics.score {                best_delta_chr_f_metrics = delta_chr_f_metrics;                best_patch_idx = Some(idx);                best_expected_text = Some(expected);            }        }         if let Some(idx) = best_patch_idx {            // Get the raw cursor offset from the expected patch (relative to hunk new text)            let expected_cursor_in_patch = expected_patches_with_cursors                .get(idx)                .and_then(|(_, cursor)| *cursor);             // For Teacher prompts, we need to apply the patch to the editable region            // to find where the hunk matched, then compute the actual cursor position            if let (Some(editable_region), Some(cursor_in_patch)) =                (&old_editable_region, expected_cursor_in_patch)            {                let (patch, _) = &expected_patches_with_cursors[idx];                if let Ok((_, hunk_offset)) =                    apply_diff_to_string_with_hunk_offset(patch, editable_region)                {                    let hunk_start = hunk_offset.unwrap_or(0);                    best_expected_cursor = Some(hunk_start + cursor_in_patch);                }            } else {                // For non-Teacher prompts or if we can't compute, use raw offset                best_expected_cursor = expected_cursor_in_patch;            }        }         let disbalance_before = metrics::braces_disbalance(&original_text);        let disbalance_after = metrics::braces_disbalance(&actual_text);        let braces_disbalance = disbalance_after.saturating_sub(disbalance_before);         // Compute exact lines match against best matching expected patch        let best_exact_lines = expected_patches_with_cursors            .iter()            .map(|(expected_patch, _)| metrics::exact_lines_match(expected_patch, &actual_patch))            .max_by_key(|m| m.true_positives)            .unwrap_or_default();         // Compute reversal ratio        let reversal_ratio = reversal_tracking::compute_prediction_reversal_ratio(            prompt_inputs,            &actual_text,            cursor_path,        );         // Compute cursor position metrics        let (cursor_distance, cursor_exact_match) =            compute_cursor_metrics(best_expected_cursor, prediction.actual_cursor.as_ref());         // Compute approximation of editable region correctness        let wrong_editable_region = Some(!metrics::is_editable_region_correct(&actual_patch));         // Check for isolated whitespace changes.        let has_isolated_whitespace_changes = metrics::has_isolated_whitespace_changes(            &actual_patch,            prediction.actual_cursor.as_ref(),        );         let kept_rate = best_expected_text.map(|final_text| {            metrics::compute_kept_rate(original_text, &actual_text, final_text).kept_rate        });         scores.push(ExampleScore {            delta_chr_f: best_delta_chr_f_metrics.score as f32,            delta_chr_f_true_positives: best_delta_chr_f_metrics.counts.true_positives,            delta_chr_f_false_positives: best_delta_chr_f_metrics.counts.false_positives,            delta_chr_f_false_negatives: best_delta_chr_f_metrics.counts.false_negatives,            delta_chr_f_precision: best_delta_chr_f_metrics.precision,            delta_chr_f_recall: best_delta_chr_f_metrics.recall,            delta_chr_f_beta: best_delta_chr_f_metrics.beta,            braces_disbalance,            exact_lines_tp: best_exact_lines.true_positives,            exact_lines_fp: best_exact_lines.false_positives,            exact_lines_fn: best_exact_lines.false_negatives,            reversal_ratio,            cursor_distance,            cursor_exact_match,            wrong_editable_region,            has_isolated_whitespace_changes,            inserted_tokens: token_changes.inserted_tokens,            deleted_tokens: token_changes.deleted_tokens,            kept_rate,            cumulative_logprob: prediction.cumulative_logprob,            avg_logprob: prediction.avg_logprob,        });    }     example.score = scores;    Ok(())} fn compute_cursor_metrics(    expected_cursor_editable_region_offset: Option<usize>,    actual_cursor: Option<&ActualCursor>,) -> (Option<usize>, Option<bool>) {    match (expected_cursor_editable_region_offset, actual_cursor) {        (Some(expected), Some(actual)) => {            let distance = expected.abs_diff(actual.editable_region_offset.unwrap_or_default());            let exact_match = distance == 0;            (Some(distance), Some(exact_match))        }        (None, None) => {            // Neither has cursor position - skip cursor scoring            (None, None)        }        (Some(_), None) | (None, Some(_)) => {            // Only one has cursor position - count as miss            (None, Some(false))        }    }} pub fn print_report(examples: &[Example], verbose: bool) {    const MAX_EXAMPLES_DEFAULT: usize = 20;    use crate::metrics::ClassificationMetrics;     const LINE_WIDTH: usize = 101;    let separator = "─".repeat(LINE_WIDTH);     println!("{}", separator);    println!(        "{:<40} {:>8} {:>5} {:>7} {:>7} {:>7} {:>7} {:>6} {:>5}",        "Example", "DeltaChrF", "Brace", "F1", "Revert", "QaRev", "QaConf", "Cursor", "WrgER"    );    println!("{}", separator);     let mut all_delta_chr_f_scores = Vec::new();    let mut all_reversal_ratios = Vec::new();    let mut braces_disbalance_sum: usize = 0;    let mut total_delta_chr_f = ClassificationMetrics::default();    let mut total_delta_chr_f_precision = 0.0;    let mut total_delta_chr_f_recall = 0.0;    let mut delta_chr_f_beta = 0.0;    let mut total_exact_lines = ClassificationMetrics::default();    let mut total_scores: usize = 0;    let mut qa_reverts_count: usize = 0;    let mut qa_reverts_total: usize = 0;    let mut qa_confidence_sum: u64 = 0;    let mut qa_confidence_count: usize = 0;    let mut cursor_exact_matches: usize = 0;    let mut cursor_total: usize = 0;    let mut cursor_distance_sum: usize = 0;    let mut cursor_distance_count: usize = 0;    let mut wrong_editable_region_count: usize = 0;    let mut wrong_editable_region_total: usize = 0;    let mut isolated_whitespace_count: usize = 0;    let mut kept_rate_sum: f64 = 0.0;    let mut kept_rate_count: usize = 0;    let mut patch_inserted_tokens: Vec<usize> = Vec::new();    let mut patch_deleted_tokens: Vec<usize> = Vec::new();    let mut predictions_with_patch: usize = 0;     let mut printed_lines: usize = 0;    let mut skipped_lines: usize = 0;     for example in examples {        for (score_idx, score) in example.score.iter().enumerate() {            let exact_lines = score.exact_lines_counts();             // Get QA results for this prediction if available            let qa_result = example.qa.get(score_idx).and_then(|q| q.as_ref());            let qa_reverts_str = qa_result                .and_then(|q| q.reverts_edits)                .map(|v| if v { "yes" } else { "no" })                .unwrap_or("-");            let qa_conf_str = qa_result                .and_then(|q| q.confidence)                .map(|v| format!("{}", v))                .unwrap_or("-".to_string());             // Format wrong editable region metric            let wrong_er_str = match score.wrong_editable_region {                Some(true) => "✗",                Some(false) => "",                None => "",            };             // Format cursor metric            let cursor_str = match (score.cursor_exact_match, score.cursor_distance) {                (Some(true), _) => "✓".to_string(),                (Some(false), Some(dist)) => format!("±{}", dist),                (Some(false), None) => "✗".to_string(),                (None, _) => "-".to_string(),            };             if verbose || printed_lines < MAX_EXAMPLES_DEFAULT {                println!(                    "{:<40} {:>8.2} {:>5} {:>6.1}% {:>6.1}% {:>7} {:>7} {:>6} {:>5}",                    truncate_name(&example.spec.name, 40),                    score.delta_chr_f,                    score.braces_disbalance,                    exact_lines.f1() * 100.0,                    score.reversal_ratio * 100.0,                    qa_reverts_str,                    qa_conf_str,                    cursor_str,                    wrong_er_str                );                printed_lines += 1;            } else {                skipped_lines += 1;            }             all_delta_chr_f_scores.push(score.delta_chr_f);            all_reversal_ratios.push(score.reversal_ratio);            total_scores += 1;            braces_disbalance_sum += score.braces_disbalance;            total_delta_chr_f.accumulate(&score.delta_chr_f_counts());            total_delta_chr_f_precision += score.delta_chr_f_precision;            total_delta_chr_f_recall += score.delta_chr_f_recall;            delta_chr_f_beta = score.delta_chr_f_beta;            total_exact_lines.accumulate(&score.exact_lines_counts());             // Accumulate QA metrics            if let Some(qa) = qa_result {                if let Some(reverts) = qa.reverts_edits {                    qa_reverts_total += 1;                    if reverts {                        qa_reverts_count += 1;                    }                }                if let Some(conf) = qa.confidence {                    qa_confidence_sum += conf as u64;                    qa_confidence_count += 1;                }            }             // Accumulate wrong editable region metrics            if let Some(wrong) = score.wrong_editable_region {                wrong_editable_region_total += 1;                if wrong {                    wrong_editable_region_count += 1;                }            }             // Accumulate isolated whitespace metrics            if score.has_isolated_whitespace_changes {                isolated_whitespace_count += 1;            }             // Accumulate kept rate metrics            if let Some(kr) = score.kept_rate {                kept_rate_sum += kr;                kept_rate_count += 1;            }             // Accumulate token change metrics (only for predictions that produced a patch)            let has_patch = example                .predictions                .get(score_idx)                .and_then(|p| p.actual_patch.as_ref())                .is_some_and(|p| !p.is_empty());            if has_patch {                predictions_with_patch += 1;                patch_inserted_tokens.push(score.inserted_tokens);                patch_deleted_tokens.push(score.deleted_tokens);            }             // Accumulate cursor metrics            if let Some(exact_match) = score.cursor_exact_match {                cursor_total += 1;                if exact_match {                    cursor_exact_matches += 1;                }            }            if let Some(dist) = score.cursor_distance {                cursor_distance_sum += dist;                cursor_distance_count += 1;            }        }    }     if skipped_lines > 0 {        println!(            "{:<40} (use --verbose to see all {} examples)",            format!("... and {} more", skipped_lines),            printed_lines + skipped_lines        );    }    println!("{}", separator);     if !all_delta_chr_f_scores.is_empty() {        let avg_delta_chr_f: f32 =            all_delta_chr_f_scores.iter().sum::<f32>() / all_delta_chr_f_scores.len() as f32;        let avg_reversal_ratio: f32 =            all_reversal_ratios.iter().sum::<f32>() / all_reversal_ratios.len() as f32;        let braces_disbalance_avg: f32 = braces_disbalance_sum as f32 / total_scores as f32;         let qa_reverts_str = if qa_reverts_total > 0 {            format!(                "{:.1}%",                qa_reverts_count as f32 / qa_reverts_total as f32 * 100.0            )        } else {            "-".to_string()        };        let qa_conf_str = if qa_confidence_count > 0 {            format!(                "{:.1}",                qa_confidence_sum as f32 / qa_confidence_count as f32            )        } else {            "-".to_string()        };        let cursor_str = if cursor_total > 0 {            format!(                "{:.0}%",                cursor_exact_matches as f32 / cursor_total as f32 * 100.0            )        } else {            "-".to_string()        };        let wrong_er_str = if wrong_editable_region_total > 0 {            format!(                "{:.2}%",                wrong_editable_region_count as f32 / wrong_editable_region_total as f32 * 100.0            )        } else {            "-".to_string()        };        let isolated_ws_str = if total_scores > 0 {            format!(                "{}/{} ({:.1}%)",                isolated_whitespace_count,                total_scores,                isolated_whitespace_count as f32 / total_scores as f32 * 100.0            )        } else {            "-".to_string()        };        let avg_cursor_distance = if cursor_distance_count > 0 {            Some(cursor_distance_sum as f32 / cursor_distance_count as f32)        } else {            None        };         println!(            "{:<40} {:>8.2} {:>5.1} {:>6.1}% {:>6.1}% {:>7} {:>7} {:>6} {:>5}",            "TOTAL / AVERAGE",            avg_delta_chr_f,            braces_disbalance_avg,            total_exact_lines.f1() * 100.0,            avg_reversal_ratio * 100.0,            qa_reverts_str,            qa_conf_str,            cursor_str,            wrong_er_str        );        println!("{}", separator);        println!(            "Delta chrF (β={:.1}): TP={}, FP={}, FN={}, P={:.1}%, R={:.1}%",            delta_chr_f_beta,            total_delta_chr_f.true_positives,            total_delta_chr_f.false_positives,            total_delta_chr_f.false_negatives,            total_delta_chr_f_precision / total_scores as f64 * 100.0,            total_delta_chr_f_recall / total_scores as f64 * 100.0        );         // Print additional cursor metrics if available        if let Some(avg_dist) = avg_cursor_distance {            println!(                "Cursor: {}/{} exact matches ({:.0}%), avg distance: {:.1} bytes",                cursor_exact_matches,                cursor_total,                cursor_exact_matches as f32 / cursor_total as f32 * 100.0,                avg_dist            );        }

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