42583c1141
Release Notes: - N/A --------- Co-authored-by: Agus Zubiaga <agus@zed.dev> Co-authored-by: Ben Kunkle <ben@zed.dev>
642 lines
20 KiB
Rust
642 lines
20 KiB
Rust
use crate::metrics::{self, Scores};
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use std::{
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collections::HashMap,
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io::{IsTerminal, Write},
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sync::Arc,
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};
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use anyhow::Result;
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use edit_prediction::{EditPredictionStore, udiff::DiffLine};
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use gpui::{AsyncApp, Entity};
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use project::Project;
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use util::ResultExt as _;
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use crate::{
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EvaluateArguments, PredictionOptions,
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example::{Example, NamedExample},
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headless::ZetaCliAppState,
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paths::print_run_data_dir,
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predict::{PredictionDetails, perform_predict, setup_store},
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};
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#[derive(Debug)]
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pub(crate) struct ExecutionData {
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execution_id: String,
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diff: String,
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reasoning: String,
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}
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pub async fn run_evaluate(
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args: EvaluateArguments,
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app_state: &Arc<ZetaCliAppState>,
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cx: &mut AsyncApp,
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) {
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if args.example_paths.is_empty() {
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eprintln!("No examples provided");
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return;
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}
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let all_tasks = args.example_paths.into_iter().map(|path| {
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let options = args.options.clone();
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let app_state = app_state.clone();
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let example = NamedExample::load(&path).expect("Failed to load example");
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cx.spawn(async move |cx| {
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let project = example.setup_project(&app_state, cx).await.unwrap();
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let providers = (0..args.repetitions)
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.map(|_| setup_store(args.options.provider, &project, &app_state, cx).unwrap())
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.collect::<Vec<_>>();
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let _edited_buffers = example.apply_edit_history(&project, cx).await.unwrap();
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let tasks = providers
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.into_iter()
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.enumerate()
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.map(move |(repetition_ix, store)| {
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let repetition_ix = (args.repetitions > 1).then(|| repetition_ix as u16);
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let example = example.clone();
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let project = project.clone();
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let options = options.clone();
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cx.spawn(async move |cx| {
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let name = example.name.clone();
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run_evaluate_one(
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example,
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repetition_ix,
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project,
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store,
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options,
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!args.skip_prediction,
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cx,
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)
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.await
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.map_err(|err| (err, name, repetition_ix))
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})
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});
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futures::future::join_all(tasks).await
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})
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});
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let all_results = futures::future::join_all(all_tasks).await;
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write_aggregated_scores(&mut std::io::stdout(), &all_results).unwrap();
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if let Some(mut output_file) =
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std::fs::File::create(crate::paths::RUN_DIR.join("aggregated_results.md")).log_err()
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{
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write_aggregated_scores(&mut output_file, &all_results).log_err();
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};
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if args.repetitions > 1 {
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if let Err(e) = write_bucketed_analysis(&all_results) {
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eprintln!("Failed to write bucketed analysis: {:?}", e);
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}
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}
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print_run_data_dir(args.repetitions == 1, std::io::stdout().is_terminal());
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}
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fn write_aggregated_scores(
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w: &mut impl std::io::Write,
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all_results: &Vec<
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Vec<Result<(EvaluationResult, ExecutionData), (anyhow::Error, String, Option<u16>)>>,
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>,
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) -> Result<()> {
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let mut successful = Vec::new();
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let mut failed_count = 0;
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for result in all_results.iter().flatten() {
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match result {
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Ok((eval_result, _execution_data)) => successful.push(eval_result),
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Err((err, name, repetition_ix)) => {
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if failed_count == 0 {
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writeln!(w, "## Errors\n")?;
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}
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failed_count += 1;
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writeln!(w, "{}", fmt_evaluation_error(err, name, repetition_ix))?;
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}
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}
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}
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if successful.len() > 1 {
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let edit_scores = successful
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.iter()
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.filter_map(|r| r.edit_scores.clone())
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.collect::<Vec<_>>();
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let has_edit_predictions = edit_scores.len() > 0;
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let aggregated_result = EvaluationResult {
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context_scores: Scores::aggregate(successful.iter().map(|r| &r.context_scores)),
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edit_scores: has_edit_predictions.then(|| EditScores::aggregate(&edit_scores)),
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prompt_len: successful.iter().map(|r| r.prompt_len).sum::<usize>() / successful.len(),
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generated_len: successful.iter().map(|r| r.generated_len).sum::<usize>()
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/ successful.len(),
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};
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writeln!(w, "\n{}", "-".repeat(80))?;
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writeln!(w, "\n## TOTAL SCORES")?;
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writeln!(w, "{:#}", aggregated_result)?;
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}
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if successful.len() + failed_count > 1 {
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writeln!(
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w,
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"\nCongratulations! {}/{} ({:.2}%) of runs weren't outright failures 🎉",
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successful.len(),
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successful.len() + failed_count,
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(successful.len() as f64 / (successful.len() + failed_count) as f64) * 100.0
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)?;
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}
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Ok(())
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}
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pub async fn run_evaluate_one(
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example: NamedExample,
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repetition_ix: Option<u16>,
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project: Entity<Project>,
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store: Entity<EditPredictionStore>,
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prediction_options: PredictionOptions,
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predict: bool,
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cx: &mut AsyncApp,
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) -> Result<(EvaluationResult, ExecutionData)> {
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let predict_result = perform_predict(
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example.clone(),
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project,
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store,
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repetition_ix,
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prediction_options,
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cx,
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)
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.await?;
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let evaluation_result = evaluate(&example.example, &predict_result, predict);
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if repetition_ix.is_none() {
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write_eval_result(
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&example,
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&predict_result,
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&evaluation_result,
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&mut std::io::stdout(),
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std::io::stdout().is_terminal(),
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predict,
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)?;
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}
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if let Some(mut results_file) =
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std::fs::File::create(predict_result.run_example_dir.join("results.md")).log_err()
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{
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write_eval_result(
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&example,
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&predict_result,
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&evaluation_result,
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&mut results_file,
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false,
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predict,
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)
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.log_err();
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}
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let execution_data = ExecutionData {
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execution_id: if let Some(rep_ix) = repetition_ix {
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format!("{:03}", rep_ix)
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} else {
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example.name.clone()
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},
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diff: predict_result.diff.clone(),
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reasoning: std::fs::read_to_string(
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predict_result
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.run_example_dir
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.join("prediction_response.md"),
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)
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.unwrap_or_default(),
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};
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anyhow::Ok((evaluation_result, execution_data))
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}
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fn write_eval_result(
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example: &NamedExample,
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predictions: &PredictionDetails,
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evaluation_result: &EvaluationResult,
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out: &mut impl Write,
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use_color: bool,
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predict: bool,
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) -> Result<()> {
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if predict {
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writeln!(
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out,
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"## Expected edit prediction:\n\n```diff\n{}\n```\n",
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compare_diffs(
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&example.example.expected_patch,
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&predictions.diff,
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use_color
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)
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)?;
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writeln!(
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out,
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"## Actual edit prediction:\n\n```diff\n{}\n```\n",
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compare_diffs(
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&predictions.diff,
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&example.example.expected_patch,
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use_color
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)
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)?;
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}
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writeln!(out, "{:#}", evaluation_result)?;
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anyhow::Ok(())
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}
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#[derive(Debug, Default, Clone)]
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pub struct EditScores {
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pub line_match: Scores,
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pub chr_f: f64,
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}
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impl EditScores {
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pub fn aggregate(scores: &[EditScores]) -> EditScores {
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let line_match = Scores::aggregate(scores.iter().map(|s| &s.line_match));
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let chr_f = scores.iter().map(|s| s.chr_f).sum::<f64>() / scores.len() as f64;
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EditScores { line_match, chr_f }
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}
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}
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#[derive(Debug, Default)]
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pub struct EvaluationResult {
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pub edit_scores: Option<EditScores>,
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pub context_scores: Scores,
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pub prompt_len: usize,
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pub generated_len: usize,
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}
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impl std::fmt::Display for EvaluationResult {
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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if f.alternate() {
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self.fmt_table(f)
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} else {
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self.fmt_markdown(f)
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}
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}
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}
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impl EvaluationResult {
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fn fmt_markdown(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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write!(
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f,
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r#"
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### Context Scores
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{}
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"#,
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self.context_scores.to_markdown(),
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)?;
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if let Some(scores) = &self.edit_scores {
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write!(
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f,
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r#"
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### Edit Prediction Scores
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{}"#,
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scores.line_match.to_markdown()
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)?;
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}
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Ok(())
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}
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fn fmt_table(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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writeln!(f, "#### Prompt Statistics")?;
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writeln!(f, "─────────────────────────")?;
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writeln!(f, "Prompt_len Generated_len")?;
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writeln!(f, "─────────────────────────")?;
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writeln!(f, "{:<11} {:<14}", self.prompt_len, self.generated_len,)?;
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writeln!(f)?;
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writeln!(f)?;
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writeln!(f, "#### Performance Scores")?;
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writeln!(
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f,
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"──────────────────────────────────────────────────────────────────"
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)?;
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writeln!(
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f,
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" TP FP FN Precision Recall F1"
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)?;
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writeln!(
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f,
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"──────────────────────────────────────────────────────────────────"
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)?;
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writeln!(
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f,
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"Context Retrieval {:<6} {:<6} {:<6} {:>8.2} {:>7.2} {:>6.2}",
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self.context_scores.true_positives,
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self.context_scores.false_positives,
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self.context_scores.false_negatives,
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self.context_scores.precision() * 100.0,
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self.context_scores.recall() * 100.0,
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self.context_scores.f1_score() * 100.0
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)?;
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if let Some(edit_scores) = &self.edit_scores {
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let line_match = &edit_scores.line_match;
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writeln!(f, "Edit Prediction")?;
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writeln!(
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f,
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" ├─ exact lines {:<6} {:<6} {:<6} {:>8.2} {:>7.2} {:>6.2}",
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line_match.true_positives,
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line_match.false_positives,
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line_match.false_negatives,
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line_match.precision() * 100.0,
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line_match.recall() * 100.0,
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line_match.f1_score() * 100.0
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)?;
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writeln!(
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f,
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" └─ diff chrF {:<6} {:<6} {:<6} {:>8} {:>8} {:>6.2}",
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"-", "-", "-", "-", "-", edit_scores.chr_f
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)?;
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}
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Ok(())
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}
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}
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fn evaluate(example: &Example, preds: &PredictionDetails, predict: bool) -> EvaluationResult {
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let mut eval_result = EvaluationResult {
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prompt_len: preds.prompt_len,
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generated_len: preds.generated_len,
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..Default::default()
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};
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if predict {
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// todo: alternatives for patches
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let expected_patch = example
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.expected_patch
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.lines()
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.map(DiffLine::parse)
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.collect::<Vec<_>>();
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let actual_patch = preds.diff.lines().map(DiffLine::parse).collect::<Vec<_>>();
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let line_match = metrics::line_match_score(&expected_patch, &actual_patch);
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let chr_f = metrics::delta_chr_f(&expected_patch, &actual_patch);
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eval_result.edit_scores = Some(EditScores { line_match, chr_f });
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}
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eval_result
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}
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/// Return annotated `patch_a` so that:
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/// Additions and deletions that are not present in `patch_b` will be highlighted in red.
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/// Additions and deletions that are present in `patch_b` will be highlighted in green.
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pub fn compare_diffs(patch_a: &str, patch_b: &str, use_color: bool) -> String {
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let green = if use_color { "\x1b[32m✓ " } else { "" };
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let red = if use_color { "\x1b[31m✗ " } else { "" };
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let neutral = if use_color { " " } else { "" };
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let reset = if use_color { "\x1b[0m" } else { "" };
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let lines_a = patch_a.lines().map(DiffLine::parse);
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let lines_b: Vec<_> = patch_b.lines().map(DiffLine::parse).collect();
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let annotated = lines_a
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.map(|line| match line {
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DiffLine::Addition(_) | DiffLine::Deletion(_) => {
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if lines_b.contains(&line) {
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format!("{green}{line}{reset}")
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} else {
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format!("{red}{line}{reset}")
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}
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}
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_ => format!("{neutral}{line}{reset}"),
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})
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.collect::<Vec<String>>();
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annotated.join("\n")
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}
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fn write_bucketed_analysis(
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all_results: &Vec<
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Vec<Result<(EvaluationResult, ExecutionData), (anyhow::Error, String, Option<u16>)>>,
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>,
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) -> Result<()> {
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#[derive(Debug)]
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struct EditBucket {
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diff: String,
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is_correct: bool,
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execution_indices: Vec<String>,
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reasoning_samples: Vec<String>,
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}
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let mut total_executions = 0;
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let mut empty_predictions = Vec::new();
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let mut errors = Vec::new();
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let mut buckets: HashMap<String, EditBucket> = HashMap::new();
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for result in all_results.iter().flatten() {
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total_executions += 1;
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let (evaluation_result, execution_data) = match result {
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Ok((eval_result, execution_data)) => {
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if execution_data.diff.is_empty() {
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empty_predictions.push(execution_data);
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continue;
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}
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(eval_result, execution_data)
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}
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Err(err) => {
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errors.push(err);
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continue;
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}
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};
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buckets
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.entry(execution_data.diff.clone())
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.and_modify(|bucket| {
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bucket
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.execution_indices
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.push(execution_data.execution_id.clone());
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bucket
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.reasoning_samples
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.push(execution_data.reasoning.clone());
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})
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.or_insert_with(|| EditBucket {
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diff: execution_data.diff.clone(),
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is_correct: {
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evaluation_result
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.edit_scores
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.as_ref()
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.map_or(false, |edit_scores| {
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edit_scores.line_match.false_positives == 0
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&& edit_scores.line_match.false_negatives == 0
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&& edit_scores.line_match.true_positives > 0
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})
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},
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execution_indices: vec![execution_data.execution_id.clone()],
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reasoning_samples: vec![execution_data.reasoning.clone()],
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});
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}
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let mut sorted_buckets = buckets.into_values().collect::<Vec<_>>();
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sorted_buckets.sort_by(|a, b| match (a.is_correct, b.is_correct) {
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(true, false) => std::cmp::Ordering::Less,
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(false, true) => std::cmp::Ordering::Greater,
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_ => b.execution_indices.len().cmp(&a.execution_indices.len()),
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});
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let output_path = crate::paths::RUN_DIR.join("bucketed_analysis.md");
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let mut output = std::fs::File::create(&output_path)?;
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writeln!(output, "# Bucketed Edit Analysis\n")?;
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writeln!(output, "## Summary\n")?;
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writeln!(output, "- **Total executions**: {}", total_executions)?;
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let correct_count: usize = sorted_buckets
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.iter()
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.filter(|b| b.is_correct)
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.map(|b| b.execution_indices.len())
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.sum();
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let incorrect_count: usize = sorted_buckets
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.iter()
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.filter(|b| !b.is_correct)
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.map(|b| b.execution_indices.len())
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.sum();
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writeln!(
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output,
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"- **Correct predictions**: {} ({:.1}%)",
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correct_count,
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(correct_count as f64 / total_executions as f64) * 100.0
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)?;
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writeln!(
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output,
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"- **Incorrect predictions**: {} ({:.1}%)",
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incorrect_count,
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(incorrect_count as f64 / total_executions as f64) * 100.0
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)?;
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writeln!(
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output,
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"- **No Predictions**: {} ({:.1}%)",
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empty_predictions.len(),
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(empty_predictions.len() as f64 / total_executions as f64) * 100.0
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)?;
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let unique_incorrect = sorted_buckets.iter().filter(|b| !b.is_correct).count();
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writeln!(
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output,
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"- **Unique incorrect edit patterns**: {}\n",
|
|
unique_incorrect
|
|
)?;
|
|
|
|
writeln!(output, "---\n")?;
|
|
|
|
for (idx, bucket) in sorted_buckets.iter().filter(|b| b.is_correct).enumerate() {
|
|
if idx == 0 {
|
|
writeln!(
|
|
output,
|
|
"## Correct Predictions ({} occurrences)\n",
|
|
bucket.execution_indices.len()
|
|
)?;
|
|
}
|
|
|
|
writeln!(output, "**Predicted Edit:**\n")?;
|
|
writeln!(output, "```diff")?;
|
|
writeln!(output, "{}", bucket.diff)?;
|
|
writeln!(output, "```\n")?;
|
|
|
|
writeln!(
|
|
output,
|
|
"**Executions:** {}\n",
|
|
bucket.execution_indices.join(", ")
|
|
)?;
|
|
writeln!(output, "---\n")?;
|
|
}
|
|
|
|
for (idx, bucket) in sorted_buckets.iter().filter(|b| !b.is_correct).enumerate() {
|
|
writeln!(
|
|
output,
|
|
"## Incorrect Prediction #{} ({} occurrences)\n",
|
|
idx + 1,
|
|
bucket.execution_indices.len()
|
|
)?;
|
|
|
|
writeln!(output, "**Predicted Edit:**\n")?;
|
|
writeln!(output, "```diff")?;
|
|
writeln!(output, "{}", bucket.diff)?;
|
|
writeln!(output, "```\n")?;
|
|
|
|
writeln!(
|
|
output,
|
|
"**Executions:** {}\n",
|
|
bucket.execution_indices.join(", ")
|
|
)?;
|
|
|
|
for (exec_id, reasoning) in bucket
|
|
.execution_indices
|
|
.iter()
|
|
.zip(bucket.reasoning_samples.iter())
|
|
{
|
|
writeln!(output, "{}", fmt_execution(exec_id, reasoning))?;
|
|
}
|
|
|
|
writeln!(output, "\n---\n")?;
|
|
}
|
|
|
|
if !empty_predictions.is_empty() {
|
|
writeln!(
|
|
output,
|
|
"## No Predictions ({} occurrences)\n",
|
|
empty_predictions.len()
|
|
)?;
|
|
|
|
for execution_data in &empty_predictions {
|
|
writeln!(
|
|
output,
|
|
"{}",
|
|
fmt_execution(&execution_data.execution_id, &execution_data.reasoning)
|
|
)?;
|
|
}
|
|
writeln!(output, "\n---\n")?;
|
|
}
|
|
|
|
if !errors.is_empty() {
|
|
writeln!(output, "## Errors ({} occurrences)\n", errors.len())?;
|
|
|
|
for (err, name, repetition_ix) in &errors {
|
|
writeln!(output, "{}", fmt_evaluation_error(err, name, repetition_ix))?;
|
|
}
|
|
writeln!(output, "\n---\n")?;
|
|
}
|
|
|
|
fn fmt_execution(exec_id: &str, reasoning: &str) -> String {
|
|
let exec_content = format!(
|
|
"\n### Execution {} `{}/{}/prediction_response.md`{}",
|
|
exec_id,
|
|
crate::paths::RUN_DIR.display(),
|
|
exec_id,
|
|
indent_text(&format!("\n\n```\n{}\n```\n", reasoning,), 2)
|
|
);
|
|
indent_text(&exec_content, 2)
|
|
}
|
|
|
|
fn indent_text(text: &str, spaces: usize) -> String {
|
|
let indent = " ".repeat(spaces);
|
|
text.lines()
|
|
.collect::<Vec<_>>()
|
|
.join(&format!("\n{}", indent))
|
|
}
|
|
|
|
Ok(())
|
|
}
|
|
|
|
fn fmt_evaluation_error(err: &anyhow::Error, name: &str, repetition_ix: &Option<u16>) -> String {
|
|
let err = format!("{err:?}")
|
|
.replace("<edits", "```xml\n<edits")
|
|
.replace("</edits>", "</edits>\n```");
|
|
format!(
|
|
"### ERROR {name}{}\n\n{err}\n",
|
|
repetition_ix
|
|
.map(|ix| format!(" [RUN {ix:03}]"))
|
|
.unwrap_or_default()
|
|
)
|
|
}
|