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progress on eval
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parent
d4fbe99052
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3 changed files with 79 additions and 5 deletions
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@ -12,7 +12,7 @@
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{
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"query": "What version of the openai package is active?",
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"matches": [
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"pyproject.toml:14"
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"pyprojet.toml:14"
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]
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},
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{
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@ -48,7 +48,7 @@
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"query": "Handle conflict when numerous actions occur on the same symbol",
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"matches": [
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"cli/src/generate/build_tables/build_parse_table.rs:363",
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"cli/src/generate/build_tables/build_parse_table.rs:442",
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"cli/src/generate/build_tables/build_parse_table.rs:442"
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]
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},
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{
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@ -1,19 +1,36 @@
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use git2::{Object, Oid, Repository};
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use semantic_index::SearchResult;
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use serde::Deserialize;
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use std::path::{Path, PathBuf};
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use std::{env, fs};
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#[derive(Deserialize, Clone)]
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struct QueryMatches {
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struct EvaluationQuery {
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query: String,
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matches: Vec<String>,
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}
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impl EvaluationQuery {
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fn match_pairs(&self) -> Vec<(PathBuf, usize)> {
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let mut pairs = Vec::new();
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for match_identifier in self.matches {
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let match_parts = match_identifier.split(":");
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if let Some(file_path) = match_parts.next() {
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if let Some(row_number) = match_parts.next() {
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pairs.push((PathBuf::from(file_path), from_str::<usize>(row_number)));
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}
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}
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pairs
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}
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}
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#[derive(Deserialize, Clone)]
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struct RepoEval {
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repo: String,
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commit: String,
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assertions: Vec<QueryMatches>,
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assertions: Vec<EvaluationQuery>,
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}
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const TMP_REPO_PATH: &str = "./target/eval_repos";
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@ -77,7 +94,60 @@ fn clone_repo(repo_eval: RepoEval) -> anyhow::Result<PathBuf> {
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Ok(clone_path)
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}
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fn dcg(hits: Vec<usize>) -> f32 {
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let mut result = 0.0;
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for (idx, hit) in hits.iter().enumerate() {
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result += *hit as f32 / (2.0 + idx as f32).log2();
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}
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println!("DCG: {:?}", result);
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result
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}
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fn evaluate_ndcg(eval_query: EvaluationQuery, search_results: Vec<SearchResult>, k: usize) -> f32 {
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// NDCG or Normalized Discounted Cumulative Gain, is determined by comparing the relevance of
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// items returned by the search engine relative to the hypothetical ideal.
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// Relevance is represented as a series of booleans, in which each search result returned
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// is identified as being inside the test set of matches (1) or not (0).
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// For example, if result 1, 3 and 5 match the 3 relevant results provided
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// actual dcg is calculated against a vector of [1, 0, 1, 0, 1]
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// whereas ideal dcg is calculated against a vector of [1, 1, 1, 0, 0]
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// as this ideal vector assumes the 3 relevant results provided were returned first
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// normalized dcg is then calculated as actual dcg / ideal dcg.
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// NDCG ranges from 0 to 1, which higher values indicating better performance
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// Commonly NDCG is expressed as NDCG@k, in which k represents the metric calculated
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// including only the top k values returned.
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// The @k metrics can help you identify, at what point does the relevant results start to fall off.
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// Ie. a NDCG@1 of 0.9 and a NDCG@3 of 0.5 may indicate that the first result returned in usually
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// very high quality, whereas rank results quickly drop off after the first result.
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let ideal = vec![1; cmp::min(eval_query.matches.len(), k)];
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return dcg(hits) / dcg(ideal);
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}
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fn evaluate_map(eval_query: EvaluationQuery, search_results: Vec<SearchResult>, k: usize) -> f32 {
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}
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fn evaluate_repo(repo_eval: RepoEval, clone_path: PathBuf) {
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// Launch new repo as a new Zed workspace/project
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// Index the project
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// Search each eval_query
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// Calculate Statistics
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}
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fn main() {
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// zed/main.rs
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// creating an app and running it, gives you the context.
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// create a project, find_or_create_local_worktree.
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if let Ok(repo_evals) = parse_eval() {
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for repo in repo_evals {
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let cloned = clone_repo(repo.clone());
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@ -85,8 +155,12 @@ fn main() {
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Ok(clone_path) => {
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println!(
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"Cloned {:?} @ {:?} into {:?}",
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repo.repo, repo.commit, clone_path
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repo.repo, repo.commit, &clone_path
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);
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// Evaluate Repo
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evaluate_repo(repo, clone_path);
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}
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Err(err) => {
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println!("Error Cloning: {:?}", err);
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