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Respect UI language in match result — LLM responds in user's selected language

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The frontend sends the active language code (currentLang()) with every match
request. CvMatcherService injects a language instruction into the system prompt
so the LLM returns summary, strengths, gaps, recommendations, and evidence in
the correct language. The match result cache (CvMatchResults) now includes
Language as part of the lookup key so Romanian and English results are stored
and retrieved independently. Existing cached rows default to 'en'.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
claude
2026-05-24 17:04:21 +03:00
parent e394dad5fb
commit b6878e3b45
10 changed files with 166 additions and 13 deletions
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Apis/cv-matcher-api/Services/CvMatcherService.cs
+18 -6
View File
@@ -69,7 +69,7 @@ public sealed class CvMatcherService : ICvMatcherService
{
var job = await _rag.GetDocumentAsync(result.DocumentId, ct);
if (job is null) continue;
jobs.Add(await ScorePairAsync(cv, job, result.MatchedChunks.Select(x => x.Text).ToArray(), request.Email, ct));
jobs.Add(await ScorePairAsync(cv, job, result.MatchedChunks.Select(x => x.Text).ToArray(), request.Email, NormalizeLanguage(null), ct));
}
return new FindJobsResponse { CvDocumentId = request.CvDocumentId, Jobs = jobs };
@@ -98,21 +98,23 @@ public sealed class CvMatcherService : ICvMatcherService
.FirstOrDefault(x => x.DocumentId == job.DocumentId)?
.MatchedChunks.Select(x => x.Text).ToArray() ?? [];
return await ScorePairAsync(cv, jobDocument, matchedChunks, request.Email, ct);
return await ScorePairAsync(cv, jobDocument, matchedChunks, request.Email, NormalizeLanguage(request.Language), ct);
}
private async Task<JobMatchResponse> ScorePairAsync(RagDocumentDetails cv, RagDocumentDetails job, IReadOnlyList<string> evidenceChunks, string? email, CancellationToken ct)
private async Task<JobMatchResponse> ScorePairAsync(RagDocumentDetails cv, RagDocumentDetails job, IReadOnlyList<string> evidenceChunks, string? email, string language, CancellationToken ct)
{
var cached = await _repository.GetMatchAsync(cv.Id, job.Id, ct);
var cached = await _repository.GetMatchAsync(cv.Id, job.Id, language, ct);
if (cached is not null) return cached;
var cvText = Limit(cv.Text, 18000);
var jobText = Limit(job.Text, 14000);
var evidence = evidenceChunks.Count > 0 ? string.Join("\n\n", evidenceChunks.Take(4)) : Limit(job.Text, 4000);
var languageName = LanguageName(language);
const string systemPrompt = """
var systemPrompt = $$"""
You are a strict CV-to-job matching engine. Return JSON only. Score realistically from 0 to 100.
Penalize missing required skills. Do not invent experience. Use concise business language.
Respond entirely in {{languageName}} — all text fields in the JSON must be in {{languageName}}.
JSON shape: {"score":number,"summary":"...","strengths":["..."],"gaps":["..."],"recommendations":["..."],"evidence":["..."]}
""";
@@ -132,7 +134,7 @@ public sealed class CvMatcherService : ICvMatcherService
result.JobDocumentId = job.Id;
result.JobUrl = job.SourceUrl;
result.Cached = false;
await _repository.SaveMatchAsync(cv.Id, job.Id, result, ct);
await _repository.SaveMatchAsync(cv.Id, job.Id, language, result, ct);
//await _email.SendMatchAsync(
// email,
@@ -175,6 +177,16 @@ public sealed class CvMatcherService : ICvMatcherService
return first ?? "Job description";
}
private static string NormalizeLanguage(string? language) =>
string.IsNullOrWhiteSpace(language) ? "en" : language.ToLowerInvariant().Split('-')[0].Trim();
private static string LanguageName(string language) => language switch
{
"ro" => "Romanian",
"en" => "English",
_ => "English"
};
private static string Limit(string value, int max) => value.Length <= max ? value : value[..max];
//private static string BuildEmailBody(RagDocumentDetails cv, RagDocumentDetails job, JobMatchResponse result) => $"""