Reported as "LinkedIn is not showing though the resume has it". The LinkedIn
was never the problem.
Traced on the live application (Mohammad Raza, inbox row 2f81cebc). Its stored
resume_text is 4,555 characters over 2,278 lines, and every one of those lines
is exactly one character long. The CV really does say
LinkedIn:linkedin.com/in/mohammad-raza-digital-marketer
but it is stored as forty separate lines, so nothing that looks for a substring
can find it. Not a link annotation, not an image, not OCR: pypdf's default mode
breaks after every glyph on PDFs whose author positioned each one separately,
which design tools do routinely.
It survived review because a model reads that text fine. The candidate was
classified, matched and scored normally. What fails, silently, is every check
that asks "does this string appear in the resume":
- slugs_from_text finds no profile, so linkedin_slug is stored empty
- _clean_skills drops every skill, since each must appear in the text
- the company and education clamps drop theirs for the same reason
- verify_matched_keywords drops every matched keyword in the ATS engine
despace_line could not help: it rebuilds glyphs padded *within* a line, and
here there is nothing left on a line to rebuild.
is_glyph_fragmented measures the giveaway — the share of non-empty lines that
are a single character — and extract_pdf_text re-extracts with pypdf's layout
mode when it trips. Layout mode is the fallback, never the default: it is
slower and pads ordinary documents with alignment whitespace, so a CV that
extracts cleanly today is untouched. The fallback is checked before it is
trusted; fragmented text still scores a candidate, empty text fails them.
Both extractors had the defect, so the helpers live in app/services/pdf.py,
which owns PDF handling and is already imported by the recruiting path.
Measured against that real CV, before and after:
slugs_from_text [] -> ['mohammad-raza-digital-marketer']
profile_url_from_text None -> https://www.linkedin.com/in/...
lines 2278 -> 61
single-char lines 2278 -> 0
'performance' found False -> True
'google ads' found False -> True
Existing rows keep their broken text; extraction runs at ingest. Re-running
the match on affected rows is what backfills them.
.gitignore had `tests/**` twice and `/backend/tests/**` once. Both suites are
tracked and both run in CI, so the rules were inert for existing files and did
nothing but swallow new ones — this test was invisible to `git status` until
they went. That is also why they are removed rather than negated.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The recruiter table was user-centric (GET /candidate/fetch/users), so it could
only ever render account fields - name, email, created date. Everything a
recruiter actually triages on lives on the application, not the user.
Point the table at GET /candidate/fetch and map application rows through a new
toApplicationListView, adding Job, ATS (score + band chip), Stage and Recruiter
columns. Stage and band become real filters; the dead Department facet is gone.
Manual uploads came back unscored because the list path never joined the ATS
results, so attach scores there and expose ai_score/recommendation from the
manager serializer, deriving the band from the score when the model omitted it.
Co-authored-by: Cursor <cursoragent@cursor.com>
Deploy to S3 / deploy (push) Successful in 36sDetails
The job picker gains a No job / store in CV bank option: files upload
one-per-request through the existing POST /candidate/cv_upload pipeline
(email auto-detected from the CV, saved as an UNASSIGNED inbox item with
background job suggestions) instead of being scored. Queue rows show
Stored plus the detected email; a CV with no detectable email fails
alone with a clear message. In this mode the scored grid gives way to a
panel linking Job Matching and the Inbox, where stored CVs are browsed
and later assigned. Also guarded the matcher enqueue in ingest_upload:
with the broker down the upload used to 500 after the row was inserted.
E2E-verified: two CVs stored (emails detected), rows visible in DB with
assigned_job_post_id NULL, both surfaced in Job Matching and the Inbox.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- Added a new `CandidateHistory` model to maintain an append-only audit log for candidate actions.
- Introduced `HistoryRecorder` functionality to log significant events across various modules, including interviews, feedback, and notes.
- Updated existing methods to include `current_user` for tracking who performed actions.
- Enhanced the `EMAIL_URL` configuration in `docker-compose.yml` to allow for environment variable overrides.
- Updated frontend components to support fetching and displaying candidate history.
This commit improves the application's ability to track changes and actions related to candidates, enhancing accountability and transparency.
- inbox_messages.ats_score/ats_band written on every completed inbox score;
inbox.ats_id always points at the current ats_results row
- ats_results now holds the supersede-chained history for BOTH inbox and
upload scores (new candidate_id link, inbox_id nullable for uploads)
- migrations/manual/*.sql apply automatically at startup, tracked once per
database in manual_migrations - developers just pull and boot
- 002_backfill_inbox_ats.sql backfills pre-existing scores
- Add Candidate modal: Matching-style role picker above the CV dropzone,
and the CV is scored via /candidate/score after creation
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Talha Ahmed
ahmed.mujtaba