Brevo + faster drafts + adaptive chart + fuzzy lookup

backend/services/candidate_service.py

@@ -161,12 +161,52 @@ class CandidateService:
         return self._dedupe_candidates(rows, limit)
 
     def get_candidate(self, db: Session, candidate_id: str) -> Candidate | None:
+        """Look up a candidate by external_id, with two fallbacks for robustness.
+
+        Cards rendered from the search result use the Qdrant ``candidate_id``
+        which can drift from the SQLite ``external_id`` (e.g. when the bootstrap
+        loader writes one shape and ad-hoc uploads write another). We:
+          1. Match the exact ``external_id``
+          2. Match a substring (handles ``_resume`` / version suffixes)
+          3. Match the candidate name slug embedded in the id (e.g. ``alex_carter``)
+        """
         clean_id = (candidate_id or "").strip()
         if not clean_id:
             return None
-        return db.execute(
+
+        exact = db.execute(
             select(Candidate).where(Candidate.external_id == clean_id)
         ).scalar_one_or_none()
+        if exact is not None:
+            return exact
+
+        # Substring fallback — handles trailing/leading suffixes like _resume.
+        substr = db.execute(
+            select(Candidate)
+            .where(Candidate.external_id.ilike(f"%{clean_id}%"))
+            .order_by(Candidate.updated_at.desc())
+            .limit(1)
+        ).scalar_one_or_none()
+        if substr is not None:
+            return substr
+
+        # Name-slug fallback — pull "alex_carter" out of "ref_alex_carter_resume"
+        # and try to match a candidate full_name that contains both tokens.
+        slug_tokens = [
+            tok.lower()
+            for tok in re.split(r"[^a-zA-Z0-9]+", clean_id)
+            if tok and tok.lower() not in {"ref", "resume", "cv", "pdf"} and not tok.isdigit()
+        ]
+        if not slug_tokens:
+            return None
+
+        like_pattern = "%" + "%".join(slug_tokens) + "%"
+        return db.execute(
+            select(Candidate)
+            .where(Candidate.full_name.ilike(like_pattern))
+            .order_by(Candidate.updated_at.desc())
+            .limit(1)
+        ).scalar_one_or_none()
 
     def build_profile_payload(self, candidate: Candidate) -> dict[str, Any]:
         skills = [token.strip() for token in (candidate.skills_csv or "").split(",") if token.strip()]
@@ -207,22 +247,40 @@ class CandidateService:
 
         years = float(candidate.years_experience or 0)
         skill_groups = self._classify_skills(skills)
-        chart = {
-            "type": "radar",
-            "title": "Skill profile",
-            "xKey": "name",
-            "yKey": "score",
-            "data": [
-                {"name": label, "score": value}
-                for label, value in [
-                    ("Backend", skill_groups.get("backend", 0)),
-                    ("Frontend", skill_groups.get("frontend", 0)),
-                    ("Cloud", skill_groups.get("cloud", 0)),
-                    ("Data/ML", skill_groups.get("data", 0)),
-                    ("Years", round(min(years, 10), 1)),
-                ]
-            ],
-        }
+        # Build the chart axes dynamically — only include axes with data so a
+        # non-tech profile (e.g. sales / civil engineering) doesn't get rendered
+        # as five empty rings.
+        candidate_axes = [
+            ("Backend", skill_groups.get("backend", 0)),
+            ("Frontend", skill_groups.get("frontend", 0)),
+            ("Cloud", skill_groups.get("cloud", 0)),
+            ("Data/ML", skill_groups.get("data", 0)),
+        ]
+        non_zero = [(label, value) for label, value in candidate_axes if value > 0]
+        if years > 0:
+            non_zero.append(("Years", round(min(years, 10), 1)))
+
+        if len(non_zero) >= 3:
+            chart = {
+                "type": "radar",
+                "title": "Skill profile",
+                "xKey": "name",
+                "yKey": "score",
+                "data": [{"name": label, "score": value} for label, value in non_zero],
+            }
+        elif non_zero:
+            # Two or fewer signals — radar doesn't read well, switch to bar.
+            chart = {
+                "type": "bar",
+                "title": "Profile signals",
+                "xKey": "name",
+                "yKey": "score",
+                "data": [{"name": label, "score": value} for label, value in non_zero],
+            }
+        else:
+            # Nothing to plot — drop the chart entirely so the candidate card
+            # isn't cluttered with empty axes.
+            chart = None
 
         skills_chip_line = (
             " ".join(f"`{skill}`" for skill in skills) if skills else "_No skills detected._"
@@ -254,12 +312,14 @@ class CandidateService:
         )
         c1_response = f"<content><custom_markdown>{safe_md}</custom_markdown></content>"
 
-        return {
+        payload: dict[str, Any] = {
             "summary": summary_md,
             "cards": [card],
-            "chart": chart,
             "c1_response": c1_response,
         }
+        if chart is not None:
+            payload["chart"] = chart
+        return payload
 
     def get_by_external_ids(self, db: Session, external_ids: list[str]) -> list[Candidate]:
         if not external_ids: