fix: harden resume section detection — anchor patterns to full line, expand header synonyms, fix name heuristic for hyphenated/middle-initial names, add parse diagnostics UI

app/pages/0_Setup.py

@@ -317,14 +317,33 @@ elif step == 4:
                 else extract_text_from_docx(file_bytes)
             )
             with st.spinner("Parsing\u2026"):
-                parsed = structure_resume(raw_text)
+                parsed, parse_err = structure_resume(raw_text)
-            if parsed:
+
+            # Diagnostic: show raw extraction + detected fields regardless of outcome
+            with st.expander("🔍 Parse diagnostics", expanded=not bool(parsed and any(
+                parsed.get(k) for k in ("name", "experience", "skills")
+            ))):
+                st.caption("**Raw extracted text (first 800 chars)**")
+                st.code(raw_text[:800] if raw_text else "(empty)", language="text")
+                if parsed:
+                    st.caption("**Detected fields**")
+                    st.json({k: (v[:3] if isinstance(v, list) else v) for k, v in parsed.items()})
+
+            if parsed and any(parsed.get(k) for k in ("name", "experience", "skills")):
                 st.session_state["_parsed_resume"] = parsed
                 st.session_state["_raw_resume_text"] = raw_text
                 _save_yaml({"_raw_resume_text": raw_text[:8000]})
                 st.success("Parsed! Review the builder tab to edit entries.")
+            elif parsed:
+                # Parsed but empty — show what we got and let them proceed or build manually
+                st.session_state["_parsed_resume"] = parsed
+                st.warning("Resume text was extracted but no fields were recognised. "
+                           "Check the diagnostics above — the section headers may use unusual labels. "
+                           "You can still fill in the Build tab manually.")
             else:
                 st.warning("Auto-parse failed \u2014 switch to the Build tab and add entries manually.")
+                if parse_err:
+                    st.caption(f"Reason: {parse_err}")
 
     with tab_builder:
         parsed = st.session_state.get("_parsed_resume", {})

scripts/resume_parser.py

@@ -22,11 +22,11 @@ log = logging.getLogger(__name__)
 # ── Section header detection ──────────────────────────────────────────────────
 
 _SECTION_NAMES = {
-    "summary":    re.compile(r"^(summary|objective|profile|about me|professional summary)", re.I),
+    "summary":    re.compile(r"^(summary|objective|profile|about me|professional summary|career summary|career objective|personal statement)\s*:?\s*$", re.I),
-    "experience": re.compile(r"^(experience|work experience|employment|work history|professional experience)", re.I),
+    "experience": re.compile(r"^(experience|work experience|employment|work history|professional experience|career history|relevant experience|professional history|employment history|positions? held)\s*:?\s*$", re.I),
-    "education":  re.compile(r"^(education|academic|qualifications|degrees?)", re.I),
+    "education":  re.compile(r"^(education|academic|qualifications|degrees?|educational background|academic background)\s*:?\s*$", re.I),
-    "skills":     re.compile(r"^(skills?|technical skills?|core competencies|competencies|expertise)", re.I),
+    "skills":     re.compile(r"^(skills?|technical skills?|core competencies|competencies|expertise|areas? of expertise|key skills?|proficiencies|tools? & technologies)\s*:?\s*$", re.I),
-    "achievements": re.compile(r"^(achievements?|accomplishments?|awards?|honors?|certifications?)", re.I),
+    "achievements": re.compile(r"^(achievements?|accomplishments?|awards?|honors?|certifications?|publications?|volunteer)\s*:?\s*$", re.I),
 }
 
 # Degrees — used to detect education lines
@@ -108,17 +108,20 @@ def _parse_header(lines: list[str]) -> dict:
     email_m   = _EMAIL_RE.search(full_text)
     phone_m   = _PHONE_RE.search(full_text)
 
-    # Name heuristic: first non-empty line that has no @ and no digits-only tokens
+    # Name heuristic: first non-empty line that looks like a person's name
     name = ""
     for line in lines[:5]:
         if "@" in line or re.match(r"^\d", line.strip()):
             continue
-        # Skip lines that look like city/state/zip
+        # Skip lines that look like city/state/zip or URLs
-        if re.search(r"\b[A-Z]{2}\b\s*\d{5}", line):
+        if re.search(r"\b[A-Z]{2}\b\s*\d{5}", line) or re.search(r"https?://|linkedin|github", line, re.I):
             continue
+        # Strip separators and credential suffixes (MBA, PhD, etc.) for the alpha check
         candidate = re.sub(r"[|•·,]+", " ", line).strip()
         candidate = re.sub(r"\s{2,}", " ", candidate)
-        if 2 <= len(candidate.split()) <= 5 and candidate.replace(" ", "").isalpha():
+        # Normalise: remove periods, hyphens for the alpha-only check
+        alpha_check = re.sub(r"[.\-'\u2019]", "", candidate.replace(" ", ""))
+        if 2 <= len(candidate.split()) <= 5 and alpha_check.isalpha():
             name = candidate
             break