Fix SBI multiline table parsing and restore template-first bank analysis

app/modules/bank_statement_analyzer/parsers/bank_identity.py

@@ -151,6 +151,10 @@ def detect_bank_identity(
 ) -> BankIdentityMatch | None:
     raw_text = str(text or "")
     text_upper = _normalise(raw_text)
+    # Identity headings and account metadata are normally in the first page.
+    # Restrict strong name evidence to the beginning so counterparty bank names
+    # inside hundreds of transaction narrations cannot relabel the statement.
+    header_upper = _normalise(raw_text[:800])
     ifsc_upper = re.sub(r"[^A-Z0-9]", "", str(ifsc or "").upper())
     file_upper = _normalise(Path(source_file or "").stem)
 
@@ -159,25 +163,36 @@ def detect_bank_identity(
         score = 0.0
         evidence: list[str] = []
 
-        # Longest/special IFSC prefixes carry the strongest identity signal.
-        matching_prefixes = [prefix for prefix in bank.ifsc_prefixes if ifsc_upper.startswith(prefix.upper())]
+        matching_prefixes = [
+            prefix for prefix in bank.ifsc_prefixes
+            if ifsc_upper.startswith(prefix.upper())
+        ]
         if matching_prefixes:
             prefix = max(matching_prefixes, key=len)
-            score += 0.72 if len(prefix) > 4 else 0.58
+            # The account IFSC belongs to the issuing bank and therefore outranks
+            # bank names appearing merely as transaction counterparties.
+            score += 0.96 if len(prefix) > 4 else 0.90
             evidence.append(f"IFSC prefix {prefix}")
 
         for domain in bank.domains:
             if domain.lower() in raw_text.lower():
-                score += 0.72
+                score += 0.92
                 evidence.append(f"domain {domain}")
                 break
 
-        alias_hits = [alias for alias in bank.aliases if _alias_present(text_upper, alias)]
-        if alias_hits:
-            longest = max(alias_hits, key=len)
-            # Long formal headings are stronger than abbreviations such as SBI.
-            score += 0.72 if len(_normalise(longest)) >= 12 else 0.36
-            evidence.append(f"name {longest}")
+        header_alias_hits = [alias for alias in bank.aliases if _alias_present(header_upper, alias)]
+        if header_alias_hits:
+            longest = max(header_alias_hits, key=len)
+            score += 0.88 if len(_normalise(longest)) >= 12 else 0.55
+            evidence.append(f"header name {longest}")
+        else:
+            # Full-document matches are weak because narrations commonly mention
+            # beneficiary and remitter banks. They may support another signal but
+            # cannot identify the issuer by themselves.
+            body_hits = [alias for alias in bank.aliases if _alias_present(text_upper, alias)]
+            if body_hits:
+                score += 0.12
+                evidence.append("body mention")
 
         if any(_alias_present(file_upper, alias) for alias in bank.aliases):
             score += 0.10
@@ -186,7 +201,9 @@ def detect_bank_identity(
         confidence = min(score, 0.99)
         if confidence < 0.50:
             continue
-        candidate = BankIdentityMatch(bank.name, bank.category, confidence, tuple(dict.fromkeys(evidence)))
+        candidate = BankIdentityMatch(
+            bank.name, bank.category, confidence, tuple(dict.fromkeys(evidence))
+        )
         if best is None or candidate.confidence > best.confidence:
             best = candidate
 
@@ -194,9 +211,21 @@ def detect_bank_identity(
 
 
 def apply_detected_bank_identity(meta, df, text: str):
+    meta_ifsc = str(getattr(meta, "ifsc", "") or "")
+    if not meta_ifsc:
+        # Some PDFs place the IFSC value far from its label in text-reading
+        # order.  Recover the first header-area IFSC token directly; limiting
+        # the search to the beginning avoids beneficiary-bank IFSC codes.
+        header_match = re.search(r"\b[A-Z]{4}0[A-Z0-9]{6}\b", str(text or "")[:2500], re.I)
+        if header_match:
+            meta_ifsc = header_match.group(0).upper()
+            try:
+                meta.ifsc = meta_ifsc
+            except Exception:
+                pass
     match = detect_bank_identity(
         text,
-        ifsc=str(getattr(meta, "ifsc", "") or ""),
+        ifsc=meta_ifsc,
         source_file=str(getattr(meta, "source_file", "") or ""),
     )
     if match is None:

app/modules/bank_statement_analyzer/parsers/registry.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+import logging
+
 from .idfc import IDFCFirstParser
 from .axis import AxisParser
 from .hdfc import HDFCParser
@@ -17,7 +19,9 @@ from .rbl_bank import RBLBankParser
 from .andhra_pradesh_grameena_bank import AndhraPradeshGrameenaBankParser
 from .bank_identity import apply_detected_bank_identity
 from .base import extract_text
+from .template_engine import parse_with_template
 
+logger = logging.getLogger(__name__)
 
 PARSERS = [
     IDFCFirstParser,
@@ -88,54 +92,137 @@ def detect_parser(text):
     return scored[0][1](), scored[0][0]
 
 
-def _selected_parser(bank_key: str, text: str):
-    candidates = BANK_PARSERS.get(bank_key, [])
-    if not candidates:
-        return None, 0
+def _usable_result(result) -> bool:
+    if result is None:
+        return False
+    try:
+        _meta, frame = result
+        return frame is not None and not frame.empty
+    except Exception:
+        return False
+
+
+def _identified(result, text: str):
+    if not _usable_result(result):
+        return None
+    meta, frame = result
+    return apply_detected_bank_identity(meta, frame, text)
+
+
+def _attempt(parser, path, text: str, route: str):
+    try:
+        result = parser.parse(path, text)
+        result = _identified(result, text)
+        if result is not None:
+            meta, frame = result
+            logger.info(
+                "Bank analyzer route accepted: route=%s parser=%s rows=%s file=%s",
+                route,
+                getattr(meta, "parser_name", parser.__class__.__name__),
+                len(frame),
+                path,
+            )
+            return result
+        logger.warning(
+            "Bank analyzer route returned no rows: route=%s parser=%s file=%s",
+            route,
+            parser.__class__.__name__,
+            path,
+        )
+    except Exception as exc:
+        logger.warning(
+            "Bank analyzer route failed: route=%s parser=%s file=%s error=%s",
+            route,
+            parser.__class__.__name__,
+            path,
+            exc,
+            exc_info=True,
+        )
+    return None
+
+
+def _template_first(path, text: str, hint: str):
+    try:
+        result = parse_with_template(path, text=text, bank_hint=hint)
+        result = _identified(result, text)
+        if result is not None:
+            meta, frame = result
+            logger.info(
+                "Bank analyzer template accepted: parser=%s rows=%s file=%s",
+                getattr(meta, "parser_name", "TemplateBasedStatementParser"),
+                len(frame),
+                path,
+            )
+            return result
+        logger.warning("Bank analyzer template returned no rows: file=%s", path)
+    except Exception as exc:
+        logger.warning(
+            "Bank analyzer template rejected: file=%s error=%s",
+            path,
+            exc,
+            exc_info=True,
+        )
+    return None
+
+
+def _ordered_bank_candidates(text: str):
     scored = sorted(
-        ((parser.detect(text), parser) for parser in candidates),
+        ((parser.detect(text), parser) for parser in PARSERS),
         key=lambda item: item[0],
         reverse=True,
     )
-    if scored and scored[0][0] > 0:
-        return scored[0][1](), scored[0][0]
-    return None, 0
-
-
-def _parse_and_identify(parser, path, text: str):
-    meta, df = parser.parse(path, text)
-    return apply_detected_bank_identity(meta, df, text)
+    return [parser for score, parser in scored if score > 0]
 
 
 def parse_pdf(path, bank_hint: str | None = None):
+    """Parse a statement using a validated template first, then bank parsers.
+
+    Bank identity is resolved independently after extraction, so using a shared
+    layout never labels a statement as the bank whose parser happens to have a
+    similar table structure.
+    """
     hint = (bank_hint or "auto").strip().lower()
     text = extract_text(path)
 
-    if hint == "hsbc":
-        meta, df = HSBCParser().parse(path, text)
-        return apply_detected_bank_identity(meta, df, text)
+    template_result = _template_first(path, text, hint)
+    if template_result is not None:
+        return template_result
 
     if hint and hint != "auto":
-        parser, score = _selected_parser(hint, text)
-        if parser is None:
-            label = dict(BANK_OPTIONS).get(hint, "the selected bank")
-            raise ValueError(
-                f"The uploaded statement does not match the selected {label} format. "
-                "Please verify the selected bank or choose Auto Detect."
-            )
-        return _parse_and_identify(parser, path, text)
-
-    parser, score = detect_parser(text)
-    if parser is None and not (text or "").strip():
-        # Image-only statements cannot be identified by pdftotext. HSBCParser
-        # performs its own OCR identification and raises a precise mismatch error.
-        try:
-            meta, df = HSBCParser().parse(path, text)
-            return apply_detected_bank_identity(meta, df, text)
-        except ValueError:
-            pass
-    if parser is None:
+        candidates = BANK_PARSERS.get(hint, [])
+        for parser_class in sorted(candidates, key=lambda cls: cls.detect(text), reverse=True):
+            result = _attempt(parser_class(), path, text, f"selected:{hint}")
+            if result is not None:
+                return result
+        label = dict(BANK_OPTIONS).get(hint, "the selected bank")
         raise ValueError(
-            "Unsupported statement format. Select the bank manually or add a bank-specific parser for this statement layout."
+            f"The uploaded statement could not be parsed by a validated layout template or the "
+            f"selected {label} parser. Please verify that the PDF is readable and supported."
         )
-    return _parse_and_identify(parser, path, text)
+
+    attempted: set[type] = set()
+    for parser_class in _ordered_bank_candidates(text):
+        attempted.add(parser_class)
+        result = _attempt(parser_class(), path, text, "auto-detected")
+        if result is not None:
+            return result
+
+    if not (text or "").strip():
+        result = _attempt(HSBCParser(), path, text, "image-only-ocr")
+        if result is not None:
+            return result
+
+    # A detector may miss a new bank layout even though an existing dedicated
+    # parser can still extract and reconcile it. Keep this compatibility pass.
+    for parser_class in PARSERS:
+        if parser_class in attempted:
+            continue
+        result = _attempt(parser_class(), path, text, "compatibility-fallback")
+        if result is not None:
+            return result
+
+    raise ValueError(
+        "The bank statement format was identified, but no transaction rows could be extracted. "
+        "The validated template engine and all bank-specific parsers were attempted. "
+        "Please verify that the PDF is text-readable and that this statement layout is supported."
+    )