A R R R Associates
213 lines
11 KiB
Python
213 lines
11 KiB
Python
from __future__ import annotations
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import json
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import math
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from collections import defaultdict
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from sqlalchemy import and_, func, or_, select
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from app.modules.accounting.gstr2b_models import AccountingGSTR2BPurchase
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from app.modules.accounting.gstr2b_service import nature_lookup, review_purchase
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from app.modules.accounting.historical_learning_service import active_natures, ledger_mappings
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from app.modules.accounting.purchase_enrichment_models import AccountingPurchaseEnrichmentRecord
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from app.modules.accounting.ai_service import ai_assist_purchase as run_ai_assist_purchase, mark_review_outcome
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from app.modules.accounting.internal_model_service import predict_purchase, record_prediction_review
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VALID_STATUSES = {"all", "pending_analysis", "suggested", "review_required", "reviewed"}
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VALID_CONFIDENCE = {"all", "high", "medium", "low"}
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VALID_SOURCE = {"all", "gstr2b_only", "enriched"}
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PER_PAGE_CHOICES = {10, 25, 50, 100}
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def _safe_page(value):
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try: return max(1, int(value))
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except Exception: return 1
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def _safe_per_page(value):
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try: value = int(value)
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except Exception: value = 25
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return value if value in PER_PAGE_CHOICES else 25
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def _base_stmt(tenant_id, client_id):
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enriched = (
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select(
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AccountingPurchaseEnrichmentRecord.gstr2b_purchase_id.label("purchase_id"),
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func.count(AccountingPurchaseEnrichmentRecord.id).label("enrichment_count"),
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)
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.where(
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AccountingPurchaseEnrichmentRecord.gstr2b_purchase_id.is_not(None),
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AccountingPurchaseEnrichmentRecord.match_status == "linked",
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)
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.group_by(AccountingPurchaseEnrichmentRecord.gstr2b_purchase_id)
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.subquery()
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)
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stmt = (
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select(
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AccountingGSTR2BPurchase,
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func.coalesce(enriched.c.enrichment_count, 0).label("enrichment_count"),
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)
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.outerjoin(enriched, enriched.c.purchase_id == AccountingGSTR2BPurchase.id)
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.where(
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AccountingGSTR2BPurchase.tenant_id == tenant_id,
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AccountingGSTR2BPurchase.client_id == client_id,
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)
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)
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return stmt, enriched
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def review_queue(db, *, tenant_id, client_id, tally_guid="", status="all", confidence="all", source="all", supplier="", return_period="", page=1, per_page=25):
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status = status if status in VALID_STATUSES else "all"
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confidence = confidence if confidence in VALID_CONFIDENCE else "all"
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source = source if source in VALID_SOURCE else "all"
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page = _safe_page(page); per_page = _safe_per_page(per_page)
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stmt, enriched = _base_stmt(tenant_id, client_id)
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if tally_guid: stmt = stmt.where(AccountingGSTR2BPurchase.tally_guid == tally_guid)
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if status != "all": stmt = stmt.where(AccountingGSTR2BPurchase.review_status == status)
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if confidence == "high": stmt = stmt.where(AccountingGSTR2BPurchase.suggested_confidence >= 85)
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elif confidence == "medium": stmt = stmt.where(and_(AccountingGSTR2BPurchase.suggested_confidence >= 60, AccountingGSTR2BPurchase.suggested_confidence < 85))
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elif confidence == "low": stmt = stmt.where(AccountingGSTR2BPurchase.suggested_confidence < 60)
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if source == "enriched": stmt = stmt.where(func.coalesce(enriched.c.enrichment_count, 0) > 0)
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elif source == "gstr2b_only": stmt = stmt.where(func.coalesce(enriched.c.enrichment_count, 0) == 0)
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supplier = (supplier or "").strip()
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if supplier:
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pattern = f"%{supplier}%"
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stmt = stmt.where(or_(
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AccountingGSTR2BPurchase.supplier_name.ilike(pattern),
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AccountingGSTR2BPurchase.supplier_gstin.ilike(pattern),
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AccountingGSTR2BPurchase.invoice_number.ilike(pattern),
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))
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if return_period: stmt = stmt.where(AccountingGSTR2BPurchase.return_period == return_period.strip())
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total = int(db.execute(select(func.count()).select_from(stmt.order_by(None).subquery())).scalar_one() or 0)
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pages = max(1, math.ceil(total / per_page)) if total else 1
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page = min(page, pages)
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rows = list(db.execute(stmt.order_by(AccountingGSTR2BPurchase.invoice_date.desc(), AccountingGSTR2BPurchase.id.desc()).offset((page-1)*per_page).limit(per_page)).all())
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return {"rows": rows, "total": total, "page": page, "per_page": per_page, "pages": pages}
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def review_counts(db, *, tenant_id, client_id):
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base = [AccountingGSTR2BPurchase.tenant_id == tenant_id, AccountingGSTR2BPurchase.client_id == client_id]
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total = int(db.execute(select(func.count(AccountingGSTR2BPurchase.id)).where(*base)).scalar_one() or 0)
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reviewed = int(db.execute(select(func.count(AccountingGSTR2BPurchase.id)).where(*base, AccountingGSTR2BPurchase.review_status == "reviewed")).scalar_one() or 0)
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high = int(db.execute(select(func.count(AccountingGSTR2BPurchase.id)).where(*base, AccountingGSTR2BPurchase.review_status != "reviewed", AccountingGSTR2BPurchase.suggested_nature_id.is_not(None), AccountingGSTR2BPurchase.suggested_confidence >= 85)).scalar_one() or 0)
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exceptions = int(db.execute(select(func.count(AccountingGSTR2BPurchase.id)).where(*base, AccountingGSTR2BPurchase.review_status != "reviewed", or_(AccountingGSTR2BPurchase.review_status == "review_required", AccountingGSTR2BPurchase.suggested_nature_id.is_(None), AccountingGSTR2BPurchase.suggested_confidence < 60))).scalar_one() or 0)
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enriched_ids = select(AccountingPurchaseEnrichmentRecord.gstr2b_purchase_id).where(AccountingPurchaseEnrichmentRecord.tenant_id == tenant_id, AccountingPurchaseEnrichmentRecord.client_id == client_id, AccountingPurchaseEnrichmentRecord.gstr2b_purchase_id.is_not(None), AccountingPurchaseEnrichmentRecord.match_status == "linked").distinct()
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enriched = int(db.execute(select(func.count(AccountingGSTR2BPurchase.id)).where(*base, AccountingGSTR2BPurchase.id.in_(enriched_ids))).scalar_one() or 0)
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return {"total": total, "reviewed": reviewed, "pending": max(0,total-reviewed), "high": high, "exceptions": exceptions, "enriched": enriched}
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def return_periods(db, *, tenant_id, client_id):
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return list(db.execute(select(AccountingGSTR2BPurchase.return_period).where(AccountingGSTR2BPurchase.tenant_id == tenant_id, AccountingGSTR2BPurchase.client_id == client_id, AccountingGSTR2BPurchase.return_period != "").distinct().order_by(AccountingGSTR2BPurchase.return_period.desc())).scalars().all())
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def nature_maps_for_rows(db, rows):
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ids=[]
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for row, _count in rows: ids.extend([row.suggested_nature_id,row.final_nature_id])
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return nature_lookup(db, ids)
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def explanations_for_rows(rows):
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result={}
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for row,_count in rows:
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try: result[row.id]=json.loads(row.suggestion_explanation_json or "[]")
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except Exception: result[row.id]=[]
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return result
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def mappings_by_nature(db, tenant_id, client_id, tally_guid=""):
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result=defaultdict(list)
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for row in ledger_mappings(db,tenant_id,client_id,tally_guid): result[int(row.nature_id)].append(row)
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for values in result.values(): values.sort(key=lambda x:(str(x.ledger_name or "").casefold(),x.id))
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return dict(result)
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def _validate_choice(db, *, tenant_id, client_id, purchase, nature_id, ledger_name):
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valid_natures={int(n.id) for n in active_natures(db,tenant_id)}
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if int(nature_id) not in valid_natures: raise ValueError("Select an active accounting nature.")
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ledger_name=(ledger_name or "").strip()
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if not ledger_name: return
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allowed=ledger_mappings(db,tenant_id,client_id,purchase.tally_guid)
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if not any(m.ledger_name == ledger_name and int(m.nature_id)==int(nature_id) for m in allowed):
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raise ValueError("Selected Tally ledger is not mapped to the selected accounting nature for this client/company.")
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def review_one(db, *, tenant_id, client_id, purchase_id, final_nature_id, final_ledger_name, user_id):
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row=db.execute(select(AccountingGSTR2BPurchase).where(AccountingGSTR2BPurchase.id==purchase_id,AccountingGSTR2BPurchase.tenant_id==tenant_id,AccountingGSTR2BPurchase.client_id==client_id)).scalar_one_or_none()
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if not row: raise ValueError("Purchase record was not found.")
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_validate_choice(db,tenant_id=tenant_id,client_id=client_id,purchase=row,nature_id=final_nature_id,ledger_name=final_ledger_name)
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reviewed = review_purchase(db,row=row,final_nature_id=int(final_nature_id),final_ledger_name=(final_ledger_name or "").strip(),user_id=user_id)
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mark_review_outcome(
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db,
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tenant_id=tenant_id,
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source_type="gstr2b",
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source_record_id=reviewed.id,
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final_nature_id=reviewed.final_nature_id,
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final_ledger_name=reviewed.final_ledger_name,
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user_id=user_id,
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)
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record_prediction_review(
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db,
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tenant_id=tenant_id,
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source_type="gstr2b",
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source_record_id=reviewed.id,
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final_nature_id=reviewed.final_nature_id,
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user_id=user_id,
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)
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return reviewed
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def bulk_confirm(db, *, tenant_id, client_id, purchase_ids, user_id):
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ids=sorted({int(x) for x in purchase_ids if str(x).isdigit() and int(x)>0})
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if not ids: raise ValueError("Select at least one high-confidence purchase.")
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rows=list(db.execute(select(AccountingGSTR2BPurchase).where(AccountingGSTR2BPurchase.tenant_id==tenant_id,AccountingGSTR2BPurchase.client_id==client_id,AccountingGSTR2BPurchase.id.in_(ids))).scalars().all())
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by_id={r.id:r for r in rows}
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if len(by_id)!=len(ids): raise ValueError("One or more selected purchases are outside this client scope.")
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completed=0
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for pid in ids:
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row=by_id[pid]
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if row.review_status=="reviewed": continue
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if not row.suggested_nature_id or int(row.suggested_confidence or 0)<85: raise ValueError(f"Invoice {row.invoice_number} is not eligible for high-confidence bulk confirmation.")
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_validate_choice(db,tenant_id=tenant_id,client_id=client_id,purchase=row,nature_id=row.suggested_nature_id,ledger_name=row.suggested_ledger_name or "")
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reviewed = review_purchase(db,row=row,final_nature_id=int(row.suggested_nature_id),final_ledger_name=row.suggested_ledger_name or "",user_id=user_id)
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mark_review_outcome(
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db,
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tenant_id=tenant_id,
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source_type="gstr2b",
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source_record_id=reviewed.id,
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final_nature_id=reviewed.final_nature_id,
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final_ledger_name=reviewed.final_ledger_name,
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user_id=user_id,
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)
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record_prediction_review(
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db,
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tenant_id=tenant_id,
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source_type="gstr2b",
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source_record_id=reviewed.id,
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final_nature_id=reviewed.final_nature_id,
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user_id=user_id,
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)
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completed+=1
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return completed
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def ai_assist_one(db, *, tenant_id, client_id, purchase_id, user_id):
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row = db.execute(select(AccountingGSTR2BPurchase).where(
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AccountingGSTR2BPurchase.id == int(purchase_id),
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AccountingGSTR2BPurchase.tenant_id == int(tenant_id),
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AccountingGSTR2BPurchase.client_id == int(client_id),
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)).scalar_one_or_none()
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if not row:
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raise ValueError("Purchase record was not found.")
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return run_ai_assist_purchase(db, row=row, user_id=user_id)
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def internal_model_predict_one(db, *, tenant_id, client_id, purchase_id, force_shadow=True):
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row = db.execute(select(AccountingGSTR2BPurchase).where(
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AccountingGSTR2BPurchase.id == int(purchase_id),
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AccountingGSTR2BPurchase.tenant_id == int(tenant_id),
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AccountingGSTR2BPurchase.client_id == int(client_id),
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)).scalar_one_or_none()
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if not row:
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raise ValueError("Purchase record was not found.")
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return predict_purchase(db, row=row, force_shadow=force_shadow)
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