import streamlit as st import pandas as pd from datetime import datetime, date, timedelta from Analytics.AnalyseFinance import ( analyser_capacite, generer_tableau_amortissement, calculer_taux_endettement, calculer_mensualite_pret, SEUILS, ) from Analytics import vortex_params from DocumentGen.AutoPDFGeneration import generer_contrat_pret, generer_reconnaissance_dette, generer_contrat_caution from core.id_generator import generate_next_id from core.email_client import envoyer_email, get_admin_email, get_credential from core.sheets_cache import clear_sheets_cache from core import signature as sg from core import signature_service as svc from core.ui_guards import rendre_form_submit_protege, rendre_bouton_protege, marquer_fait, liberer import time import requests import base64 import os from modules.jasmine_widget import render_scoped_widget # ============================================================================ # FONCTION ISOLEE — ENVOI DES CONTRATS PAR EMAIL # ============================================================================ def envoyer_contrat_tactique(email_client, loan_data, client_data, pdf_contrat, pdf_dette, pdf_caution=None, garant_data=None): """Envoi des documents d'octroi (contrat, reconnaissance de dette, caution) : garant en CC, admin en BCC. Transport mutualise dans core.email_client.envoyer_email.""" if not email_client or "@" not in str(email_client): return False, "Adresse email invalide ou manquante." nom_client = client_data.get('Nom_Complet', 'Client') id_pret = loan_data.get('ID_Pret', 'N/A') montant_capital = loan_data.get('Montant_Capital', 0) montant_total = loan_data.get('Montant_Total', 0) offre = loan_data.get('Offre', 'Standard') html_content = f"""
CONFIRMATION D'OCTROI DE PRET

CLIENT IDENTIFIE : {nom_client}

REFERENCE DOSSIER : {id_pret}

OFFRE SOUSCRITE : {offre}

CAPITAL DEBLOQUE

{montant_capital:,.0f} XOF

MONTANT TOTAL A REMBOURSER

{montant_total:,.0f} XOF

Veuillez trouver vos documents officiels (Contrat de pret, Echeancier, Reconnaissance de dette, et l'acte de caution le cas echeant) en pieces jointes (PDF). Ces documents ont ete generes automatiquement par le systeme Vortex.

""" def _octets(pdf_obj): return pdf_obj.getvalue() if hasattr(pdf_obj, 'getvalue') else pdf_obj attachments = [ (f"Contrat_{id_pret}.pdf", _octets(pdf_contrat)), (f"Dette_{id_pret}.pdf", _octets(pdf_dette)), ] if pdf_caution: attachments.append((f"Caution_{id_pret}.pdf", _octets(pdf_caution))) cc = None if garant_data: email_garant = str(garant_data.get('Email', '')) if "@" in email_garant: cc = email_garant return envoyer_email( to=email_client, subject=f"DOCUMENTS D'OCTROI DE PRET - {id_pret}", html_content=html_content, bcc=get_admin_email(), cc=cc, attachments=attachments, sender_name="Vortex Finance", ) # ============================================================================ # GESTION DU CACHE # ============================================================================ @st.cache_data(ttl=600) def get_cached_data(_client, sheet_name, worksheet_name): try: sh = _client.open(sheet_name) ws = sh.worksheet(worksheet_name) return pd.DataFrame(ws.get_all_records()) except Exception as e: st.error(f"Erreur lors de la lecture de {worksheet_name}: {e}") return pd.DataFrame() # ============================================================================ # CSS — STYLE GOTHAM / PALANTIR ALIGNÉ SUR streamlit_app.py # ============================================================================ def apply_loans_engine_styles(): st.markdown(""" """, unsafe_allow_html=True) # ============================================================================ # COMPOSANT : SÉLECTION D'OFFRE TACTIQUE # ============================================================================ OFFRES = { "Offre Consumer Loan": { "key": "consumer", "tag": "// SEGMENT RETAIL", "desc": "Credit a la consommation destine aux particuliers.\nRemboursement hebdomadaire ou mensuel.\nMontants standards, durees courtes a moyennes.", "color": "#58a6ff" }, "Offre Découvert Privilège": { "key": "decouvert", "tag": "// SEGMENT PREMIUM", "desc": "Facilite de caisse pour clients a profil etabli.\nSouplesse de remboursement personnalisee.\nAcces prioritaire et conditions negociees.", "color": "#8a9aaa" }, "Offre Private Credit": { "key": "private", "tag": "// SEGMENT PRIVE", "desc": "Credit sur mesure pour projets d'envergure.\nMontants eleves, structuration sur-mesure.\nReserve aux profils analyses et valides.", "color": "#f39c12" } } def render_offer_selector(): """ Affiche le selecteur d'offre tactique (3 cartes HTML + boutons Streamlit). Retourne le nom de l'offre selectionnee ou None. """ if 'selected_offre' not in st.session_state: st.session_state.selected_offre = None st.markdown('// SELECTION DE L\'OFFRE', unsafe_allow_html=True) cols = st.columns(3) for col, (offre_name, meta) in zip(cols, OFFRES.items()): key = meta["key"] is_selected = st.session_state.selected_offre == offre_name card_class = f"offer-card {key} {'selected' if is_selected else ''}" indicator_class = f"offer-indicator {'active ' + key if is_selected else ''}" indicator_text = "[ SELECTIONNE ]" if is_selected else "[ SELECTIONNER ]" with col: st.markdown(f"""
{meta['tag']}
{offre_name}
{meta['desc'].replace(chr(10), '
')}
{indicator_text}
""", unsafe_allow_html=True) st.markdown(f'
', unsafe_allow_html=True) if st.button(offre_name, key=f"btn_offre_{key}"): st.session_state.selected_offre = offre_name st.rerun() st.markdown('
', unsafe_allow_html=True) if st.session_state.selected_offre: meta = OFFRES[st.session_state.selected_offre] st.markdown( f'' f'OFFRE ACTIVE : {st.session_state.selected_offre}' f'', unsafe_allow_html=True ) return st.session_state.selected_offre # ============================================================================ # MAIN FUNCTION # ============================================================================ def show_loans_engine(client, sheet_name): apply_loans_engine_styles() st.markdown('
', unsafe_allow_html=True) st.markdown("## MOTEUR FINANCIER : OCTROI DE PRET") # ── SELECTION OFFRE ──────────────────────────────────────────────────── offre_selectionnee = render_offer_selector() if not offre_selectionnee: st.markdown("""
SELECTIONNER UNE OFFRE CI-DESSUS POUR ACCEDER A LA CONFIGURATION DU PRET.
""", unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) return # ── CHARGEMENT DONNÉES ───────────────────────────────────────────────── try: sh = client.open(sheet_name) df_clients = get_cached_data(client, sheet_name, "Clients_KYC") try: df_garants = get_cached_data(client, sheet_name, "Garants_KYC") if not df_garants.empty: df_garants['search_label'] = df_garants['ID_Garant'].astype(str) + " - " + df_garants['Nom_Complet'].astype(str) except Exception as e: st.error(f"Erreur sur la feuille Garants : {e}") df_garants = pd.DataFrame() except Exception as e: st.error(f"Erreur connexion : {e}") return # ── SÉLECTION CLIENT ─────────────────────────────────────────────────── if df_clients.empty: st.error("Aucun client trouve dans la base KYC.") st.markdown('', unsafe_allow_html=True) return st.markdown('// IDENTIFICATION CIBLE', unsafe_allow_html=True) df_clients['search_label'] = df_clients['ID_Client'].astype(str) + " - " + df_clients['Nom_Complet'].astype(str) selected_client_label = st.selectbox("Rechercher une cible", [""] + df_clients['search_label'].tolist()) if not selected_client_label: st.markdown('', unsafe_allow_html=True) return client_info = df_clients[df_clients['search_label'] == selected_client_label].iloc[0] client_id = client_info['ID_Client'] try: pers_charge = int(client_info.get('Pers_Charge', 0)) except (ValueError, TypeError): pers_charge = 0 st.info(f"CIBLE : {client_info['Nom_Complet']}") with st.expander(f"SOLVABILITE // {client_info['Nom_Complet']}", expanded=True): def clean_val(val): try: return float(str(val).replace("XOF","").replace(" ","").replace(",","")) except (ValueError, TypeError) as e: from core.errors import log_swallowed log_swallowed(f"Montant illisible pour {client_info.get('ID_Client', '?')} (valeur : {val!r})", e) return 0.0 rev = clean_val(client_info['Revenus_Mensuels']) chg = clean_val(client_info['Charges_Estimees']) reste = rev - chg c1, c2, c3 = st.columns(3) c1.metric("Revenus Mensuels", f"{int(rev):,} XOF".replace(",", " ")) c2.metric("Charges Estimees", f"{int(chg):,} XOF".replace(",", " ")) delta_color = "normal" if reste > SEUILS["reste_a_vivre_min"]["acceptable"] else "inverse" c3.metric("Reste a Vivre (Net)", f"{int(reste):,} XOF".replace(",", " "), delta=f"{int(reste):,}", delta_color=delta_color) st.markdown(f"**Profession :** {client_info['Statut_Pro']} | **Ville :** {client_info['Ville']}") if pers_charge >= 1: ipf = rev / (1 + pers_charge) st.info(f"IPF (Indice de Pression Familiale) : {int(ipf):,} XOF — base de calcul ajustee ({pers_charge} pers. a charge)".replace(",", " ")) # ── SÉLECTION GARANT ─────────────────────────────────────────────────── selected_garant = None garant_id = "" st.markdown('// GARANT (OPTIONNEL)', unsafe_allow_html=True) if df_garants.empty: st.info("Aucun garant enregistre dans la base.") else: selected_garant_label = st.selectbox("Rechercher un garant (Optionnel)", [""] + df_garants['search_label'].tolist()) if selected_garant_label: garant_info = df_garants[df_garants['search_label'] == selected_garant_label].iloc[0] selected_garant = garant_info garant_id = garant_info['ID_Garant'] st.info(f"GARANT : {garant_info['Nom_Complet']}") with st.expander(f"ANALYSE CAUTION // {garant_info['Nom_Complet']}", expanded=True): rev_g = clean_val(garant_info['Revenus_Mensuels']) chg_g = clean_val(garant_info['Charges_Estimees']) g1, g2, g3 = st.columns(3) g1.metric("Revenus Garant", f"{int(rev_g):,} XOF".replace(",", " ")) g2.metric("Charges Garant", f"{int(chg_g):,} XOF".replace(",", " ")) g3.metric("Reste a Vivre", f"{int(rev_g - chg_g):,} XOF".replace(",", " ")) st.warning("ENGAGEMENT SOLIDAIRE : Le garant renonce aux benefices de discussion et de division.") # ── CONFIGURATION PRÊT ──────────────────────────────────────────────── st.markdown('// CONFIGURATION DU PRET', unsafe_allow_html=True) col_motif, col_type, col_moyen = st.columns(3) with col_motif: motif = st.selectbox("Motif du pret", [ "Commerce / Achat de stock", "Investissement", "Tresorerie professionnelle", "Lancement d'activite", "Developpement d'activite", "Agriculture / Elevage", "Transport / Logistique", "Urgence medicale", "Scolarite / Formation", "Logement / Habitat", "Reparations", "Evenements familiaux", "Voyage / Deplacement", "Consommation", "Achat d'equipement personnel", "Projet personnel", "Autre" ]) with col_type: type_pret = st.selectbox("Type de remboursement", [ "In Fine", "Mensuel - Interets", "Mensuel - Constant", "Hebdomadaire", "Personnalise" ]) with col_moyen: moyen_transfert = st.selectbox("Moyen de transfert", ["Wave", "Orange Money", "Virement"]) type_code_map = { "In Fine": "IN_FINE", "Mensuel - Interets": "MENSUEL_INTERETS", "Mensuel - Constant": "MENSUEL_CONSTANT", "Hebdomadaire": "HEBDOMADAIRE", "Personnalise": "PERSONNALISE" } type_code = type_code_map[type_pret] col1, col2, col3 = st.columns(3) montant = col1.number_input("Montant (XOF)", 10000, value=100000, step=10000) taux_hebdo = col2.number_input("Taux Hebdo (%)", 0.1, value=2.0, step=0.1) # ── VARIABLES INIT ──────────────────────────────────────────────────── duree_semaines = 0 duree_mois = 0 dates_versements = [] date_debut = date.today() date_fin = date_debut st.markdown('// SIMULATION', unsafe_allow_html=True) # ── SAISIE DE LA DUREE / DES ECHEANCES (widgets seulement) ─────────── if type_code == "IN_FINE": duree_semaines = col3.number_input("Duree (en semaines)", min_value=1, max_value=104, value=8) date_fin = date_debut + timedelta(weeks=duree_semaines) dates_versements = [date_fin] elif type_code in ("MENSUEL_INTERETS", "MENSUEL_CONSTANT"): duree_mois = col3.number_input("Duree (en mois)", min_value=1, max_value=60, value=12) date_fin = date_debut + timedelta(days=duree_mois * 30) duree_semaines = duree_mois * 4.33 dates_versements = [date_debut + timedelta(days=30 * i) for i in range(1, int(duree_mois) + 1)] elif type_code == "HEBDOMADAIRE": duree_semaines = col3.number_input("Duree (en semaines)", min_value=1, max_value=104, value=12) date_fin = date_debut + timedelta(weeks=duree_semaines) dates_versements = [date_debut + timedelta(weeks=i) for i in range(1, int(duree_semaines) + 1)] else: # PERSONNALISE st.info("Configurez les dates de versement ci-dessous") if 'dates_perso' not in st.session_state: st.session_state.dates_perso = [date.today() + timedelta(weeks=2)] col_add, _ = st.columns([1, 4]) if col_add.button("AJOUTER ECHEANCE"): st.session_state.dates_perso.append(st.session_state.dates_perso[-1] + timedelta(weeks=1)) st.rerun() dates_saisies = [] for idx, dt in enumerate(st.session_state.dates_perso): col_d, col_x = st.columns([4, 1]) new_date = col_d.date_input(f"Echeance {idx+1}", value=dt, key=f"d_{idx}", min_value=date.today()) dates_saisies.append(new_date) if col_x.button("[ X ]", key=f"del_{idx}") and len(st.session_state.dates_perso) > 1: st.session_state.dates_perso.pop(idx) st.rerun() st.session_state.dates_perso = dates_saisies dates_versements = sorted(dates_saisies) if dates_versements: date_fin = dates_versements[-1] duree_semaines = max(1, (date_fin - date_debut).days // 7) if not dates_versements: st.warning("Ajoutez au moins une echeance.") st.markdown('', unsafe_allow_html=True) return # ── CALCUL UNIQUE (meme moteur que le simulateur : frais de transfert + forfait duree min) ── df_param_regles = get_cached_data(client, sheet_name, "Parametres_Vortex") regles = vortex_params.get_regles_actuelles_depuis_df(df_param_regles) calc = calculer_mensualite_pret( type_code, montant, taux_hebdo, duree_semaines, duree_mois, nb_dates_perso=len(dates_versements), duree_minimale_semaines=regles["Regle_Duree_Minimale_Semaines"], forfait_pct=regles["Regle_Forfait_Duree_Minimale_Pct"], ) montant_total = calc["montant_total"] cout_credit = calc["cout_credit"] montant_versement = calc["mensualite"] nb_versements = calc["nb_versements"] frais_transfert = calc["frais_transfert"] forfait_applique = calc["duree_min_non_respectee"] # ── METRIQUES (valeurs issues du calcul ci-dessus) ──────────────────── libelle_versement = { "IN_FINE": "Versement unique", "MENSUEL_INTERETS": "Interets mensuels", "MENSUEL_CONSTANT": "Mensualite constante", "HEBDOMADAIRE": "Versement Hebdo", "PERSONNALISE": "Moyenne/Versement", }[type_code] if forfait_applique: st.info("Duree inferieure au minimum : forfait fixe applique.") r1, r2, r3 = st.columns(3) r1.metric(libelle_versement, f"{int(montant_versement):,} XOF".replace(",", " ")) r2.metric("Cout du credit", f"{int(cout_credit):,} XOF".replace(",", " ")) r3.metric("Montant Total", f"{int(montant_total):,} XOF".replace(",", " "), delta=f"+{int(cout_credit):,}") # ── ANALYSE CAPACITÉ ────────────────────────────────────────────────── st.markdown('// ANALYSE DE CAPACITE', unsafe_allow_html=True) analyse = analyser_capacite( type_code, montant, taux_hebdo, duree_semaines, montant_versement, nb_versements, client_info['Revenus_Mensuels'], client_info.get('Charges_Estimees', 0), montant_total, pers_charge=pers_charge ) _couleur = analyse['couleur'] _statut = analyse['statut'] st.markdown( f"" f"STATUT : {_statut}", unsafe_allow_html=True ) st.info(analyse['message']) with st.expander("DETAILS FINANCIERS"): st.markdown(analyse['details']) # ── TABLEAU D'AMORTISSEMENT ─────────────────────────────────────────── st.markdown('// TABLEAU D\'ECHEANCES', unsafe_allow_html=True) date_debut = date.today() df_amort = generer_tableau_amortissement( type_code, montant, taux_hebdo, duree_semaines, montant_versement, nb_versements, date_debut, dates_versements=dates_versements, frais_transfert=frais_transfert, forfait_fixe_pct=regles["Regle_Forfait_Duree_Minimale_Pct"] if forfait_applique else None, ) if not df_amort.empty: df_amort.insert(0, "Type", type_pret) st.dataframe(df_amort, hide_index=True, use_container_width=True) # ── TAUX D'ENDETTEMENT ──────────────────────────────────────────────── from Analytics.AnalyseFinance import calculer_taux_endettement taux_endettement = calculer_taux_endettement( type_code, montant_versement, nb_versements, duree_semaines, client_info['Revenus_Mensuels'], pers_charge=pers_charge ) st.info(f"TAUX D'ENDETTEMENT CALCULE : {taux_endettement:.2f}%") # ── VALIDATION ──────────────────────────────────────────────────────── st.markdown('// VALIDATION & OCTROI', unsafe_allow_html=True) with st.form("valid_pret"): submit = rendre_form_submit_protege("[ OCTROYER & GENERER DOCS ]", cle=f"octroi_direct_{client_id}") if submit: try: ws_prets = sh.worksheet("Prets_Master") new_id = generate_next_id(ws_prets, "PRT") row_data = [ new_id, # ID_Pret client_id, # ID_Client client_info['Nom_Complet'], # Nom_Complet offre_selectionnee, # Offre [OK] type_code, # Type_Pret motif, # Motif montant, # Montant_Capital taux_hebdo, # Taux_Hebdo round(taux_endettement, 2), # Taux_Endettement duree_semaines, # Duree_Semaines round(montant_versement), # Montant_Versement round(montant_total), # Montant_Total round(cout_credit), # Cout_Credit nb_versements, # Nb_Versements ";".join([d.strftime("%d/%m/%Y") for d in dates_versements]) if dates_versements else "", # Dates_Versements date_debut.strftime("%d/%m/%Y"), # Date_Deblocage date_fin.strftime("%d/%m/%Y"), # Date_Fin moyen_transfert, # Moyen_Transfert sg.STATUT_PRET_EN_ATTENTE, # Statut : ACTIF seulement apres signature garant_id, # ID_Garant datetime.now().strftime("%d/%m/%Y %H:%M:%S"), # Date_Creation datetime.now().strftime("%d/%m/%Y %H:%M:%S"), # Date_Update ] ws_prets.append_row(row_data) get_cached_data.clear() clear_sheets_cache() st.session_state.loan_validated = True st.session_state.loan_id = new_id st.session_state.loan_data = { "ID_Pret": new_id, "Offre": offre_selectionnee, "Montant_Capital": montant, "Montant_Total": montant_total, "Taux_Hebdo": taux_hebdo, "Taux_Endettement": taux_endettement, "Duree_Semaines": duree_semaines, "Motif": motif, "Date_Deblocage": date_debut.strftime("%d/%m/%Y"), "Date_Fin": date_fin.strftime("%d/%m/%Y"), } st.session_state.client_data = client_info.to_dict() st.session_state.garant_data = selected_garant.to_dict() if selected_garant is not None else None st.session_state.df_amort = df_amort.copy() # Signature electronique : le pret reste EN_ATTENTE_SIGNATURE (bloque) tant que le client # (et le garant) n'ont pas signe via le lien recu par email. snapshot_sig = sg.construire_snapshot( {**st.session_state.loan_data, "ID_Client": client_id, "ID_Garant": garant_id, "Type_Pret": type_code, "Montant_Versement": round(montant_versement), "Nb_Versements": nb_versements, "Cout_Credit": round(cout_credit), "Moyen_Transfert": moyen_transfert}, st.session_state.client_data, st.session_state.garant_data, df_amort) st.session_state.signature_snapshot = snapshot_sig try: st.session_state.signature_resultats = svc.lancer_signature_pret( sh, id_pret=new_id, source=svc.SOURCE_MASTER, snapshot=snapshot_sig) except Exception as exc: from core.errors import log_swallowed log_swallowed(f"Lancement de la signature du pret {new_id} echoue", exc) st.session_state.signature_resultats = [ {"role": sg.ROLE_EMPRUNTEUR, "ok": False, "detail": f"Erreur technique : {exc}", "id_signature": None}] marquer_fait(f"octroi_direct_{client_id}") st.success(f"PRET {new_id} ENREGISTRE — EN ATTENTE DE SIGNATURE — OFFRE : {offre_selectionnee}") except Exception as e: liberer(f"octroi_direct_{client_id}") st.error(f"Erreur lors de l'octroi : {e}") # ── DOCUMENTS PDF & ENVOI MAIL ──────────────────────────────────────── if st.session_state.get('loan_validated', False): st.markdown('// DOCUMENTS & TRANSMISSION', unsafe_allow_html=True) st.markdown(f"PRET **{st.session_state.loan_id}** — OFFRE : **{st.session_state.loan_data.get('Offre', '')}**") loan_data = st.session_state.loan_data client_data = st.session_state.client_data garant_data = st.session_state.garant_data df_amort_saved = st.session_state.df_amort # Génération unique des PDF en mémoire if st.session_state.get('pdf_contrat_for') != st.session_state.loan_id: for _k in ['pdf_contrat', 'pdf_dette', 'pdf_caution', 'pdf_contrat_for']: st.session_state.pop(_k, None) if 'pdf_contrat' not in st.session_state: with st.spinner("Génération des documents PDF..."): st.session_state.pdf_contrat = generer_contrat_pret(loan_data, client_data, df_amort_saved) st.session_state.pdf_dette = generer_reconnaissance_dette(loan_data, client_data) if garant_data is not None: st.session_state.pdf_caution = generer_contrat_caution(loan_data, garant_data) else: st.session_state.pdf_caution = None st.session_state.pdf_contrat_for = st.session_state.loan_id col_dl1, col_dl2, col_dl3 = st.columns(3) with col_dl1: st.download_button( "Télécharger Contrat", st.session_state.pdf_contrat, f"Contrat_{st.session_state.loan_id}.pdf", "application/pdf", use_container_width=True ) with col_dl2: st.download_button( "Télécharger Dette", st.session_state.pdf_dette, f"Dette_{st.session_state.loan_id}.pdf", "application/pdf", use_container_width=True ) with col_dl3: if st.session_state.pdf_caution: st.download_button( "Télécharger Caution", st.session_state.pdf_caution, f"Caution_{st.session_state.loan_id}.pdf", "application/pdf", use_container_width=True ) else: st.info("Aucun garant associé") st.divider() # ── Signature electronique ──────────────────────────────────────── st.markdown('// SIGNATURE ELECTRONIQUE', unsafe_allow_html=True) resultats_sig = st.session_state.get('signature_resultats') or [] if not resultats_sig: st.warning("Aucune demande de signature lancee pour ce pret.") for r in resultats_sig: if r["ok"]: st.success(f"{r['role'].title()} : lien de signature envoye par email.") else: st.error(f"{r['role'].title()} : {r['detail']}") st.caption("Le pret reste EN_ATTENTE_SIGNATURE (aucun remboursement possible) jusqu'a la signature de toutes " "les parties. Suivi, relances et renvois : module Signatures.") col_sig, col_reset = st.columns([2, 1]) with col_sig: if (not resultats_sig or any(not r["ok"] for r in resultats_sig)) and st.session_state.get('signature_snapshot'): if rendre_bouton_protege( "RELANCER L'ENVOI DES LIENS", cle=f"lock_relance_sig_{loan_data['ID_Pret']}", use_container_width=True, ): try: st.session_state.signature_resultats = svc.lancer_signature_pret( sh, id_pret=loan_data['ID_Pret'], source=svc.SOURCE_MASTER, snapshot=st.session_state.signature_snapshot) except Exception as exc: st.error(f"Erreur technique : {exc}") liberer(f"lock_relance_sig_{loan_data['ID_Pret']}") st.rerun() with col_reset: if st.button("Octroyer un nouveau prêt", use_container_width=True, key="loans_engine_nouvel_octroi"): liberer(f"octroi_direct_{client_id}") for key in ['loan_validated', 'loan_id', 'loan_data', 'client_data', 'garant_data', 'df_amort', 'pdf_contrat', 'pdf_dette', 'pdf_caution', 'pdf_contrat_for', 'dates_perso', 'selected_offre', 'signature_snapshot', 'signature_resultats']: st.session_state.pop(key, None) st.rerun() render_scoped_widget( client, sheet_name, scope_label=f"Octroi de prêt en cours — {client_info.get('Nom_Complet', client_id)}", context_data={ "client": {"id": client_id}, # pas de nom : donnee personnelle non envoyee au LLM "pret": { "offre": offre_selectionnee, "montant_xof": montant, "montant_total_xof": montant_total, "taux_hebdo_pct": taux_hebdo, "type_pret": type_code, "taux_endettement_pct": taux_endettement, "statut_analyse": _statut, }, "guide_page": ( "Moteur d'octroi : simulation puis création effective d'un nouveau prêt. L'agent " "choisit le type de remboursement et le montant, le système calcule l'échéancier, " "le taux d'endettement et un statut de capacité, puis 'OCTROYER & GENERER DOCS' " "écrit le prêt dans Prets_Master (statut ACTIF) et génère les documents contractuels." ), "definitions_champs": { "montant_xof": "Capital demandé, saisi par l'agent.", "montant_total_xof": "Capital + coût du crédit — montant total à rembourser sur toute la durée.", "taux_hebdo_pct": "Taux d'intérêt hebdomadaire saisi par l'agent.", "type_pret": ( "Mode de remboursement : IN_FINE (versement unique en fin de période, capital+intérêts) ; " "MENSUEL_INTERETS (mensualités d'intérêts seuls, capital in fine) ; " "MENSUEL_CONSTANT (mensualités constantes, capital+intérêts amortis) ; " "HEBDOMADAIRE (versements hebdomadaires constants) ; PERSONNALISE (échéancier à dates libres)." ), "taux_endettement_pct": "Charge mensuelle de ce prêt / revenus mensuels du client (ajustés des personnes à charge), en %.", "statut_analyse": "Verdict de capacité de remboursement : EXCELLENT, BON, ACCEPTABLE ou INSUFFISANT (risque élevé).", }, }, key_prefix="loans_engine", )