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1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
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8192834f31 |
291
extraction.py
291
extraction.py
@@ -298,14 +298,157 @@ Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"n_ogc":"","date_concertation":"","argumentaire_medecin_controleur":""}\
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{"n_ogc":"","date_concertation":"","argumentaire_medecin_controleur":""}\
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"""
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"""
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PROMPT_SEJOUR_MANUSCRIT = """\
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Tu es un assistant d'extraction de données médicales.
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Cette page est intitulée "Séjour d'hospitalisation complète".
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Elle comporte deux colonnes de texte entièrement manuscrit :
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- Colonne gauche : "Commentaires du médecin contrôleur"
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- Colonne droite : "Commentaires du médecin du DIM"
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RÈGLES STRICTES :
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- Le texte peut déborder largement EN DESSOUS du tableau et légèrement sur les côtés des colonnes : inclure TOUT le texte visible de chaque colonne, y compris celui qui dépasse les bordures.
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- Retranscrire le texte manuscrit tel quel, y compris abréviations et codes médicaux.
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- Pour attribuer un texte débordant à la bonne colonne : le texte débordant d'une colonne lui appartient même s'il dépasse physiquement le cadre.
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- Si une colonne est illisible ou vide, retourner "".
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Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"commentaire_medecin_controleur":"","commentaire_medecin_dim":""}\
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"""
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PROMPTS = {
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PROMPTS = {
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"FICHE_RECUEIL": PROMPT_FICHE_RECUEIL,
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"FICHE_RECUEIL": PROMPT_FICHE_RECUEIL,
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"ELEMENTS_PREUVE": PROMPT_ELEMENTS_PREUVE,
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"SEJOUR_MANUSCRIT": PROMPT_SEJOUR_MANUSCRIT,
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"FICHE_ADMIN_2_2": PROMPT_FICHE_ADMIN_2_2,
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"ELEMENTS_PREUVE": PROMPT_ELEMENTS_PREUVE,
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"FICHE_ADMIN_1_2": PROMPT_FICHE_ADMIN_1_2,
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"FICHE_ADMIN_2_2": PROMPT_FICHE_ADMIN_2_2,
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"FICHE_ADMIN_1_2": PROMPT_FICHE_ADMIN_1_2,
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}
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}
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SKIP_TYPES = {"SEJOUR_MANUSCRIT", "FICHE_CONCERTATION_VIDE", "AUTRE"}
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SKIP_TYPES = {"FICHE_CONCERTATION_VIDE", "AUTRE"}
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# ─── Découpage zones FICHE_RECUEIL ───────────────────────────────────────────
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def crop_zone(img: Image.Image, y_start: float, y_end: float) -> Image.Image:
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W, H = img.size
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return img.crop((0, int(y_start * H), W, int(y_end * H)))
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PROMPT_RECUEIL_Z1 = """\
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Tu es un assistant d'extraction de données médicales.
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Extrait les informations d'en-tête et des tableaux "Données du séjour" et "Données du RUM"
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de cette portion de fiche médicale de recueil du praticien conseil.
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RÈGLES STRICTES :
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- Si un champ n'a pas de valeur clairement visible, retourner "".
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- Ne jamais deviner, inférer ou compléter un champ absent.
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- Le champ "provenance" est très souvent vide : ne le remplir QUE si une valeur est explicitement imprimée.
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- Le tableau "Données du séjour" contient ces colonnes DANS CET ORDRE EXACT, de gauche à droite :
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Age(ans) | Age(jours) | Sexe | Délai dern. règles | Age gestation | Poids d'entrée |
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Durée de séjour | Mode d'entrée | Provenance | Mode de sortie | Destination |
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Nb séances | Nb RUM | Nb j EXH | Type EXB | Nb j EXB
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RÈGLE ABSOLUE : lire chaque valeur dans sa colonne uniquement. Si une colonne est vide, retourner "".
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Ne jamais décaler les valeurs vers la gauche pour compenser une cellule vide.
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Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"n_ogc":"","etablissement":"","finess":"","date_debut_controle":"","n_champ":"","libelle_champ":"","dossier_manquant":"","date_debut_sejour":"","date_fin_sejour":"",
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"sejour_etab":{"age_ans":"","age_jours":"","sexe":"","poids_entree":"","duree_sejour":"","mode_entree":"","provenance":"","mode_sortie":"","destination":"","nb_seances":"","nb_rum":"","nb_j_exh":"","type_exb":"","nb_j_exb":""},
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"sejour_reco":{"age_ans":"","age_jours":"","sexe":"","poids_entree":"","duree_sejour":"","mode_entree":"","provenance":"","mode_sortie":"","destination":"","nb_seances":"","nb_rum":"","nb_j_exh":"","type_exb":"","nb_j_exb":""},
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"rum_etab":{"n_rum":"","lits_dedies_sp":"","um":"","igs_ii":"","duree_rum_debut":"","duree_rum_fin":"","nature_suppl":"","nb_suppl":""},
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"rum_reco":{"n_rum":"","lits_dedies_sp":"","um":"","igs_ii":"","duree_rum_debut":"","duree_rum_fin":"","nature_suppl":"","nb_suppl":""}}\
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"""
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PROMPT_RECUEIL_Z2 = """\
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Tu es un assistant d'extraction de données médicales.
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Extrait uniquement les lignes DP et DR de la section "Codage de l'Établissement"
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et leur colonne "Recodage" correspondante.
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RÈGLES STRICTES :
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- Le formulaire comporte exactement UNE ligne pour le DP et UNE ligne pour le DR.
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- Pour chaque ligne : si la colonne "Recodage" en face est vide sur le document, retourner "" pour dp_reco/dr_reco.
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- Si la ligne DR est entièrement vide sur le document, retourner {"code":"","libelle":""} pour dr_etab et "" pour dr_reco.
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- Ne jamais copier le code d'une autre ligne dans DP ou DR.
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Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"dp_etab":{"code":"","libelle":""},"dr_etab":{"code":"","libelle":""},"dp_reco":{"code":""},"dr_reco":{"code":""}}\
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"""
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PROMPT_RECUEIL_Z3 = """\
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Tu es un assistant d'extraction de données médicales.
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Extrait toutes les lignes DAS et Actes de cette section de la fiche médicale de recueil.
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RÈGLES STRICTES :
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- Extraire TOUTES les lignes non vides, sans limite de nombre.
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- Les diagnostics (codes CIM-10 courts, ex: R33, E43, Z515) vont dans "das_etab" / "das_reco".
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- Les actes (codes CCAM longs, 7+ caractères commençant par lettres, ex: JDPE002, NJFA008) vont dans "actes_etab" / "actes_reco".
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- Ne jamais mettre un code CCAM dans das_etab, ni un code CIM-10 dans actes_etab.
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- Si la colonne "Recodage" d'une ligne est vide, ne pas créer d'entrée dans das_reco/actes_reco pour cette ligne.
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- Ne pas retourner les lignes entièrement vides.
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Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"das_etab":[{"code":"","niveau":"","libelle":""}],"actes_etab":[{"code":"","niveau":"","libelle":""}],"das_reco":[{"code":"","niveau":""}],"actes_reco":[{"code":"","niveau":""}]}\
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"""
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PROMPT_RECUEIL_Z4 = """\
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Tu es un assistant d'extraction de données médicales.
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Extrait les informations de la barre GHM/GHS et de la zone décision de cette portion de fiche médicale.
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RÈGLES STRICTES :
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- Pour "se_coche" : retourner "SE1", "SE2", "SE3" ou "SE4" si une case est explicitement cochée, sinon "". Ce champ est TRÈS SOUVENT vide.
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- Pour les valeurs GHS (nombres) : retourner uniquement les chiffres sans point ni espace (ex: "4169" et non "4.169").
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- Pour "accord_desaccord" : retourner "accord" ou "désaccord" selon la case cochée.
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- Pour "atu", "ffm", "fsd" : retourner "oui" si la case est cochée, "" sinon.
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- Si un champ est absent ou illisible, retourner "".
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Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après.
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{"ghm_etab":"","ghs_etab":"","ghm_reco":"","ghs_reco":"","recodage_impactant_facturation":"","ghs_injustifie":"","se_coche":"","atu":"","ffm":"","fsd":"","accord_desaccord":"","decision_finale":"","nom_praticien_conseil":""}\
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"""
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# (y_start, y_end, prompt, num_predict) — légère superposition aux jointures pour ne pas couper une ligne
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# Z2 finit à 0.415 pour inclure les lignes DP+DR qui sont sous le header "Codage"
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# Z4 commence à 0.822 pour capturer la barre GHM/GHS qui précède les cases SE
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RECUEIL_ZONES = [
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(0.000, 0.325, PROMPT_RECUEIL_Z1, 8192),
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(0.310, 0.415, PROMPT_RECUEIL_Z2, 3000),
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(0.358, 0.815, PROMPT_RECUEIL_Z3, 8192),
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# Z4 commence à 0.800 pour absorber les décalages de scan sur la ligne GHM/GHS
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(0.800, 1.000, PROMPT_RECUEIL_Z4, 3000),
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]
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def _ask_zone(zone_img: Image.Image, prompt: str, num_predict: int,
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timing_record: dict | None) -> dict:
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"""Appelle ask_vision sur une zone, parse le JSON, gère un retry si nécessaire."""
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raw = ask_vision(prompt, zone_img, timeout=240, num_predict=num_predict,
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timing_record=timing_record)
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data = extract_json(raw)
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if data is None:
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retry_prompt = (
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"Ta réponse précédente n'était pas un JSON valide. "
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"Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après, "
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"sans bloc ```json```. Voici le schéma attendu :\n\n" + prompt
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)
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raw2 = ask_vision(retry_prompt, zone_img, timeout=240, num_predict=num_predict,
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timing_record=timing_record)
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data = extract_json(raw2)
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return data or {}
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def extract_fiche_recueil_zones(img: Image.Image,
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timing_record: dict | None = None) -> tuple[dict, list]:
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"""
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Extrait une FICHE_RECUEIL par découpage en 4 zones.
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Retourne (merged_data, zones_timing).
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"""
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merged: dict = {}
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zones_timing: list = []
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for idx, (y0, y1, prompt, num_pred) in enumerate(RECUEIL_ZONES, start=1):
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t0 = time.time()
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zone_img = crop_zone(img, y0, y1)
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try:
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data = _ask_zone(zone_img, prompt, num_pred, timing_record)
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except Exception as e:
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print(f" ⚠ Zone {idx}/4 erreur : {e}")
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data = {}
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elapsed = round(time.time() - t0, 2)
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zones_timing.append({"zone": idx, "duree_s": elapsed})
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print(f" → Zone {idx}/4 OK ({elapsed:.1f}s)")
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merged.update(data)
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return merged, zones_timing
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# ─── Traitement d'un PDF ──────────────────────────────────────────────────────
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# ─── Traitement d'un PDF ──────────────────────────────────────────────────────
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@@ -420,15 +563,24 @@ def _normalize_result(result: dict) -> None:
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# se_coche : normaliser "1"→"SE1", rejeter toute valeur non SE1-4
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# se_coche : normaliser "1"→"SE1", rejeter toute valeur non SE1-4
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se_raw = str(d.get("se_coche", "")).strip()
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se_raw = str(d.get("se_coche", "")).strip()
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if se_raw.upper() in {"SE1", "SE2", "SE3", "SE4"}:
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if se_raw.upper() in {"SE1", "SE2", "SE3", "SE4"}:
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# Format déjà correct
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d["se_coche"] = se_raw.upper()
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d["se_coche"] = se_raw.upper()
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elif se_raw in {"1", "2", "3", "4"}:
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elif se_raw in {"1", "2", "3", "4"}:
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# Chiffre seul = ambigu, le modèle confond avec le rang d'un DAS → vider
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d["se_coche"] = ""
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d["se_coche"] = ""
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elif se_raw:
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elif se_raw:
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# Valeur inattendue (ex: "accord", "désaccord") → vider
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d["se_coche"] = ""
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d["se_coche"] = ""
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# accord_desaccord : forcer minuscule + alias orthographiques
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acc = str(d.get("accord_desaccord", "")).strip().lower()
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acc = acc.replace("é", "e").replace("desaccord", "désaccord")
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if acc in {"accord", "désaccord"}:
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d["accord_desaccord"] = acc
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elif acc:
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d["accord_desaccord"] = ""
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# decision_finale : forcer minuscule
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df = str(d.get("decision_finale", "")).strip().lower()
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d["decision_finale"] = df
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if ptype in ("FICHE_ADMIN_2_2", "FICHE_ADMIN_1_2"):
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if ptype in ("FICHE_ADMIN_2_2", "FICHE_ADMIN_1_2"):
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for date_field in ("date_concertation",):
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for date_field in ("date_concertation",):
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if d.get(date_field):
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if d.get(date_field):
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@@ -611,62 +763,75 @@ def process_pdf(pdf_path: Path) -> tuple[dict, dict]:
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print(" → Extraction en cours...")
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print(" → Extraction en cours...")
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t0 = time.time()
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t0 = time.time()
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try:
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num_predict = 12000 if page_type == "FICHE_RECUEIL" else 8192
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raw = ask_vision(PROMPTS[page_type], img, timeout=240,
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num_predict=num_predict, timing_record=timing)
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except Exception as e:
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print(f" ⚠ Erreur extraction : {e}")
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duree_ext = round(time.time() - t0, 2)
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page_timing["duree_extraction_s"] = duree_ext
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page_timing["statut"] = "erreur_extraction"
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page_timing["erreur"] = str(e)
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timing["erreurs"].append({"page": i, "phase": "extraction", "type": page_type, "message": str(e)})
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timing["pages"].append(page_timing)
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result["pages_traitees"].append({"page": i, "type": page_type,
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"data": {"erreur": str(e)}})
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continue
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duree_ext = round(time.time() - t0, 2)
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if page_type == "FICHE_RECUEIL":
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page_timing["duree_extraction_s"] = duree_ext
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print(f" → Réponse reçue ({duree_ext:.1f}s)")
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data = extract_json(raw)
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if data is None:
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print(f" ⚠ JSON non parsable — retry en cours...")
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retry_prompt = (
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"Ta réponse précédente n'était pas un JSON valide. "
|
|
||||||
"Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après, "
|
|
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"sans bloc ```json```. Voici le schéma attendu :\n\n"
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+ PROMPTS[page_type]
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)
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try:
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try:
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raw2 = ask_vision(retry_prompt, img, timeout=240, num_predict=12000,
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data, zones_t = extract_fiche_recueil_zones(img, timing_record=timing)
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timing_record=timing)
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page_timing["duree_extraction_s"] = round(time.time() - t0, 2)
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data = extract_json(raw2)
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page_timing["zones_timing"] = zones_t
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page_timing["statut"] = "ok"
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except Exception as e:
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except Exception as e:
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print(f" ⚠ Erreur retry : {e}")
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print(f" ⚠ Erreur extraction zones : {e}")
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data = None
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page_timing["duree_extraction_s"] = round(time.time() - t0, 2)
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page_timing["statut"] = "erreur_extraction"
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if data is None:
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page_timing["erreur"] = str(e)
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print(f" ⚠ Retry échoué — raw_response conservé")
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timing["erreurs"].append({"page": i, "phase": "extraction", "type": page_type, "message": str(e)})
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page_timing["statut"] = "json_non_parsable"
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timing["pages"].append(page_timing)
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timing["erreurs"].append({
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result["pages_traitees"].append({"page": i, "type": page_type, "data": {"erreur": str(e)}})
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"page": i, "phase": "parsing_json", "type": page_type,
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continue
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"message": f"JSON non parsable après retry : {raw[:100]}",
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"retry": True,
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})
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data = {"raw_response": raw}
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else:
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print(f" ✓ Retry réussi")
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page_timing["statut"] = "ok_after_retry"
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timing["erreurs"].append({
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"page": i, "phase": "parsing_json", "type": page_type,
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"message": "JSON non parsable au 1er appel, corrigé par retry",
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"retry": True, "retry_ok": True,
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})
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else:
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else:
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page_timing["statut"] = "ok"
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try:
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raw = ask_vision(PROMPTS[page_type], img, timeout=240,
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num_predict=8192, timing_record=timing)
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except Exception as e:
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print(f" ⚠ Erreur extraction : {e}")
|
||||||
|
page_timing["duree_extraction_s"] = round(time.time() - t0, 2)
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page_timing["statut"] = "erreur_extraction"
|
||||||
|
page_timing["erreur"] = str(e)
|
||||||
|
timing["erreurs"].append({"page": i, "phase": "extraction", "type": page_type, "message": str(e)})
|
||||||
|
timing["pages"].append(page_timing)
|
||||||
|
result["pages_traitees"].append({"page": i, "type": page_type, "data": {"erreur": str(e)}})
|
||||||
|
continue
|
||||||
|
|
||||||
|
page_timing["duree_extraction_s"] = round(time.time() - t0, 2)
|
||||||
|
print(f" → Réponse reçue ({page_timing['duree_extraction_s']:.1f}s)")
|
||||||
|
|
||||||
|
data = extract_json(raw)
|
||||||
|
if data is None:
|
||||||
|
print(f" ⚠ JSON non parsable — retry en cours...")
|
||||||
|
retry_prompt = (
|
||||||
|
"Ta réponse précédente n'était pas un JSON valide. "
|
||||||
|
"Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant ni après, "
|
||||||
|
"sans bloc ```json```. Voici le schéma attendu :\n\n"
|
||||||
|
+ PROMPTS[page_type]
|
||||||
|
)
|
||||||
|
try:
|
||||||
|
raw2 = ask_vision(retry_prompt, img, timeout=240, num_predict=12000,
|
||||||
|
timing_record=timing)
|
||||||
|
data = extract_json(raw2)
|
||||||
|
except Exception as e:
|
||||||
|
print(f" ⚠ Erreur retry : {e}")
|
||||||
|
data = None
|
||||||
|
|
||||||
|
if data is None:
|
||||||
|
print(f" ⚠ Retry échoué — raw_response conservé")
|
||||||
|
page_timing["statut"] = "json_non_parsable"
|
||||||
|
timing["erreurs"].append({
|
||||||
|
"page": i, "phase": "parsing_json", "type": page_type,
|
||||||
|
"message": f"JSON non parsable après retry : {raw[:100]}",
|
||||||
|
"retry": True,
|
||||||
|
})
|
||||||
|
data = {"raw_response": raw}
|
||||||
|
else:
|
||||||
|
print(f" ✓ Retry réussi")
|
||||||
|
page_timing["statut"] = "ok_after_retry"
|
||||||
|
timing["erreurs"].append({
|
||||||
|
"page": i, "phase": "parsing_json", "type": page_type,
|
||||||
|
"message": "JSON non parsable au 1er appel, corrigé par retry",
|
||||||
|
"retry": True, "retry_ok": True,
|
||||||
|
})
|
||||||
|
else:
|
||||||
|
page_timing["statut"] = "ok"
|
||||||
|
|
||||||
timing["pages"].append(page_timing)
|
timing["pages"].append(page_timing)
|
||||||
result["pages_traitees"].append({"page": i, "type": page_type, "data": data})
|
result["pages_traitees"].append({"page": i, "type": page_type, "data": data})
|
||||||
@@ -705,7 +870,8 @@ def flatten(result: dict) -> dict:
|
|||||||
row["dr_reco_code"] = (d.get("dr_reco") or {}).get("code", "")
|
row["dr_reco_code"] = (d.get("dr_reco") or {}).get("code", "")
|
||||||
for k in ["ghm_etab","ghs_etab","ghm_reco","ghs_reco",
|
for k in ["ghm_etab","ghs_etab","ghm_reco","ghs_reco",
|
||||||
"recodage_impactant_facturation","ghs_injustifie",
|
"recodage_impactant_facturation","ghs_injustifie",
|
||||||
"se_coche","atu","ffm","fsd","accord_desaccord","nom_praticien_conseil"]:
|
"se_coche","atu","ffm","fsd","accord_desaccord",
|
||||||
|
"decision_finale","nom_praticien_conseil"]:
|
||||||
row[k] = d.get(k, "")
|
row[k] = d.get(k, "")
|
||||||
general_done = True
|
general_done = True
|
||||||
# ── Comptages et durées agrégés sur tous les RUM ──
|
# ── Comptages et durées agrégés sur tous les RUM ──
|
||||||
@@ -736,6 +902,9 @@ def flatten(result: dict) -> dict:
|
|||||||
elif ptype == "FICHE_ADMIN_1_2":
|
elif ptype == "FICHE_ADMIN_1_2":
|
||||||
row["admin12_date_concertation"] = d.get("date_concertation", "")
|
row["admin12_date_concertation"] = d.get("date_concertation", "")
|
||||||
row["admin12_argumentaire"] = d.get("argumentaire_medecin_controleur", "")
|
row["admin12_argumentaire"] = d.get("argumentaire_medecin_controleur", "")
|
||||||
|
elif ptype == "SEJOUR_MANUSCRIT":
|
||||||
|
row["sejour_ms_controleur"] = d.get("commentaire_medecin_controleur", "")
|
||||||
|
row["sejour_ms_dim"] = d.get("commentaire_medecin_dim", "")
|
||||||
|
|
||||||
# ── RÈGLE MÉTIER GHS FINAL ─────────────────────────────────────────────
|
# ── RÈGLE MÉTIER GHS FINAL ─────────────────────────────────────────────
|
||||||
# ghs_final_apres_concertation est manuscrit et souvent mal lu.
|
# ghs_final_apres_concertation est manuscrit et souvent mal lu.
|
||||||
|
|||||||
@@ -140,6 +140,19 @@ def _normalize_keys(flat: dict) -> dict:
|
|||||||
return {k.replace(".rang", ".niveau"): v for k, v in flat.items()}
|
return {k.replace(".rang", ".niveau"): v for k, v in flat.items()}
|
||||||
|
|
||||||
|
|
||||||
|
_LOWER_FIELDS = {"accord_desaccord", "avis_dim_final", "decision_finale"}
|
||||||
|
|
||||||
|
def _norm_values(flat: dict) -> dict:
|
||||||
|
"""Normalise en minuscule les champs textuels dont la casse varie entre extraction et correction."""
|
||||||
|
out = {}
|
||||||
|
for k, v in flat.items():
|
||||||
|
field = k.split(".")[-1]
|
||||||
|
if field in _LOWER_FIELDS and isinstance(v, str):
|
||||||
|
v = v.strip().lower().replace("desaccord", "désaccord")
|
||||||
|
out[k] = v
|
||||||
|
return out
|
||||||
|
|
||||||
|
|
||||||
def _get_cat(key: str, ptype: str = "") -> str:
|
def _get_cat(key: str, ptype: str = "") -> str:
|
||||||
k = key.lower()
|
k = key.lower()
|
||||||
if ptype == "ELEMENTS_PREUVE":
|
if ptype == "ELEMENTS_PREUVE":
|
||||||
@@ -210,8 +223,8 @@ def compare_extractions(orig_list, corr_list):
|
|||||||
ep_counters["json_non_parsable"]["dossiers"].add(fichier)
|
ep_counters["json_non_parsable"]["dossiers"].add(fichier)
|
||||||
continue
|
continue
|
||||||
|
|
||||||
o_flat = _normalize_keys(_flatten(od))
|
o_flat = _norm_values(_normalize_keys(_flatten(od)))
|
||||||
c_flat = _normalize_keys(_flatten(cd))
|
c_flat = _norm_values(_normalize_keys(_flatten(cd)))
|
||||||
all_keys = set(o_flat) | set(c_flat)
|
all_keys = set(o_flat) | set(c_flat)
|
||||||
|
|
||||||
for k in all_keys:
|
for k in all_keys:
|
||||||
|
|||||||
Binary file not shown.
4145
output/extraction_ogc_raw_qwen (3).json
Normal file
4145
output/extraction_ogc_raw_qwen (3).json
Normal file
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -107,7 +107,7 @@ endobj
|
|||||||
endobj
|
endobj
|
||||||
14 0 obj
|
14 0 obj
|
||||||
<<
|
<<
|
||||||
/Author (\(anonymous\)) /CreationDate (D:20260421112058+02'00') /Creator (\(unspecified\)) /Keywords () /ModDate (D:20260421112058+02'00') /Producer (ReportLab PDF Library - www.reportlab.com)
|
/Author (\(anonymous\)) /CreationDate (D:20260427123928+02'00') /Creator (\(unspecified\)) /Keywords () /ModDate (D:20260427123928+02'00') /Producer (ReportLab PDF Library - www.reportlab.com)
|
||||||
/Subject (\(unspecified\)) /Title (\(anonymous\)) /Trapped /False
|
/Subject (\(unspecified\)) /Title (\(anonymous\)) /Trapped /False
|
||||||
>>
|
>>
|
||||||
endobj
|
endobj
|
||||||
@@ -118,59 +118,59 @@ endobj
|
|||||||
endobj
|
endobj
|
||||||
16 0 obj
|
16 0 obj
|
||||||
<<
|
<<
|
||||||
/Filter [ /ASCII85Decode /FlateDecode ] /Length 2001
|
/Filter [ /ASCII85Decode /FlateDecode ] /Length 1990
|
||||||
>>
|
>>
|
||||||
stream
|
stream
|
||||||
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|
||||||
endobj
|
endobj
|
||||||
17 0 obj
|
17 0 obj
|
||||||
<<
|
<<
|
||||||
/Filter [ /ASCII85Decode /FlateDecode ] /Length 1684
|
/Filter [ /ASCII85Decode /FlateDecode ] /Length 1667
|
||||||
>>
|
>>
|
||||||
stream
|
stream
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trailer
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trailer
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<<
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<<
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||||||
/ID
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% ReportLab generated PDF document -- digest (http://www.reportlab.com)
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>>
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startxref
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16736
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%%EOF
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Reference in New Issue
Block a user