Update app.py

app.py

@@ -588,172 +588,128 @@ def build_outputs(results, descriptions, result_details, plate_number):
 
 app = FastAPI()
 
-@app.get("/")
-def greet_json():
+@app.post("/")
+def greet_json(
+    message : str, 
+    threshold : float = 0.0005,
+    tarif_pkb : float = 0.015,
+    tarif_bbnkb : float = 0.1,
+):
     global codes_emb
     global undetected
 
     undetected_code = undetected[:3]
-
-    # if history and history[-1][-1][21:24] == undetected_code: 
-    #     list_his = ""
-    #     for his in history[::-1]:
-    #         if his[-1][21:24] != undetected_code:
-    #             break
-    #         list_his = his[0] + "\n" + list_his
-
-    #     message += "\n" + list_his
     
-    # pattern = r'\b([A-Z]{1,2})\s?(\d{4})\s?([A-Z]{3})\b'
-    # pattern = r'\b([A-Z]{1,2})\s?(\d{4})\s?([A-Z]{1,3})\b'
-    pattern = r'\b([A-Za-z]{1,2})\s?(\d{4})\s?([A-Za-z]{1,3})\b'
+    # tarif_pkb = 1.5/100
+    # tarif_bbnkb = 0.1
 
+    pattern = r'\b([A-Za-z]{1,2})\s?(\d{2,4})\s?([A-Za-z]{1,3})\b'
+    
     matches = re.findall(pattern, message)
-
+    
     plates = [" ".join(x).upper() for i,x in enumerate(matches)]
 
-    plate_numbers = ", ".join(plates)
 
-    # if model.config._name_or_path in model_ids[-2:]:
     if type(model) == CrossEncoder:
-        # documents = [v["name"] for v in detail_perhitungan.values()]
-        sentence_pairs = [[message, v["name"]] for v in detail_perhitungan.values()]
-        # sentence_pairs = [[message, doc] for doc in documents]
+        sentence_pairs = [[message, v[6:]] for v in codes]
         scores = model.predict(sentence_pairs, convert_to_tensor=True)
-        weights = [1,1,1,1,1,1,1,1,1]
-        # scores = [x["score"] for x in model.rank(message, documents)]
+        weights = [9,8]
     else:
         text_emb = model.encode(message)
         scores = cos_sim(codes_emb, text_emb).mean(axis=-1)#[:,0]
-        weights = [19,8,7,6,5,4,3,2,1]
-
+        weights = [11,9]
+        
     scores_argsort = scores.argsort(descending=True)
-    
-
-    # if n_num == 0:
-    #     std = scores.std()
-    # else:
-    #     std = 0
-    if n_num == 0:
-        # w_avg = np.average(scores[scores_argsort].numpy(), weights=range(len(scores),0,-1))
-        w_avg = np.average(scores[scores_argsort].numpy(), weights=weights)
-    else:
-        w_avg = 9999
-    #[::-1]
-
-    if is_multiple:
-        request_details = []
-        request_numbers = []
-        request_scores = []
-        # request_undetected = False
-        # for i,score in enumerate(scores):
-        if scores[scores_argsort[0]] < threshold:
-            request_details.append(undetected[6:])
-            request_numbers.append(undetected_code)
-        else:
-            for i in scores_argsort:
-                # if scores[scores_argsort[0]] - std <= scores[i]:
-                if scores[i] > w_avg:
-                    request_details.append(codes[i][6:])
-                    request_numbers.append(codes[i][:3])
-                    request_scores.append(str( round(scores[i].tolist(), 3) ) )
-                else:
-                    if len(request_scores) >= n_num:
-                        break
-                    if scores[i] > threshold:
-                        request_details.append(codes[i][6:])
-                        request_numbers.append(codes[i][:3])
-                        request_scores.append(str( round(scores[i].tolist(), 3) ) )
-            
-
-        request_numbers_copy = request_numbers
-        request_details_copy = request_details
-
-        request_numbers = "\n".join(request_numbers)
-        request_details = "\n".join(request_details)
-        request_scores = "\n".join(request_scores)
-
-        # if len(request_numbers_copy) > 0:
-        #     for code, detail in zip(request_numbers_copy, request_details_copy):
-        #         kode_mohon = detail_perhitungan.get(code)
-        #         formula = kode_mohon.get("formula")
-        #         description = inspect.getsource(formula).split(":", 2)[-1].strip()
-
-        # if request_undetected and len(plates) == 0:
-            # + f"\n\nConfidence score:\n{request_scores}"
-            # return "Request code number:\n" + request_numbers + "\n\nRequest detail:\n" + request_details + "\n\nPlate numbers: " + plate_numbers
-        print(request_scores)
-        out = ""
-        for plate in plates:
-            results, descriptions, result_details = [], [], []
-            for code in request_numbers_copy:
-                result, description, result_detail = get_calculation(code, plate)
-
-                if result != None:
-                    results.append(result)
-                if descriptions != None:
-                    descriptions.append(description)
-                    result_details.append(result_detail)
-
-            if results:
-                out += "\n\n" + build_outputs(results, descriptions, result_details, plate)
-            elif vehicle_tax_info.get(plate):
-                out += "\n\n" + build_output_vehicle(plate)
-
-        if out == "":
-            descriptions, result_details = [], []
-            for code in request_numbers_copy:
-                result, description, result_detail = get_calculation(code, "")
-                if description != None:
-                    descriptions.append(description)
-                    result_details.append(result_detail)
-            if descriptions:
-                out += "\n\n" + build_output_formula(descriptions, result_details)
-            else:
-                return "Request code number: " + request_numbers + "\nRequest detail: " + request_details + "\nPlate numbers: " + plate_numbers
-
-        return {"results":out}
-
-        # result, description, result_detailget_calculation(request_code, plate_number)
-
-
-
-    s_max = scores.argmax()
-
-    if scores[s_max] < threshold:
-        # request_code = "033 - Other/Undetected"
-        request_code = undetected
-    else:
-        request_code = codes[scores.argmax()]
-        # "{:.2f}".format(a)
+    w_avg = np.average(scores[scores_argsort].numpy(), weights=weights)
 
-    # out = "Request code number: " + request_code[:3] + "\nRequest detail: " + request_code[6:] + f"\nConfidence score: {round(scores[s_max].tolist(),3)}" + "\nPlate numbers: " + plate_numbers
 
     out = ""
-    for plate in plates:
-        results, descriptions, result_details = [], [], []
-        result, description, result_detail = get_calculation(request_code[:3], plate)
-
-        if result != None:
-            results.append(result)
-            descriptions.append(description)
-            result_details.append(result_detail)
-            out += "\n\n" + build_outputs(results, descriptions, result_details, plate)
-        elif vehicle_tax_info.get(plate):
-            out += "\n\n" + build_output_vehicle(plate)
-        elif description != None:
-            descriptions.append(description)
-            result_details.append(result_detail)
-            out += "\n\n" + build_output_formula(descriptions, result_details)
-        # else:
-        #     # + f"\nConfidence score: {round(scores[s_max].tolist(),3)}"
-        #     out += "Request code number: " + request_code[:3] + "\nRequest detail: " + "\nPlate numbers: " + plate_numbers
-
-    if out == "":
-        if request_code[:3] == undetected_code:
-            return "Request code number: " + request_code[:3] + "\nRequest detail: " + request_code[6:] + "\nPlate numbers: " + plate_numbers
+    
+    for inp in plates:
+    
+        vehicle = df_sample[df_sample["no_polisi"] == inp.strip()].copy()
+        
+        if vehicle.shape[0] == 0:
+          out += f"\n\n---\nKendaraan {inp} Tidak Ditemukan\n"
         else:
-            result, description, result_detail = get_calculation(request_code[:3], "")
-            out += build_output_formula([description], [result_detail])
+          vehicle["nm_pemilik"] = censor_middle(vehicle["nm_pemilik"].values[0], -1)
+          vehicle["al_pemilik"] = censor_middle(vehicle["al_pemilik"].values[0], -1)
+            
+          v_type = vehicle["nm_jenis_kb"].values[0]
+          nilai_jual = vehicle["nilai_jual"].values[0]
+          pnbp_stnk = vehicle["pnbp_stnk"].values[0]
+          pnbp_tnkb = vehicle["pnbp_tnkb"].values[0]
+        
+          bobot = df_bobot[df_bobot["JENIS_KENDARAAN"]==v_type]["BOBOT"].values[0]
+        
+          bbnkb = tarif_bbnkb * nilai_jual * 1 # pengenaan
+          pkb = tarif_pkb * bobot * nilai_jual * 1 # pengenaan
+        
+          vehicle["nilai_jual"] = f"Rp{int(nilai_jual):,}"
+          out += "\n\n---\nDetail Kendaraan:"
+          for k,v in vehicle.iloc[0].items():
+            out += f"\n{k} \t\t: {v}"
+          # out += "\n=================================================================="
+            
+          out += "\n--"
+
+          if scores[scores_argsort[0]] < threshold:
+              continue
+
+          header_rincian = "| POKOK | DENDA | TOTAL ||\n|-:|-:|-:|:-|\n"
+          rincian = "\n\n### RINCIAN:\n\n" + header_rincian
+
+          is_rincian = False
+
+          out_k = ""
+
+          if scores[0] > w_avg:
+              out += f"\nBBNKB \t\t: {int(bbnkb):,}"
+              
+              out_k += "\nRumus Bea Balik Nama Kendaraan Bermotor (BBNKB) : TARIF x NJKB x PENGENAAN"
+              out_k += f"\nKalkulasi : {tarif_bbnkb*100}% x Rp{int(nilai_jual):,} x 100%"
+              out_k += f"\nTotal Pembayaran : Rp{int(bbnkb):,}\n"
+              rincian += f"|{int(bbnkb):,}|0|{int(bbnkb):,}|BBNKB|\n"
+              is_rincian = True
+          else:
+              bbnkb = 0
+              
+          if scores[1] > w_avg:
+              d = datetime.now().date() - vehicle["tg_akhir_pkb"].values[0]
+              d = d.days // 365
+              if d < 1:
+                  d = 1
+              # swdkllj = 35000
+              swdkllj = dict_swdkllj.get(vehicle["gol"].values[0])
+
+              out += f"\nPKB \t\t: {int(pkb*d):,}"
+              out += f"\nSWDKLLJ \t\t: {int(swdkllj*d):,}"
+              out += f"\nPNBP STNK \t\t:{int(pnbp_stnk):,}"
+              out += f"\nPNBP TNKB \t\t:{int(pnbp_tnkb):,}"
+              out += f"\nTOTAL \t\t: {int(pkb*d + swdkllj*d + pnbp_stnk + pnbp_tnkb + bbnkb):,}"
+              
+              out_k += "\nRumus Pokok Pajak Kendaraan Bermotor (PKB) : TARIF * NJKB * BOBOT * PENGENAAN * TAHUN BAYAR"
+              out_k += f"\nKalkulasi : {tarif_pkb*100}% * Rp{int(nilai_jual):,} * {bobot} * 100% * {d}"
+              out_k += f"\nTotal Pembayaran : Rp{int(pkb*d):,}\n"
+              out_k += "\nRumus Total PKB: PKB + SWDKLLJ + PNBP STNK + PNBP TNKB"
+              out_k += f"\nKalkulasi : Rp{int(pkb*d):,} + Rp{int(swdkllj*d):,} + Rp{int(pnbp_stnk):,} + Rp{int(pnbp_tnkb):,}"
+              out_k += f"\nTotal Pembayaran : Rp{int(pkb*d + swdkllj*d + pnbp_stnk + pnbp_tnkb):,}\n"
+              
+              rincian += f"|{int(pkb*d):,}|0|{int(pkb*d):,}|PKB|\n" + f"|{int(swdkllj*d):,}|0|{int(swdkllj*d):,}|SWDKLLJ|\n\n"
+              rincian_pkb = "### RINCIAN PKB:\n\n| POKOK | DENDA | TOTAL |\n|-:|-:|-:|\n"
+              rincian_swdkllj = "### RINCIAN SWDKLLJ:\n\n| POKOK | DENDA | TOTAL |\n|-:|-:|-:|\n"
+              for i in range(d):
+                  rincian_pkb += f"|{int(pkb):,}|0|{int(pkb):,}|PKB|\n"
+                  rincian_swdkllj += f"|{int(swdkllj):,}|0|{int(swdkllj):,}|PKB|\n"
+              rincian += rincian_pkb + "\n" + rincian_swdkllj
+              is_rincian = True
+          out += out_k
+          if is_rincian:
+              out += rincian
+    if not out and scores[scores_argsort[0]] >= threshold:
+        if scores[0] > w_avg:
+            out += "\nRumus Bea Balik Nama Kendaraan Bermotor (BBNKB) : TARIF x NJKB x PENGENAAN"
+        if scores[1] > w_avg:
+            out += "\nRumus Pokok Pajak Kendaraan Bermotor (PKB) : TARIF * NJKB * BOBOT * PENGENAAN"
 
     return {"results":out}