add ai generate suggestion
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49
services/upload_file/ai_generate.py
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49
services/upload_file/ai_generate.py
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@ -0,0 +1,49 @@
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import requests
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from typing import Dict, Any
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from core.config import GEN_AI_URL
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URL = GEN_AI_URL
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def send_metadata(payload: Dict[str, Any]) -> Dict[str, Any]:
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headers = {
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"Content-Type": "application/json",
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"API_KEY": "testsatupeta"
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}
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try:
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response = requests.post(
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f"{URL}",
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json=payload,
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headers=headers,
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)
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# response.raise_for_status()
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return response.json()
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except requests.exceptions.RequestException as e:
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return {
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"success": False,
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"error": str(e)
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}
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if __name__ == "__main__":
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# Contoh payload
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payload = {
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"nama_file_peta": "peta bencana.pdf",
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"nama_opd": "Badan Penanggulangan Bencana Daerah (BPBD)",
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"tipe_data_spasial": "Multipolygon",
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"struktur_atribut_data": {},
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"metadata": {
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"judul": "",
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"abstrak": "",
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"tujuan": "",
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"keyword": [],
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"kategori": [],
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"kategori_mapset": ""
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}
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}
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result = send_metadata(payload)
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print(result)
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@ -5,10 +5,15 @@ import geopandas as gpd
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import numpy as np
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import re
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import zipfile
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import tempfile
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import asyncio
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from pyproj import CRS
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from shapely.geometry.base import BaseGeometry
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from shapely.geometry import base as shapely_base
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from fastapi import File, Form, UploadFile, HTTPException
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from api.routers.datasets_router import cleansing_data
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from core.config import UPLOAD_FOLDER, MAX_FILE_MB, VALID_WKT_PREFIXES
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from services.upload_file.ai_generate import send_metadata
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from services.upload_file.readers.reader_csv import read_csv
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from services.upload_file.readers.reader_shp import read_shp
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from services.upload_file.readers.reader_gdb import read_gdb
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@ -16,6 +21,7 @@ from services.upload_file.readers.reader_mpk import read_mpk
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from services.upload_file.readers.reader_pdf import convert_df, read_pdf
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from services.upload_file.utils.geometry_detector import detect_and_build_geometry
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from services.upload_file.utils.geometry_detector import attach_polygon_geometry_auto
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from services.upload_file.upload_ws import report_progress
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from database.connection import engine, sync_engine
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from database.models import Base
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from pydantic import BaseModel
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@ -68,17 +74,172 @@ def detect_zip_type(zip_path: str) -> str:
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return "unknown"
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def process_data(df: pd.DataFrame, ext: str):
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# def detect_zip_type(zip_path: str) -> str:
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# files = zip_ref.namelist()
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# # -------------------------------------------------------------
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# # 1) DETECT FileGDB
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# # -------------------------------------------------------------
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# is_gdb = (
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# any(".gdb/" in f.lower() for f in files)
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# or any(f.lower().endswith(ext) for ext in
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# [".gdbtable", ".gdbtablx", ".gdbindexes", ".spx"] for f in files)
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# )
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# if is_gdb:
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# print("\n[INFO] ZIP terdeteksi berisi FileGDB.")
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# with tempfile.TemporaryDirectory() as temp_dir:
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# # extract ZIP
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# zip_ref.extractall(temp_dir)
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# # find folder *.gdb
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# gdb_path = None
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# for root, dirs, _ in os.walk(temp_dir):
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# for d in dirs:
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# if d.lower().endswith(".gdb"):
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# gdb_path = os.path.join(root, d)
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# break
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# if not gdb_path:
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# print("[ERROR] Folder .gdb tidak ditemukan.")
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# return "gdb"
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# print(f"[INFO] GDB Path: {gdb_path}")
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# # Cari seluruh file .gdbtable
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# table_files = [
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# os.path.join(gdb_path, f)
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# for f in os.listdir(gdb_path)
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# if f.lower().endswith(".gdbtable")
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# ]
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# if not table_files:
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# print("[ERROR] Tidak ada file .gdbtable ditemukan.")
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# return "gdb"
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# # Scan semua table file untuk mencari SpatialReference
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# found_crs = False
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# for table_file in table_files:
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# try:
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# with open(table_file, "rb") as f:
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# raw = f.read(15000) # baca awal file, cukup untuk header JSON
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# text = raw.decode("utf-8", errors="ignore")
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# start = text.find("{")
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# end = text.rfind("}") + 1
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# if start == -1 or end == -1:
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# continue
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# json_str = text[start:end]
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# meta = json.loads(json_str)
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# spatial_ref = meta.get("SpatialReference")
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# if not spatial_ref:
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# continue
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# wkt = spatial_ref.get("WKT")
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# if not wkt:
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# continue
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# print(f"[FOUND] CRS metadata pada: {os.path.basename(table_file)}")
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# print(f"[CRS WKT] {wkt[:200]}...")
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# # Convert to EPSG
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# try:
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# epsg = CRS.from_wkt(wkt).to_epsg()
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# print(f"[EPSG] {epsg}")
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# except:
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# print("[EPSG] Tidak ditemukan EPSG.")
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# found_crs = True
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# break
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# except Exception:
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# continue
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# if not found_crs:
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# print("[WARNING] Tidak ditemukan CRS di file .gdbtable manapun.")
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# return "gdb"
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# # -----------------------------------------------------
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# # 2. DETEKSI SHP
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# # -----------------------------------------------------
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# if any(f.lower().endswith(".shp") for f in files):
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# print("\n[INFO] ZIP terdeteksi berisi SHP.")
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# # cari file .prj
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# prj_files = [f for f in files if f.lower().endswith(".prj")]
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# if not prj_files:
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# print("[WARNING] Tidak ada file .prj → CRS tidak diketahui.")
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# return "shp"
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# with tempfile.TemporaryDirectory() as temp_dir:
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# prj_path = os.path.join(temp_dir, os.path.basename(prj_files[0]))
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# zip_ref.extract(prj_files[0], temp_dir)
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# # baca isi prj
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# with open(prj_path, "r") as f:
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# prj_text = f.read()
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# try:
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# crs = CRS.from_wkt(prj_text)
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# print(f"[CRS WKT] {crs.to_wkt()[:200]}...")
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# epsg = crs.to_epsg()
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# if epsg:
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# print(f"[EPSG] {epsg}")
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# else:
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# print("[EPSG] Tidak ditemukan dalam database EPSG.")
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# except Exception as e:
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# print("[ERROR] Gagal membaca CRS dari file PRJ:", e)
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# return "shp"
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# # -----------------------------------------------------
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# # 3. UNKNOWN
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# # -----------------------------------------------------
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# return "unknown"
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def process_data(df: pd.DataFrame, ext: str, filename: str, fileDesc: str):
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result = detect_and_build_geometry(df, master_polygons=None)
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if not hasattr(result, "geometry") or result.geometry.isna().all():
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result = attach_polygon_geometry_auto(result)
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if isinstance(result, gpd.GeoDataFrame) and "geometry" in result.columns:
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geom_type = ", ".join([g for g in result.geometry.geom_type.unique() if g]) \
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if not result.empty else "None"
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# if isinstance(result, gpd.GeoDataFrame) and "geometry" in result.columns:
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# geom_type = ", ".join([g for g in result.geometry.geom_type.unique() if g]) \
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# if not result.empty else "None"
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# null_geom = result.geometry.isna().sum()
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def normalize_geom_type(geom_type):
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if geom_type.startswith("Multi"):
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return geom_type.replace("Multi", "")
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return geom_type
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if isinstance(result, gpd.GeoDataFrame) and "geometry" in result.columns:
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geom_types = (
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result.geometry
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.dropna()
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.geom_type
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.apply(normalize_geom_type)
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.unique()
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)
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geom_type = geom_types[0] if len(geom_types) > 0 else "None"
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null_geom = result.geometry.isna().sum()
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print(f"[INFO] Tipe Geometry: {geom_type}")
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print(f"[INFO] Jumlah geometry kosong: {null_geom}")
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else:
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warning_safe = [
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{k: safe_json(v) for k, v in row.items()} for row in warning_examples
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]
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ai_context = {
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"nama_file_peta": filename,
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"nama_opd": "Badan Penanggulangan Bencana Daerah (BPBD) Provinsi Jatim",
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"tipe_data_spasial": geom_type,
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"deskripsi_singkat": fileDesc,
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"struktur_atribut_data": {},
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# "metadata": {
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# "judul": "",
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# "abstrak": "",
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# "tujuan": "",
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# "keyword": [],
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# "kategori": [],
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# "kategori_mapset": ""
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# }
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}
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ai_suggest = send_metadata(ai_context)
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# ai_suggest = {'judul': 'Peta Risiko Letusan Gunung Arjuna di Provinsi Jawa Timur', 'abstrak': 'Peta ini menggambarkan wilayah berisiko letusan Gunung Arjuna yang berada di Provinsi Jawa Timur. Data disajikan dalam bentuk poligon yang menunjukkan zona risiko berdasarkan analisis potensi aktivitas vulkanik.', 'tujuan': 'Data dapat digunakan untuk perencanaan mitigasi bencana dan pengambilan keputusan di wilayah Jawa Timur.', 'keyword': ['Risiko letusan', 'Gunung Arjuna', 'Bencana alam', 'Provinsi Jawa Timur', 'Geologi'], 'kategori': ['Geoscientific information', 'Environment'], 'kategori_mapset': 'Lingkungan Hidup'}
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print(ai_suggest)
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response = {
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"message": "File berhasil dibaca dan dianalisis.",
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"file_name": filename,
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"file_type": ext,
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"rows": int(len(result)),
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"columns": list(map(str, result.columns)),
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"geometry_valid": int(valid_count),
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"geometry_empty": int(empty_count),
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"geometry_valid_percent": float(round(match_percentage, 2)),
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"geometry_type": geom_type,
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"warnings": warnings,
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"warning_examples": warning_safe,
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"preview": preview_safe
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"warning_rows": warning_safe,
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"preview": preview_safe,
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"metadata_suggest": ai_suggest
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}
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# return successRes(content=response)
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return response
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@ -156,7 +339,7 @@ def process_data(df: pd.DataFrame, ext: str):
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async def handle_upload_file(file: UploadFile = File(...), page: Optional[str] = Form(""), sheet: Optional[str] = Form("")):
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async def handle_upload_file(file: UploadFile = File(...), page: Optional[str] = Form(""), sheet: Optional[str] = Form(""), fileDesc: Optional[str] = Form("")):
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fname = file.filename
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ext = os.path.splitext(fname)[1].lower()
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contents = await file.read()
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@ -216,7 +399,7 @@ async def handle_upload_file(file: UploadFile = File(...), page: Optional[str] =
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if df is None or (hasattr(df, "empty") and df.empty):
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return successRes(message="File berhasil dibaca, Tetapi tidak ditemukan tabel valid")
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res = process_data(df, ext)
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res = process_data(df, ext, fname, fileDesc)
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tmp_path.unlink(missing_ok=True)
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@ -241,6 +424,8 @@ class PdfRequest(BaseModel):
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title: str
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columns: List[str]
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rows: List[List]
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fileName: str
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fileDesc: str
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async def handle_process_pdf(payload: PdfRequest):
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try:
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@ -248,7 +433,7 @@ async def handle_process_pdf(payload: PdfRequest):
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if df is None or (hasattr(df, "empty") and df.empty):
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return errorRes(message="Tidak ada tabel")
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res = process_data(df, '.pdf')
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res = process_data(df, '.pdf', payload.fileName, payload.fileDesc)
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return successRes(data=res)
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except Exception as e:
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@ -271,6 +456,7 @@ class UploadRequest(BaseModel):
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rows: List[dict]
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columns: List[str]
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author: Dict[str, Any]
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style: str
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# generate _2 if exist
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async def generate_unique_table_name(base_name: str):
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@ -300,125 +486,32 @@ def str_to_date(raw_date: str):
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print("[WARNING] Tidak bisa parse dateCreated:", e)
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return None
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import asyncio
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# async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
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# try:
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# table_name = await generate_unique_table_name(payload.title)
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# df = pd.DataFrame(payload.rows)
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# df.columns = [col.upper() for col in df.columns]
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# if "GEOMETRY" not in df.columns:
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# raise HTTPException(400, "Kolom GEOMETRY tidak ditemukan")
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# df["GEOMETRY"] = df["GEOMETRY"].apply(
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# lambda g: wkt.loads(g)
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# if isinstance(g, str) else None
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# )
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def generate_job_id(user_id: str) -> str:
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timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
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return f"{user_id}_{timestamp}"
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# # ======================================================
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# # RENAME kolom GEOMETRY → geom (WAJIB)
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# # ======================================================
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# df = df.rename(columns={"GEOMETRY": "geom"})
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# gdf = gpd.GeoDataFrame(df, geometry="geom", crs="EPSG:4326")
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# # --- Wajib: gunakan engine sync TANPA asyncpg
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# loop = asyncio.get_running_loop()
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# await loop.run_in_executor(
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# None,
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# lambda: gdf.to_postgis(
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# table_name,
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# sync_engine,
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# if_exists="replace",
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# index=False
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# )
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# )
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def save_xml_to_sld(xml_string, filename):
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folder_path = 'style_temp'
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os.makedirs(folder_path, exist_ok=True)
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file_path = os.path.join(folder_path, f"{filename}.sld")
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with open(file_path, "w", encoding="utf-8") as f:
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f.write(xml_string)
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return file_path
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# # === STEP 4: add ID column ===
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# async with engine.begin() as conn:
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# await conn.execute(text(
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# f'ALTER TABLE "{table_name}" ADD COLUMN _ID SERIAL PRIMARY KEY;'
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# ))
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# # === STEP 5: save author metadata ===
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# author = payload.author
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# async with engine.begin() as conn:
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# await conn.execute(text("""
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# INSERT INTO backend.author_metadata (
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# table_title,
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# dataset_title,
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# dataset_abstract,
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# keywords,
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# topic_category,
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# date_created,
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# dataset_status,
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# organization_name,
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# contact_person_name,
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# contact_email,
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# contact_phone,
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# geom_type,
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# user_id
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# ) VALUES (
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# :table_title,
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# :dataset_title,
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# :dataset_abstract,
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# :keywords,
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# :topic_category,
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# :date_created,
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# :dataset_status,
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# :organization_name,
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# :contact_person_name,
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# :contact_email,
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# :contact_phone,
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# :geom_type,
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# :user_id
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# )
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# """), {
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# "table_title": table_name,
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# "dataset_title": author.get("title") or payload.title,
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# "dataset_abstract": author.get("abstract"),
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# "keywords": author.get("keywords"),
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# "topic_category": author.get("topicCategory"),
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# "date_created": str_to_date(author.get("dateCreated")),
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# "dataset_status": author.get("status"),
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# "organization_name": author.get("organization"),
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# "contact_person_name": author.get("contactName"),
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# "contact_email": author.get("contactEmail"),
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# "contact_phone": author.get("contactPhone"),
|
||||
# "geom_type": json.dumps(list(gdf.geom_type.unique())),
|
||||
# "user_id": user_id
|
||||
# })
|
||||
|
||||
# # === STEP 6: log success ===
|
||||
# await log_activity(
|
||||
# user_id=user_id,
|
||||
# action_type="UPLOAD",
|
||||
# action_title=f"Upload dataset {table_name}",
|
||||
# details={"table_name": table_name, "rows": len(gdf)}
|
||||
# )
|
||||
|
||||
# res = {
|
||||
# "table_name": table_name,
|
||||
# "status": "success",
|
||||
# "message": f"Tabel '{table_name}' berhasil dibuat.",
|
||||
# "total_rows": len(gdf),
|
||||
# "geometry_type": list(gdf.geom_type.unique()),
|
||||
# }
|
||||
|
||||
# return successRes(data=res)
|
||||
|
||||
# except Exception as e:
|
||||
# await log_activity(
|
||||
# user_id=user_id,
|
||||
# action_type="ERROR",
|
||||
# action_title="Upload gagal",
|
||||
# details={"error": str(e)}
|
||||
# )
|
||||
# print(f"error : {str(e)}")
|
||||
# raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
||||
try:
|
||||
|
|
@ -479,9 +572,10 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
if not detected_crs:
|
||||
detected_crs = "EPSG:4326"
|
||||
|
||||
|
||||
detected_crs = 'EPSG:4326'
|
||||
# Buat GeoDataFrame
|
||||
gdf = gpd.GeoDataFrame(df, geometry="geom", crs=detected_crs)
|
||||
row_count = len(gdf)
|
||||
|
||||
# =====================================================================
|
||||
# 6. VERIFY CRS (SRID) VALID di PROJ / PostGIS
|
||||
|
|
@ -533,7 +627,9 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
contact_email,
|
||||
contact_phone,
|
||||
geom_type,
|
||||
user_id
|
||||
user_id,
|
||||
process,
|
||||
geometry_count
|
||||
) VALUES (
|
||||
:table_title,
|
||||
:dataset_title,
|
||||
|
|
@ -547,14 +643,17 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
:contact_email,
|
||||
:contact_phone,
|
||||
:geom_type,
|
||||
:user_id
|
||||
:user_id,
|
||||
:process,
|
||||
:geometry_count
|
||||
)
|
||||
"""), {
|
||||
"table_title": table_name,
|
||||
"dataset_title": author.get("title") or payload.title,
|
||||
"dataset_title": payload.title,
|
||||
"dataset_abstract": author.get("abstract"),
|
||||
"keywords": author.get("keywords"),
|
||||
"topic_category": author.get("topicCategory"),
|
||||
# "topic_category": author.get("topicCategory"),
|
||||
"topic_category": ", ".join(author.get("topicCategory")),
|
||||
"date_created": str_to_date(author.get("dateCreated")),
|
||||
"dataset_status": author.get("status"),
|
||||
"organization_name": author.get("organization"),
|
||||
|
|
@ -562,7 +661,9 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
"contact_email": author.get("contactEmail"),
|
||||
"contact_phone": author.get("contactPhone"),
|
||||
"geom_type": json.dumps(unified_geom_type),
|
||||
"user_id": user_id
|
||||
"user_id": user_id,
|
||||
"process": 'CLEANSING',
|
||||
"geometry_count": row_count
|
||||
})
|
||||
|
||||
|
||||
|
|
@ -576,7 +677,9 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
details={"table_name": table_name, "rows": len(gdf)}
|
||||
)
|
||||
|
||||
job_id = generate_job_id(str(user_id))
|
||||
result = {
|
||||
"job_id": job_id,
|
||||
"table_name": table_name,
|
||||
"status": "success",
|
||||
"message": f"Tabel '{table_name}' berhasil dibuat.",
|
||||
|
|
@ -584,6 +687,10 @@ async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
|||
"geometry_type": unified_geom_type,
|
||||
"crs": detected_crs,
|
||||
}
|
||||
save_xml_to_sld(payload.style, job_id)
|
||||
|
||||
await report_progress(job_id, "upload", 20, "Upload selesai")
|
||||
cleansing_data(table_name, job_id)
|
||||
return successRes(data=result)
|
||||
|
||||
except Exception as e:
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user