src/fetch_places.py

import os
import requests
import json
from datetime import datetime

from typing import Tuple
from data_models.park_manager import ParkManager
from data_models.image_manager import ImageManager
from data_models.openai_manager import OpenAIManager
from openai_predictions import process_agent_predictions
from cloud_storage.google_cloud_storage import GoogleCloudStorage

park_manager = ParkManager()
image_manager = ImageManager()
prediction_manager = OpenAIManager()
gcs = GoogleCloudStorage("ialab-fr-7047e56bef0b.json")


def nearby_search(coordinates: tuple) -> Tuple[str, str, dict]:
    """Search nearby places

    Args:
        coordinates (tuple): Coordinates

    Raises:
        Exception: Failed to fetch places

    Returns:
        str: Place ID
    """
    url = "https://places.googleapis.com/v1/places:searchNearby"
    payload = json.dumps(
        {
            "includedTypes": ["park"],
            "maxResultCount": 1,
            "locationRestriction": {
                "circle": {
                    "center": {"longitude": coordinates[0], "latitude": coordinates[1]},
                    "radius": 500,
                }
            },
        }
    )
    headers = {
        "Content-Type": "application/json",
        "X-Goog-Api-Key": "AIzaSyAPmP_sVOZMmJvyXFNPrWJY11BzhKRRBh4",
        "X-Goog-FieldMask": "places.id,places.name,places.photos",
    }

    response = requests.request("POST", url, headers=headers, data=payload)
    if response.status_code != 200:
        raise Exception(f"Failed to fetch places: {response.text}")

    response = response.json()
    if "places" not in response:
        return None, None, None

    return (
        response["places"][0]["id"],
        response["places"][0]["name"],
        response["places"][0]["photos"],
    )


def place_details(place_id: str) -> dict:
    """Get place details

    Args:
        place_id (str): Place ID

    Raises:
        Exception: Failed to fetch place details

    Returns:
        dict: Place details
    """
    url = f"https://places.googleapis.com/v1/places/{place_id}"
    payload = {}
    headers = {
        "Content-Type": "application/json",
        "X-Goog-Api-Key": "AIzaSyAPmP_sVOZMmJvyXFNPrWJY11BzhKRRBh4",
        "X-Goog-FieldMask": "photos",
    }

    response = requests.request("GET", url, headers=headers, data=payload)

    if response.status_code != 200:
        raise Exception(f"Failed to fetch place details: {response.text}")

    return response.json()


def fetch_photo(place_id: str, photo_id: str, max_width: int, max_height: int) -> bytes:
    """Fetch photo from place

    Args:
        place_id (str): Place ID
        photo_id (str): Photo ID
        max_width (int): Max width
        max_height (int): Max height

    Raises:
        Exception: Failed to fetch photo

    Returns:
        str: Photo binary
    """
    url = f"https://places.googleapis.com/v1/places/{place_id}/photos/{photo_id}/media?key=AIzaSyAPmP_sVOZMmJvyXFNPrWJY11BzhKRRBh4&maxHeightPx={max_width}&maxWidthPx={max_height}"

    payload = {}
    headers = {
        "Content-Type": "application/json",
        "X-Goog-Api-Key": "AIzaSyAPmP_sVOZMmJvyXFNPrWJY11BzhKRRBh4",
    }

    response = requests.request("GET", url, headers=headers, data=payload)

    if response.status_code != 200:
        raise Exception(f"Failed to fetch photo: {response.text}")

    return response.content


def fetch_place_photos(place_id: str, place_name: str, photos: dict) -> int:
    """Fetch all photos from place datas

    Args:
        place_id (str): Place ID
        place_name (str): Place name
        photos (dict): Photos
        folder (str): Folder to save photos

    Returns:
        str: Place ID
    """
    folder_path = f"images/{place_name}"
    os.makedirs(folder_path, exist_ok=True)

    if park_manager.get_park_id(place_name):
        print(f"Place: {place_name} already exists")
        return 0

    park_id = park_manager.add_park(place_name)
    for photo in photos:
        photo_id = photo["name"].replace(f"places/{place_id}/photos/", "")
        photo_id = photo_id.replace("/", "_")

        max_width = photo["widthPx"]
        max_height = photo["heightPx"]

        photo_binary = fetch_photo(place_id, photo_id, max_width, max_height)

        file_name = f"{place_name}/{photo_id[:150]}.jpg"
        bucket_path = gcs.upload_file_from_content("suad_park", file_name, photo_binary)
        image_id = image_manager.add_image(bucket_path, datetime.now(), park_id=park_id)
        predictions = process_agent_predictions(file_name, photo_binary)
        prediction_manager.add_predictions(image_id, predictions)

    print(f"{len(photos)} photos fetched for place: {place_name}")
    return len(photos)