Spaces:
Sleeping
Sleeping
File size: 6,889 Bytes
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import logging
import pandas as pd
import os
from typing import Optional, Dict, Any
import gradio as gr
import googlemaps
from PIL import Image
from langchain.utilities.google_places_api import GooglePlacesAPIWrapper
import plotly.graph_objects as go
import requests
from PIL import Image
from io import BytesIO
import tempfile
class GooglePlacesAPIWrapperExtended(GooglePlacesAPIWrapper):
api_key = os.environ["GPLACES_API_KEY"]
def __init__(self, **kwargs):
super().__init__(**kwargs)
def run(self, query: str, **kwargs) -> pd.DataFrame:
"""Run Places search and get k number of places that exist that match."""
search_results = self.google_map_client.places(query, **kwargs)["results"]
num_to_return = len(search_results)
places = []
if num_to_return == 0:
return pd.DataFrame(columns=["Name", "Address", "Phone Number", "Website",
"Opening Hours", "Is Open Now", "latitude", "longitude",
"Summary", "Rating", "Image", "Reviews"])
num_to_return = (
num_to_return
if self.top_k_results is None
else min(num_to_return, self.top_k_results)
)
for i in range(num_to_return):
result = search_results[i]
details = self.fetch_place_details(result["place_id"])
if details is not None:
places.append(details)
return pd.DataFrame(places)
def fetch_place_details(self, place_id: str) -> Optional[Dict[str, Any]]:
try:
place_details = self.google_map_client.place(place_id)
formatted_details = self.format_place_details(place_details)
return formatted_details
except Exception as e:
logging.error(f"An Error occurred while fetching place details: {e}")
return None
def format_place_details(self, place_details: Dict[str, Any]) -> Optional[Dict[str, Any]]:
try:
name = place_details.get("result", {}).get("name", "Unknown")
address = place_details.get("result", {}).get("formatted_address", "Unknown")
phone_number = place_details.get("result", {}).get("formatted_phone_number", "Unknown")
website = place_details.get("result", {}).get("website", "Unknown")
weekday_text = place_details.get("result", {}).get("opening_hours", {}).get("weekday_text", [])
is_open = place_details.get("result", {}).get("opening_hours", {}).get("open_now", "Unknown")
location = place_details.get("result", {}).get("geometry", {}).get("location", {})
latitude = location.get("lat", "Unknown")
longitude = location.get("lng", "Unknown")
summary = place_details.get("result", {}).get("editorial_summary", {}).get("overview", "Unknown")
rating = place_details.get("result", {}).get("rating", "Unknown")
image = place_details.get("result", {}).get("photos", [{}])[0].get("photo_reference", "Unknown")
image_url = f"https://maps.googleapis.com/maps/api/place/photo?maxwidth=400&photoreference={image}&key={self.api_key}"
first_three_reviews = place_details.get("result", {}).get("reviews", [])[:3]
formatted_details = {
"name": name,
"address": address,
"phone_number": phone_number,
"website": website,
"opening_hours": weekday_text,
"is_open_now": is_open,
"latitude": latitude,
"longitude": longitude,
"summary": summary,
"rating": rating,
"image": image_url,
"reviews": first_three_reviews
}
return formatted_details
except Exception as e:
logging.error(f"An error occurred while formatting place details: {e}")
return None
#pd.set_option("display.max_columns", None)
#pd.set_option("display.max_rows", None)
#gplaceapi = GooglePlacesAPIWrapperExtended()
#query = "Louvre, Paris"
#result_df = gplaceapi.run(query)
#print(result_df)
#query = gr.inputs.Textbox(lines=2, label="Query")
#result_df = gr.outputs.Dataframe(type="pandas")
#gr.Interface(fn=GooglePlacesAPIWrapperExtended().run, inputs=query, outputs=result_df).launch(debug=True)
def filter_map(locations):
dataframe = pd.DataFrame()
for location in locations:
dataframe = pd.concat([dataframe, GooglePlacesAPIWrapperExtended().run(location)])
names = dataframe["name"].tolist()
summaries = dataframe["summary"].tolist()
image_urls = dataframe["image"].tolist()
fig = go.Figure(go.Scattermapbox(
lat=dataframe['latitude'].tolist(),
lon=dataframe['longitude'].tolist(),
mode='markers',
marker=go.scattermapbox.Marker(
size=13,
color='rgb(255, 123, 0)',
),
hovertemplate='Name: %{customdata[0]}<br>Summary: %{customdata[1]}',
customdata=list(zip(names, summaries)),
name='Places'
))
fig.update_layout(
mapbox_style="open-street-map",
hovermode='closest',
mapbox=dict(
bearing=0,
center=go.layout.mapbox.Center(
lat=dataframe['latitude'].tolist()[0],
lon=dataframe['longitude'].tolist()[0]
),
pitch=0,
zoom=12
),
)
# Add images using layout.images attribute
#for i, url in enumerate(image_urls):
# response = requests.get(url)
# img = Image.open(BytesIO(response.content))
# with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp:
# img.save(temp.name)
# fig.add_layout_image(
# dict(
# source=temp.name,
# xref='x',
# yref='y',
# x=dataframe['longitude'].iloc[i],
# y=dataframe['latitude'].iloc[i],
# sizex=0.05,
# sizey=0.05,
# sizing='stretch',
# opacity=0.7,
# layer='above'
# )
# )
#
#fig.update_layout(
# xaxis=dict(range=[dataframe['longitude'].min(), dataframe['longitude'].max()]),
# yaxis=dict(range=[dataframe['latitude'].min(), dataframe['latitude'].max()])
#)
#
return fig, dataframe
if __name__ == "main":
with gr.Blocks() as demo:
with gr.Column():
location = gr.Textbox(lines=2, label="Location")
btn = gr.Button(value="Update Filter")
map = gr.Plot().style()
result_df = gr.Dataframe(type="pandas")
btn.click(filter_map, [location], [map, result_df])
demo.queue(concurrency_count=6).launch() |