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brian-yu-nexusflow
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6db0fcc
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Parent(s):
63b3c15
Update tools.py
Browse files
tools.py
CHANGED
@@ -2,8 +2,10 @@
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These are all the tools used in the NexusRaven V2 demo! You can provide any tools you want to Raven.
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Nothing in this file is specific to Raven, code/information related to Raven can be found in the `raven_demo.py` file.
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"""
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from typing import Dict, List
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from math import radians, cos, sin, asin, sqrt
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@@ -23,6 +25,12 @@ class Tools:
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self.gmaps = Client(config.gmaps_client_key)
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self.client_ip: str | None = None
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def haversine(self, lon1, lat1, lon2, lat2) -> float:
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"""
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Calculate the great circle distance in kilometers between two points on the earth (specified in decimal degrees).
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@@ -52,7 +60,9 @@ class Tools:
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except:
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return "San Francisco, California, US"
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def sort_results(
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"""
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Sorts the results by either 'distance', 'rating' or 'price'.
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@@ -60,7 +70,7 @@ class Tools:
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- sort (str): If set, sorts by either 'distance' or 'rating' or 'price'. ONLY supports 'distance' or 'rating' or 'price'.
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- descending (bool): If descending is set, setting this boolean to true will sort the results such that the highest values are first.
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- first_n (int): If provided, only retains the first n items in the final sorted list.
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-
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When people ask for 'closest' or 'nearest', sort by 'distance'.
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When people ask for 'cheapest' or 'most expensive', sort by 'price'.
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When people ask for 'best' or 'highest rated', sort by rating.
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@@ -88,7 +98,13 @@ class Tools:
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- location: This can be a city like 'Austin', or a place like 'Austin Airport', etc.
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"""
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-
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def get_distance(self, place_1: str, place_2: str):
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"""
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"""
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if isinstance(place_1, list) and len(place_1) > 0:
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place_1 = place_1[0]
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if isinstance(place_2, list) and len(place_2) > 0:
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place_2 = place_2[0]
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latlong_1 = self.get_latitude_longitude(place_1)
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latlong_2 = self.get_latitude_longitude(place_2)
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if isinstance(place_1, dict):
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place_1 = place_1["name"]
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if isinstance(place_2, dict):
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place_2 = place_2["name"]
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-
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-
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dist = self.haversine(
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)
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dist = dist * 0.621371
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return [
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def get_recommendations(self, topics: list, lat_long: tuple):
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"""
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topic = " ".join(topics)
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latlong = lat_long[0]["geometry"]["location"]
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results = self.gmaps.places(
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query=topic,
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location=latlong,
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type_of_place = " ".join(type_of_place)
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# Perform the search using Google Places API
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places_result = self.gmaps.places_nearby(
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location=location, keyword=type_of_place, radius=radius_miles * 1609.34
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)
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if distance == 0.0:
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continue
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-
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new_places.append(place)
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places = new_places
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location = None
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if location and isinstance(location, str):
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place_name += " , " + location
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elif
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place_name = place_name["results"]["name"]
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elif isinstance(place_name, dict) and "name" in place_name:
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place_name = place_name["name"]
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-
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if
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return []
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# Assuming the first result is the most relevant
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place_id = search_results["
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place_details = self.gmaps.place(place_id=place_id)
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reviews = place_details["result"].get("reviews", [])
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These are all the tools used in the NexusRaven V2 demo! You can provide any tools you want to Raven.
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Nothing in this file is specific to Raven, code/information related to Raven can be found in the `raven_demo.py` file.
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For more information about the Google Maps Places API Python client, see https://github.com/googlemaps/google-maps-services-python
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"""
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from typing import Dict, List
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from math import radians, cos, sin, asin, sqrt
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self.gmaps = Client(config.gmaps_client_key)
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self.client_ip: str | None = None
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def capitalize(self, s: str) -> str:
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if s.lower() != s:
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return s
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return s.title()
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def haversine(self, lon1, lat1, lon2, lat2) -> float:
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"""
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Calculate the great circle distance in kilometers between two points on the earth (specified in decimal degrees).
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except:
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return "San Francisco, California, US"
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def sort_results(
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self, places: list, sort: str, descending: bool = True, first_n: int = None
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) -> List:
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"""
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Sorts the results by either 'distance', 'rating' or 'price'.
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- sort (str): If set, sorts by either 'distance' or 'rating' or 'price'. ONLY supports 'distance' or 'rating' or 'price'.
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- descending (bool): If descending is set, setting this boolean to true will sort the results such that the highest values are first.
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- first_n (int): If provided, only retains the first n items in the final sorted list.
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When people ask for 'closest' or 'nearest', sort by 'distance'.
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When people ask for 'cheapest' or 'most expensive', sort by 'price'.
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When people ask for 'best' or 'highest rated', sort by rating.
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- location: This can be a city like 'Austin', or a place like 'Austin Airport', etc.
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"""
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# For response content, see https://developers.google.com/maps/documentation/geocoding/requests-geocoding#GeocodingResponses
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results = self.gmaps.geocode(location)
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location = self.capitalize(location)
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for r in results:
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r["name"] = location
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return results
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def get_distance(self, place_1: str, place_2: str):
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"""
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"""
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if isinstance(place_1, list) and len(place_1) > 0:
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place_1 = place_1[0]
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if isinstance(place_2, list) and len(place_2) > 0:
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place_2 = place_2[0]
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if isinstance(place_1, dict):
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place_1: str = place_1["name"]
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if isinstance(place_2, dict):
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place_2: str = place_2["name"]
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latlong_1 = self.get_latitude_longitude(place_1)
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if len(latlong_1) == 0:
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return f"No place found for `{place_1}`. Please be more explicit."
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latlong_2 = self.get_latitude_longitude(place_2)
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if len(latlong_2) == 0:
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return f"No place found for `{place_2}`. Please be more explicit."
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latlong_1 = latlong_1[0]
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latlong_2 = latlong_2[0]
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latlong_values_1 = latlong_1["geometry"]["location"]
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latlong_values_2 = latlong_2["geometry"]["location"]
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dist = self.haversine(
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latlong_values_1["lng"],
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latlong_values_1["lat"],
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latlong_values_2["lng"],
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latlong_values_2["lat"],
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)
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dist = dist * 0.621371
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return [
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latlong_1,
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latlong_2,
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f"The distance between {place_1} and {place_2} is {dist:.3f} miles",
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]
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def get_recommendations(self, topics: list, lat_long: tuple):
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"""
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topic = " ".join(topics)
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latlong = lat_long[0]["geometry"]["location"]
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# For response format, see https://developers.google.com/maps/documentation/places/web-service/search-find-place#find-place-responses
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results = self.gmaps.places(
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query=topic,
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location=latlong,
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type_of_place = " ".join(type_of_place)
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# Perform the search using Google Places API
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# For response format, see https://developers.google.com/maps/documentation/places/web-service/search-nearby#nearby-search-responses
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places_result = self.gmaps.places_nearby(
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location=location, keyword=type_of_place, radius=radius_miles * 1609.34
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)
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if distance == 0.0:
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continue
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distance = distance * 0.621371
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place["distance"] = f"{distance} miles from {verb_location}"
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new_places.append(place)
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places = new_places
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location = None
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if location and isinstance(location, str):
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place_name += " , " + location
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elif (
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isinstance(place_name, dict)
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and "results" in place_name
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and "name" in place_name["results"]
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):
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place_name = place_name["results"]["name"]
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elif isinstance(place_name, dict) and "name" in place_name:
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place_name = place_name["name"]
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# For response format, see https://developers.google.com/maps/documentation/places/web-service/search-find-place#find-place-responses
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search_results = self.gmaps.find_place(
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place_name, input_type="textquery", location_bias="ipbias"
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)
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if len(search_results.get("candidates", [])) == 0:
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return []
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# Assuming the first result is the most relevant
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place_id = search_results["candidates"][0]["place_id"]
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# For response format, see https://developers.google.com/maps/documentation/places/web-service/details#PlaceDetailsResponses
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place_details = self.gmaps.place(place_id=place_id)
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reviews = place_details["result"].get("reviews", [])
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