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""" PlaceRecommender |
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@author: Burak Kaya |
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@email: [email protected] |
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""" |
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import gradio as gr |
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from huggingface_hub import InferenceClient |
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import json |
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from openai import OpenAI |
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import os |
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import requests |
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import googlemaps |
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import pandas as pd |
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OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY') |
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MAPS_API_KEY = os.environ.get('MAPS_API_KEY') |
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LOC_ERR_MSG = "Lütfen yukarıdaki bölümden, dilediğiniz konumu giriniz." |
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client = OpenAI(api_key=OPENAI_API_KEY) |
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def get_place_details(place_id, api_key): |
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URL = f"https://maps.googleapis.com/maps/api/place/details/json?place_id={place_id}&key={api_key}" |
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response = requests.get(URL) |
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if response.status_code == 200: |
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result = json.loads(response.content)["result"] |
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return result |
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else: |
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print(f"Google Place Details API request failed with status code {response.status_code}") |
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print(f"Response content: {response.content}") |
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return None |
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def generate_short_answer(user_input): |
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OpenAI(api_key=OPENAI_API_KEY) |
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response = client.chat.completions.create( |
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model="gpt-3.5-turbo-0125", |
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messages=[ |
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{ |
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"role": "system", |
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"content": "Kullanıcı girdisine dayanarak, cümlenin ana konusunu veya amacını temsil eden bir arama kelimesi veya kelime öbeği çıkarın. Herhangi bir ek metin veya açıklama olmadan yalnızca arama sözcüğünü veya ifadesini çıktı olarak sağlayın." |
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}, |
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{ |
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"role": "user", |
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"content": user_input |
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} |
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], |
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temperature=0, |
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max_tokens=256, |
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top_p=1, |
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frequency_penalty=0, |
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presence_penalty=0 |
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) |
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output_string = response.choices[0].message.content |
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return output_string |
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def call_google_places_api(location, food_preference=None): |
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try: |
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map_client = googlemaps.Client(MAPS_API_KEY) |
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search_string = food_preference |
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address = location |
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geocode = map_client.geocode(address=address) |
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(lat, lng) = map(geocode[0]['geometry']['location'].get, ('lat', 'lng')) |
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response = map_client.places_nearby( |
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location=(lat, lng), |
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keyword=search_string, |
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radius=1000 |
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) |
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business_list = response.get('results') |
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df = pd.DataFrame(business_list) |
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df['url'] = 'https://www.google.com/maps/place/?q=place_id:' + df['place_id'] |
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top_places = df[(df['user_ratings_total'] > 100) & (df['rating'] >= 4.2)].sort_values(by=['rating', 'user_ratings_total']).sort_values(by=['rating','user_ratings_total'],ascending=False).head(4) |
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places = [] |
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for _, place in top_places.iterrows(): |
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place_id = place['place_id'] |
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place_details = get_place_details(place_id, MAPS_API_KEY) |
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place_name = place_details.get("name", "N/A") |
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place_rating = place_details.get("rating", "N/A") |
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total_ratings = place_details.get("user_ratings_total", "N/A") |
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place_address = place_details.get("vicinity", "N/A") |
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place_url = place_details.get("url", "N/A") |
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place_reviews = [] |
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reviews = place_details.get("reviews", []) |
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for review in reviews[:5]: |
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review_dict = { |
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"text": review["text"], |
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} |
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place_reviews.append(review_dict) |
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if ',' in place_address: |
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street_address = place_address.split(',')[0] |
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else: |
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street_address = place_address |
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place_info = f"[{place_name}]({place_url}) is a located at {street_address}. It has a rating of {place_rating} based on {total_ratings} user reviews: {place_reviews}. \n" |
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places.append(place_info) |
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return places |
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except Exception as e: |
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print(f"Error during the Google Places API call with radius 1000: {e}") |
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try: |
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response = map_client.places_nearby( |
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location=(lat, lng), |
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keyword=search_string, |
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radius=2000 |
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) |
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business_list = response.get('results') |
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df = pd.DataFrame(business_list) |
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df['url'] = 'https://www.google.com/maps/place/?q=place_id:' + df['place_id'] |
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top_places = df[(df['user_ratings_total'] > 100) & (df['rating'] >= 4.2)].sort_values(by=['rating', 'user_ratings_total']).sort_values(by=['rating','user_ratings_total'],ascending=False).head(4) |
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places = [] |
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for _, place in top_places.iterrows(): |
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place_id = place['place_id'] |
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place_details = get_place_details(place_id, MAPS_API_KEY) |
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place_name = place_details.get("name", "N/A") |
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place_rating = place_details.get("rating", "N/A") |
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total_ratings = place_details.get("user_ratings_total", "N/A") |
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place_address = place_details.get("vicinity", "N/A") |
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place_url = place_details.get("url", "N/A") |
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place_reviews = [] |
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reviews = place_details.get("reviews", []) |
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for review in reviews[:5]: |
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review_dict = { |
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"text": review["text"], |
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} |
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place_reviews.append(review_dict) |
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if ',' in place_address: |
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street_address = place_address.split(',')[0] |
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else: |
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street_address = place_address |
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place_info = f"[{place_name}]({place_url}) is a located at {street_address}. It has a rating of {place_rating} based on {total_ratings} user reviews: {place_reviews}. \n" |
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places.append(place_info) |
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return places |
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except Exception as e: |
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print(f"Error during the Google Places API call with radius 2000: {e}") |
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return [] |
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def provide_user_specific_recommendations(user_input, location): |
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place_type = generate_short_answer(user_input) |
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places = call_google_places_api(location, place_type) |
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if places: |
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return f"Here are some places you might be interested in: {' '.join(places)}" |
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else: |
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return "Yakınlarda ilgi çekici bir yer bulamadım. Lütfen başka bir şekilde dile getirmeyi deneyiniz" |
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def bot(user_input, history,Konum): |
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if not Konum: |
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yield LOC_ERR_MSG |
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if Konum: |
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output = provide_user_specific_recommendations(user_input, Konum) |
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OpenAI(api_key=OPENAI_API_KEY) |
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stream = client.chat.completions.create( |
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model="gpt-3.5-turbo-0125", |
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messages=[ |
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{ |
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"role": "system", |
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"content": "Sen bir mekan tavsiyecisisin. Kullanicinin sorusuna uygun mekanlari buluyorsun, mekan yorumlarini anlayarak o mekanlari neden secmesi gerektigini tek tek ozetliyorsun.**[cafe ismi](url link)** formatini muhakkak ver. Emoji kullanmaktan cekinme" |
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}, |
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{ |
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"role": "user", |
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"content": user_input + output |
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} |
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], |
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temperature=0, |
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max_tokens=2048, |
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top_p=1, |
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frequency_penalty=0, |
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presence_penalty=0, |
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stream=True |
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) |
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partial_message = "" |
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for chunk in stream: |
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if chunk.choices[0].delta.content is not None: |
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partial_message = partial_message + chunk.choices[0].delta.content |
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yield partial_message |
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yield partial_message |
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my_theme = gr.Theme.from_hub("bethecloud/storj_theme") |
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with gr.Blocks(theme = my_theme) as demo: |
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with gr.Row() as Konum: |
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Konum = gr.Textbox(label="Konum",placeholder="Konum Giriniz (Kadıköy, Moda)") |
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chatbot = gr.Chatbot( |
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[], |
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elem_id="chatbot", |
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bubble_full_width=False, |
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render=False, |
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height=500, |
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) |
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gr.ChatInterface( |
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bot,chatbot=chatbot, |
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additional_inputs=Konum, |
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examples=[["Arkadașlarımla oturup kahve içebileceğimiz bir yer arıyoruz. Önerebileceğin yerler var mı?","Alsancak"], ["Bilgisayar ile çalışabileceğim sessiz kafe var mı?","Kadıköy, Moda"], ["Kız arkadaşım ile özel bir akşam yemeği yemek istiyoruz. Bir tavsiyen var mı?","Bornova"]],) |
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if __name__ == "__main__": |
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demo.launch(show_api=False) |
