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server.py
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server.py
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import streamlit as st
import pickle
import pandas as pd
from sklearn.metrics.pairwise import sigmoid_kernel
import requests
from flask import Flask, request,jsonify
from flask_restful import Resource, Api
from flask_cors import CORS
import requests
import json
anime_list=pickle.load(open('model/movie_dict.pk1','rb'))
anime=pd.DataFrame(anime_list)
#API CALL FOR IMAGE OF ANIME
image_link=[]
def apis(ids):
reply =requests.get('https://api.jikan.moe/v4/anime/'+str(ids))
meta_data=reply.json()
try:
df=pd.DataFrame(meta_data)
image_url =str(df['data'][11]['jpg']['large_image_url'])
return image_url
except:
return
def give_rec(title, sig,anime_data,indices):
idx = indices[title]
sig_scores = list(enumerate(sig[idx]))
sig_scores = sorted(sig_scores, key=lambda x: x[1], reverse=True)
sig_scores = sig_scores[1:11]
# Movie indices
anime_indices = [i[0] for i in sig_scores]
# Top 10 most similar movies
return pd.DataFrame({'Anime name': anime_data['name'].iloc[anime_indices].values,'Rating': anime_data['rating'].iloc[anime_indices].values})
def id_of_anime(anime,ans,image_link):
for i in range(5):
id_list=anime.loc[lambda anime:anime['name']==ans['Anime name'][i]]
ids=id_list['anime_id']
image_url=apis(ids)
image_link.append(image_url)
return
def recommended(name,anime,image_link):
tfv=pickle.load(open('model/tfv.pk1','rb'))
anime_data=pickle.load(open('model/anime_data.pk1','rb'))
indices=pickle.load(open('model/indices.pk1','rb'))
anime_data=pd.DataFrame(anime_data)
indices = pd.Series(anime_data.index, index=anime_data['name']).drop_duplicates()
# Compute the sigmoid kernel
sig = sigmoid_kernel(tfv, tfv)
ans=give_rec(name, sig,anime_data,indices)
id_of_anime(anime,ans,image_link)
return ans
app = Flask(__name__)
# creating an API object
api = Api(app)
CORS(app, resources={r"/*": {"origins": "*"}})
image_link=[]
#API CALL FOR IMAGE OF ANIME
class recommend(Resource):
def post(self):
an_request = request.get_json()
an_request=json.loads(an_request)
return recommended(an_request["name"],anime,image_link).to_json()
# adding the defined resources along with their corresponding urls
api.add_resource(recommend, '/')
# driver function
if __name__ == '__main__':
app.run(debug=False)