Upload 3 files

Title.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ee90d5c9c96cd2550a99a2935264fa8c87074ef9fcdcf7b691bc825db8cad2df
+size 10035

app.py

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+import gradio as gr
+import joblib
+import pickle
+import numpy as np
+from janome.tokenizer import Tokenizer
+
+
+model = joblib.load('./doc2vec.pkl')
+with open('document_vecs.pkl', 'rb') as f:
+  document_vecs = pickle.load(f)
+with open('Title.pkl', 'rb') as f:
+  Title = pickle.load(f)
+
+def sep_by_janome(text):
+    t = Tokenizer()
+    tokens = t.tokenize(text)
+    docs=[]
+    for token in tokens:
+        docs.append(token.surface)
+    return docs
+
+
+#コサイン類似度の計算＋ランキング化
+
+def cos_calc(text):
+  tokens = sep_by_janome(text)
+  input_vec = model.infer_vector(tokens)
+
+  rank_size = 5
+  
+  v1 = np.linalg.norm(input_vec)
+  cos_sim = []
+  for v2 in document_vecs:
+      cos_sim.append( np.dot(input_vec,v2)/(v1*np.linalg.norm(v2)) )
+  doc_sort = np.argsort(np.array(cos_sim))[::-1]
+  cos_sort = sorted(cos_sim,reverse=True)
+  
+  cos = []
+  titles = []
+  for i in range(rank_size):
+      cos.append(cos_sort[i])
+      titles.append(Title[doc_sort[i]])
+  
+  rank_1 = f'{titles[0]} \nコサイン類似度：{cos[0]}'
+  rank_2 = f'{titles[1]} \nコサイン類似度：{cos[1]}'
+  rank_3 = f'{titles[2]} \nコサイン類似度：{cos[2]}'
+  rank_4 = f'{titles[3]} \nコサイン類似度：{cos[3]}'
+  rank_5 = f'{titles[4]} \nコサイン類似度：{cos[4]}'
+  
+  return rank_1, rank_2, rank_3, rank_4, rank_5
+
+demo = gr.Interface(fn=cos_calc,
+                    inputs=gr.Textbox(label="検索ワード"),
+                    outputs=[gr.Textbox(label='1位'),
+                    gr.Textbox(label='2位'),
+                    gr.Textbox(label='3位'),
+                    gr.Textbox(label='4位'),
+                    gr.Textbox(label='5位')
+                    ])
+
+demo.launch()

document_vecs.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4a34c2c32ff6772d96321f68b08b680deca82d5b352d44a6e955ad08041def64
+size 148219