app.py

from flask import Flask, render_template, request, jsonify
from gensim.models import Word2Vec
import os

app = Flask(__name__)

# モデルのパスを設定（webフォルダ直下）
MODEL_PATH = os.path.join(os.path.dirname(__file__), 'jawiki_word2vec_2.1.model')
model = None

def load_model():
    global model
    if model is None:
        model = Word2Vec.load(MODEL_PATH)
    return model

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/calculate', methods=['POST'])
def calculate():
    try:
        data = request.json
        positive = [word.strip() for word in data.get('positive', '').split(',') if word.strip()]
        negative = [word.strip() for word in data.get('negative', '').split(',') if word.strip()]
        print(positive, negative)
        topn = 10  # 固定
        
        if not positive and not negative:
            return jsonify({'error': '少なくとも1つの単語を入力してください'}), 400
        
        model = load_model()
        
        # most_similarを実行
        kwargs = {'topn': topn}
        if positive:
            kwargs['positive'] = positive
        if negative:
            kwargs['negative'] = negative
            
        results = model.wv.most_similar(**kwargs)
        
        # 結果を整形
        formatted_results = [
            {'word': word, 'similarity': float(similarity)}
            for word, similarity in results
        ]
        
        return jsonify({'results': formatted_results})
        
    except KeyError as e:
        return jsonify({'error': f'単語が見つかりません: {str(e)}'}), 400
    except Exception as e:
        return jsonify({'error': f'エラーが発生しました: {str(e)}'}), 500

if __name__ == '__main__':
    print('モデルを読み込んでいます...')
    load_model()
    print('モデルの読み込みが完了しました')
    app.run(debug=True, host='0.0.0.0', port=5000)