get_context_for_each_candidate.py

def get_context_for_each_candidate(question,options_list):
    """ Searches the user query and finds the best matches using elasticsearch."""
    #query = input("Enter query: ")
    """This function will return a context after joining a question
    and its options separately. 
    For example: question + option_1
                 question + option_2
                 question + option_3
                 question + option_4"""
   
    option_1_docs = []
    option_2_docs =  []
    option_3_docs =  []
    option_4_docs =  []
    option_5_docs =  []
    for j in range(len(options_list)):
        query=question+options_list[j]
        search_start = time.time()
        search = {"size": 8,"query": {"match": {"body": query}}}
        #print(search)
        response = es.search(index='corpus2', body=json.dumps(search))
        search_time = time.time() - search_start
        #print("{} total hits.".format(response["hits"]["total"]["value"]))
        print("search time: {:.2f} ms".format(search_time * 1000))
        sentences = []
        for hit in response["hits"]["hits"]:
            sentence = hit['_source']
            out=list(sentence.values())
            out = reduce(operator.concat,out)
           
            if j == 0:
                option_1_docs.append(out)
            elif j == 1:
                option_2_docs.append(out)
            elif j == 2:
                option_3_docs.append(out)
            elif j == 3:
                option_4_docs.append(out)
            elif j == 4:
                option_5_docs.append(out)
        
    return pd.Series([option_1_docs, option_2_docs, option_3_docs, option_4_docs, option_5_docs])

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