def process_Query_Type(self,tokens):
boost_params = []
boosts = {"title_sinhala":1,"artist_name":1,"writer_name":1,"music":1,"movie":1,"genre":1,"lyrics":1}
additional_tokens =[]
for token in tokens:
splits = word_splitter.split(token)
additional_tokens.append(splits['base'])
if(token in views_boosters or splits['affix'] in views_boosters or splits['base'] in views_boosters):
boost_params.append("view")
if(token in artist_name_boosters or splits['affix'] in artist_name_boosters or splits['base'] in artist_name_boosters):
boost_params.append("artist_name")
boosts['artist_name'] = 2
if(token in writer_name_boosters or splits['affix'] in writer_name_boosters or splits['base'] in writer_name_boosters):
boost_params.append("writer_name")
boosts['writer_name'] = 2
if(token in music_boosters or splits['affix'] in music_boosters or splits['base'] in music_boosters):
boost_params.append("music")
boosts['music'] = 2
if(token in movie_boosters or splits['affix'] in movie_boosters or splits['base'] in movie_boosters):
boost_params.append("movie")
boosts['movie'] = 2
if(token in genre_boosters or splits['affix'] in genre_boosters or splits['base'] in genre_boosters):
boost_params.append("genre")
boosts['genre'] = 2
query_mod = " ".join(tokens+additional_tokens)
return set(boost_params),boosts,query_mod
def predictQType(self,tokens):
boost_params = []
boosts = {"title_si":1,"artist":1,"writer":1,"music":1,"genre":1.0,"lyrics":1}
additional_tokens =[]
print(tokens)
for token in tokens:
#split the tokens to identify affixes
splits = word_splitter.split(token)
additional_tokens.append(splits['base'])
#add base to query depending on the threshold
if(token in rating_boosters or splits['affix'] in rating_boosters or splits['base'] in rating_boosters):
boost_params.append("rate")
if(token in artist_boosters or splits['affix'] in artist_boosters or splits['base'] in artist_boosters):
boost_params.append("artist")
boosts['artist'] = 2
if(token in writer_boosters or splits['affix'] in writer_boosters or splits['base'] in writer_boosters):
boost_params.append("writer")
boosts['writer'] = 2
if(token in music_boosters or splits['affix'] in music_boosters or splits['base'] in music_boosters):
boost_params.append("music")
boosts['music'] = 2
if(token in genre_boosters or splits['affix'] in genre_boosters or splits['base'] in genre_boosters):
boost_params.append("genre")
boosts['genre'] = 2
#append music as well.
query_mod = " ".join(tokens+additional_tokens)
return set(boost_params),boosts,query_mod
def process_word(sentence):
raw_list = sentence.split()
temp_list = []
for raw_word in raw_list:
if len(raw_word) < 10:
temp_list.append(raw_word)
continue
result = word_splitter.split(raw_word)
temp_list.append(result['base'])
temp_list.append(result['affix'])
final_query = " "
for piece in temp_list:
final_query = final_query + " " + piece
return temp_list, final_query
def create_orig_to_base_json(lines: list):
# lines is a list of sentences
from sinling import word_splitter as ws
unique_file_name = str(uuid.uuid4()) + ".json"
output_dict = dict()
for sentence in lines:
words = sentence.split()
for word in words:
# word = word.replace('\u200d', '')
if is_sinhala_word(word):
try:
base = ws.split(word)['base']
print(word, base)
if word not in output_dict:
output_dict[word] = base
except Exception as e:
print("word:", word)
print(e, "\n")
with open(unique_file_name, 'w', encoding='utf8') as outfile:
json.dump(output_dict, outfile, ensure_ascii=False)
def identifyContext(self, tokens, query):
boosting_fields = []
boosting_data = {}
print(tokens)
for token in tokens:
results = word_splitter.split(token)
#Split the token into affix and the base
if (results['affix'] == "ගේ"):
query = query.replace(token, results['base'])
if ("ගීත" in token):
query = query.replace("ගීත", " ")
#print(results, token)
if (token in rating_identifiers
or results['affix'] in rating_identifiers
or results['base'] in rating_identifiers):
boosting_fields.append("rate")
print(token)
query = self.replaceUnwantedData(
query, [token, results['base'], results['affix']])
if (token in artist_identifiers
or results['affix'] in artist_identifiers
or results['base'] in artist_identifiers):
boosting_fields.append("artist")
boosting_data['artist'] = 2.0
query = self.replaceUnwantedData(query, [results['affix']])
if (token in writer_identifiers
or results['affix'] in writer_identifiers
or results['base'] in writer_identifiers):
boosting_fields.append("writer")
boosting_data['writer'] = 2.0
query = self.replaceUnwantedData(
query, [token, results['base'], results['affix']])
if (token in genre_boosters or results['affix'] in genre_boosters
or results['base'] in genre_boosters):
boosting_fields.append("genre")
boosting_data['genre'] = 3.0
#append music as well.
return list(set(boosting_fields)), boosting_data, query
def get_base(word):
return word_splitter.split(word)['base']
def split():
query_request = request.json
print(query_request)
results = word_splitter.split(query_request["word"])
return results
def query_process(query):
artist_flag = False
splited_sentence = tokenizer.tokenize(query)
print(splited_sentence)
for word in splited_sentence:
if word in artist_consider:
artist_flag = True
break
else:
print(word_splitter.split(word))
affix = word_splitter.split(word)['affix']
base = word_splitter.split(word)['base']
print(affix)
if affix in artist_consider:
artist_flag = True
query = query + ' ' + base
break
print(artist_flag)
if artist_flag:
body = {
"query": {
"multi_match": {
"type":
"most_fields",
"query":
query,
"fields": [
"artist^3.0", "lyrics^1.0", "title^1.0",
"musicArtist^1.0", "lyricsArtist^1.0", "genre^1.0",
"movie^1.0"
]
}
},
"aggs": {
"rate_range": {
"range": {
"field":
"rate",
"ranges": [{
"from": 0,
"to": 1000
}, {
"from": 1000,
"to": 2000
}, {
"from": 2000,
"to": 3000
}, {
"from": 3000,
"to": 4000
}, {
"from": 4000,
"to": 5000
}, {
"from": 5000,
"to": 6000
}, {
"from": 6000,
"to": 7000
}, {
"from": 7000,
"to": 8000
}, {
"from": 8000,
"to": 9000
}, {
"from": 9000,
"to": 10000
}]
}
}
}
}
else:
body = {
"query": {
"multi_match": {
"type":
"most_fields",
"query":
query,
"fields": [
"artist", "lyrics", "title", "musicArtist",
"lyricsArtist", "genre", "movie"
]
}
},
"aggs": {
"rate_range": {
"range": {
"field":
"rate",
"ranges": [{
"from": 0,
"to": 1000
}, {
"from": 1000,
"to": 2000
}, {
"from": 2000,
"to": 3000
}, {
"from": 3000,
"to": 4000
}, {
"from": 4000,
"to": 5000
}, {
"from": 5000,
"to": 6000
}, {
"from": 6000,
"to": 7000
}, {
"from": 7000,
"to": 8000
}, {
"from": 8000,
"to": 9000
}, {
"from": 9000,
"to": 10000
}]
}
}
}
}
return body
def search():
boosting_list=["name"]
query=[]
is_rating_query=False
numeric_value=0
query_request= request.form["query"].strip().lower()
processed_query_request=""
token_list=tokenizer.tokenize(query_request)
# boosting_list[1] = ["artist^3" if ("ගේ" in artist) else "artist" for artist in token_list][0]
# boosting_list[2] = ["genere^3" if (genere in token_list) else "genere" for genere in genere_list][0]
if(any(x in genere_list for x in token_list)):
boosting_list.append("genere^2")
if(any(x in lyrics_by_list for x in token_list)):
boosting_list.append("lyrics by^2")
if(any(x in music_by_list for x in token_list)):
boosting_list.append("music by^2")
if(any(x in key_list for x in token_list)):
boosting_list.append("key^2")
if(any(("ගේ" in x or x in artist_list) for x in token_list)):
boosting_list.append("artist^2")
if(any(x in popular_list for x in token_list)):
token_list = [i for i in token_list if i not in popular_list]
is_rating_query= True
if(any(x.isnumeric() for x in token_list)):
for x in token_list:
if (x.isnumeric()):
print(x)
token_list.remove(x)
numeric_value=int(x)
# = [ if (lyrics_by in token_list) else "lyrics by"for lyrics_by in lyrics_by_list][0]
# boosting_list[4] = ["music by^3" if (music_by in token_list) else "music by"for music_by in music_by_list][0]
# boosting_list[5] = ["key^3" if (music_by in token_list) else "key"for music_by in music_by_list][0]
# affix=word_splitter.split(query_request)["affix"]
processed_query_request =" ".join([word_splitter.split(item)["base"] if len(item)>5 else item for item in token_list])
# result = es.search(index="lyrics", doc_type="doc",body={ "query": {"match" : { "genere": affix}}})
boosting_list=list(dict.fromkeys(boosting_list))
print(numeric_value)
print(query_request)
print(token_list)
print(processed_query_request)
print(boosting_list)
print(is_rating_query)
if(len(processed_query_request)==0):
query= {"query" : {
"match_all" :{}
}
}
else:
query= {"query" : {
"multi_match" : {
"query" : processed_query_request,
"fields" : boosting_list
}
}
}
# if(len(boosting_list)==0):
# boosting_list=["name", "artist","genere","lyrics by","music by","key","lyrics" ]
if(is_rating_query):
query["sort"]=[{'views':'desc'}]
if(numeric_value !=0):
query["size"] = numeric_value
boosted_query= es.search(index="lyrics", doc_type="doc",body=json.dumps(query))
hits = boosted_query["hits"]["hits"]
if(len(hits)==0):
return render_template('ui.html', result = "No search result exists")
lyrcs_list=[lyrics["_source"] for lyrics in hits ]
return render_template('ui.html', results = lyrcs_list)
sys.path.append("/home/basa/sinling/Sinling")
from sinling import word_splitter
filepath = "new.txt"
a = {}
b = {}
with open(filepath, encoding="utf8") as fp:
for line in fp:
x = line.strip().split(' ')
for j in x:
a[j] = 0
for i in a:
results = word_splitter.split(i)
b[results['base']] = 0
f = open('roots.txt', 'w', encoding="utf8")
#print (a)
for i in b:
f.write(i + "\n")
#print (results)
f.close()
#word = "බළ්ලාට"
#results = word_splitter.split(word)
#print (results['base'])