def _suggest_batch(client, texts: Iterable[str], **kwargs) -> List[Dict]:
suggester_name = "autocorrect"
queries = (generate_suggest_query(text, name=suggester_name, **kwargs)
for text in texts)
body = generate_msearch_body(settings.ELASTICSEARCH_PRODUCT_INDEX, queries)
response = client.msearch(body=body, doc_type=settings.ELASTICSEARCH_TYPE)
suggestions = []
for r in response["responses"]:
if r["status"] != 200:
root_cause = response["error"]["root_cause"][0]
error_type = root_cause["type"]
error_reason = root_cause["reason"]
print("Elasticsearch error: {} [{}]"
"".format(error_reason, error_type))
continue
suggestions.append(r["suggest"][suggester_name][0])
return suggestions
def suggest_batch(self, texts: Iterable[str]) -> List[Dict]:
queries = [self.__generate_query(text) for text in texts]
body = generate_msearch_body(self.index_name, queries)
response = self.client.msearch(body=body)
suggestions = self.__postprocess_response(response)
return suggestions