diff --git a/sdk/cosmos/azure-cosmos/CHANGELOG.md b/sdk/cosmos/azure-cosmos/CHANGELOG.md index f9569ca962ad..d571f200c8d3 100644 --- a/sdk/cosmos/azure-cosmos/CHANGELOG.md +++ b/sdk/cosmos/azure-cosmos/CHANGELOG.md @@ -4,6 +4,7 @@ #### Features Added * Added full text policy and full text indexing policy. See [PR 37891](https://github.com/Azure/azure-sdk-for-python/pull/37891). +* Added support for full text search and hybrid search queries. See [PR 38275](https://github.com/Azure/azure-sdk-for-python/pull/38275). #### Breaking Changes diff --git a/sdk/cosmos/azure-cosmos/README.md b/sdk/cosmos/azure-cosmos/README.md index d6094bcc9c81..65a0b94bf3c4 100644 --- a/sdk/cosmos/azure-cosmos/README.md +++ b/sdk/cosmos/azure-cosmos/README.md @@ -818,6 +818,40 @@ indexing_policy = { Modifying the index in a container is an asynchronous operation that can take a long time to finish. See [here][cosmos_index_policy_change] for more information. For more information on using full text policies and full text indexes, see [here][cosmos_fts]. +### Public Preview - Full Text Search and Hybrid Search + +With the addition of the full text indexing and full text policies, the SDK can now perform full text search and hybrid search queries. +These queries can utilize the new query functions `FullTextContains()`, `FullTextContainsAll`, and `FullTextContainsAny` to efficiently +search for the given terms within your item fields. + +Beyond these, you can also utilize the new `Order By RANK` and `Order By RANK RRF` along with `FullTextScore` to execute the [BM25][BM25] scoring algorithm +or [Reciprocal Rank Fusion][RRF] (RRF) on your query, finding the items with the highest relevance to the terms you are looking for. +All of these mentioned queries would look something like this: + +- `SELECT TOP 10 c.id, c.text FROM c WHERE FullTextContains(c.text, 'quantum')` + + +- `SELECT TOP 10 c.id, c.text FROM c WHERE FullTextContainsAll(c.text, 'quantum', 'theory')` + + +- `SELECT TOP 10 c.id, c.text FROM c WHERE FullTextContainsAny(c.text, 'quantum', 'theory')` + + +- `SELECT TOP 10 c.id, c.text FROM c ORDER BY RANK FullTextScore(c.text, ['quantum', 'theory'])` + + +- `SELECT TOP 10 c.id, c.text FROM c ORDER BY RANK RRF(FullTextScore(c.text, ['quantum', 'theory']), FullTextScore(c.text, ['model']))` + + +- `SELECT TOP 10 c.id, c.text FROM c ORDER BY RANK RRF(FullTextScore(c.text, ['quantum', 'theory']), FullTextScore(c.text, ['model']), VectorDistance(c.embedding, {item_embedding}))"` + +These queries must always use a TOP or LIMIT clause within the query since hybrid search queries have to look through a lot of data otherwise and may become too expensive or long-running. +Since these queries are relatively expensive, the SDK sets a default limit of 1000 max items per query - if you'd like to raise that further, you +can use the `AZURE_COSMOS_HYBRID_SEARCH_MAX_ITEMS` environment variable to do so. However, be advised that queries with too many vector results +may have additional latencies associated with searching in the service. + +You can find our sync samples [here][cosmos_index_sample] and our async samples [here][cosmos_index_sample_async] as well for additional guidance. + ## Troubleshooting ### General @@ -954,6 +988,8 @@ For more extensive documentation on the Cosmos DB service, see the [Azure Cosmos [cosmos_concurrency_sample]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/cosmos/azure-cosmos/samples/concurrency_sample.py [cosmos_index_sample]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/cosmos/azure-cosmos/samples/index_management.py [cosmos_index_sample_async]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/cosmos/azure-cosmos/samples/index_management_async.py +[RRF]: https://learn.microsoft.com/azure/search/hybrid-search-ranking +[BM25]: https://learn.microsoft.com/azure/search/index-similarity-and-scoring [cosmos_fts]: https://aka.ms/cosmosfulltextsearch [cosmos_index_policy_change]: https://learn.microsoft.com/azure/cosmos-db/index-policy#modifying-the-indexing-policy diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_cosmos_client_connection.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_cosmos_client_connection.py index 2b52eb4872ad..f20e5649f259 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_cosmos_client_connection.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_cosmos_client_connection.py @@ -3141,7 +3141,8 @@ def _GetQueryPlanThroughGateway(self, query: str, resource_link: str, **kwargs: documents._QueryFeature.OffsetAndLimit + "," + documents._QueryFeature.OrderBy + "," + documents._QueryFeature.Top + "," + - documents._QueryFeature.NonStreamingOrderBy) + documents._QueryFeature.NonStreamingOrderBy + "," + + documents._QueryFeature.HybridSearch) if os.environ.get('AZURE_COSMOS_DISABLE_NON_STREAMING_ORDER_BY', False): supported_query_features = (documents._QueryFeature.Aggregate + "," + documents._QueryFeature.CompositeAggregate + "," + diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/document_producer.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/document_producer.py index 5037f24a0e66..14c58012663e 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/document_producer.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/document_producer.py @@ -53,6 +53,7 @@ def __init__(self, partition_key_target_range, client, collection_link, query, d self._is_finished = False self._has_started = False self._cur_item = None + self._query = query # initiate execution context path = _base.GetPathFromLink(collection_link, "docs") diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/endpoint_component.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/endpoint_component.py index 5a8e8f917c73..e8c432f8881f 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/endpoint_component.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/endpoint_component.py @@ -173,7 +173,7 @@ def __init__(self, execution_context, aggregate_operators): for operator in aggregate_operators: if operator == "Average": self._local_aggregators.append(_AverageAggregator()) - elif operator == "Count": + elif operator in ("Count", "CountIf"): self._local_aggregators.append(_CountAggregator()) elif operator == "Max": self._local_aggregators.append(_MaxAggregator()) diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/execution_dispatcher.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/execution_dispatcher.py index fd78870db7c1..cff1e5197147 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/execution_dispatcher.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/execution_dispatcher.py @@ -25,10 +25,10 @@ import os from azure.cosmos._execution_context.aio import endpoint_component, multi_execution_aggregator -from azure.cosmos._execution_context.aio import non_streaming_order_by_aggregator +from azure.cosmos._execution_context.aio import non_streaming_order_by_aggregator, hybrid_search_aggregator from azure.cosmos._execution_context.aio.base_execution_context import _QueryExecutionContextBase from azure.cosmos._execution_context.aio.base_execution_context import _DefaultQueryExecutionContext -from azure.cosmos._execution_context.execution_dispatcher import _is_partitioned_execution_info +from azure.cosmos._execution_context.execution_dispatcher import _is_partitioned_execution_info, _is_hybrid_search_query from azure.cosmos._execution_context.query_execution_info import _PartitionedQueryExecutionInfo from azure.cosmos.documents import _DistinctType from azure.cosmos.exceptions import CosmosHttpResponseError @@ -89,7 +89,7 @@ async def fetch_next_block(self): try: return await self._execution_context.fetch_next_block() except CosmosHttpResponseError as e: - if _is_partitioned_execution_info(e): #cross partition query not servable + if _is_partitioned_execution_info(e) or _is_hybrid_search_query(self._query, e): query_to_use = self._query if self._query is not None else "Select * from root r" query_execution_info = _PartitionedQueryExecutionInfo(await self._client._GetQueryPlanThroughGateway (query_to_use, self._resource_link)) @@ -126,6 +126,22 @@ async def _create_pipelined_execution_context(self, query_execution_info): self._options, query_execution_info) await execution_context_aggregator._configure_partition_ranges() + elif query_execution_info.has_hybrid_search_query_info(): + hybrid_search_query_info = query_execution_info._query_execution_info['hybridSearchQueryInfo'] + if not hybrid_search_query_info['take']: + raise ValueError("Executing a hybrid search query without TOP or LIMIT can consume many" + + " RUs very fast and have long runtimes. Please ensure you are using one" + + " of the two filters with your hybrid search query.") + if hybrid_search_query_info['take'] > os.environ.get('AZURE_COSMOS_HYBRID_SEARCH_MAX_ITEMS', 1000): + raise ValueError("Executing a hybrid search query with more items than the max is not allowed." + + "Please ensure you are using a limit smaller than the max, or change the max.") + execution_context_aggregator = \ + hybrid_search_aggregator._HybridSearchContextAggregator(self._client, + self._resource_link, + self._options, + query_execution_info, + hybrid_search_query_info) + await execution_context_aggregator._run_hybrid_search() else: execution_context_aggregator = multi_execution_aggregator._MultiExecutionContextAggregator(self._client, self._resource_link, diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/hybrid_search_aggregator.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/hybrid_search_aggregator.py new file mode 100644 index 000000000000..8a71070db39d --- /dev/null +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/aio/hybrid_search_aggregator.py @@ -0,0 +1,243 @@ +# The MIT License (MIT) +# Copyright (c) 2024 Microsoft Corporation + +"""Internal class for multi execution context aggregator implementation in the Azure Cosmos database service. +""" + +from azure.cosmos._execution_context.aio.base_execution_context import _QueryExecutionContextBase +from azure.cosmos._execution_context.aio import document_producer +from azure.cosmos._execution_context.hybrid_search_aggregator import _retrieve_component_scores, _rewrite_query_infos, \ + _compute_rrf_scores, _compute_ranks, _coalesce_duplicate_rids +from azure.cosmos._routing import routing_range +from azure.cosmos import exceptions + +# pylint: disable=protected-access +RRF_CONSTANT = 60 + + +class _Placeholders: + total_document_count = "{documentdb-formattablehybridsearchquery-totaldocumentcount}" + formattable_total_word_count = "{{documentdb-formattablehybridsearchquery-totalwordcount-{0}}}" + formattable_hit_counts_array = "{{documentdb-formattablehybridsearchquery-hitcountsarray-{0}}}" + formattable_order_by = "{documentdb-formattableorderbyquery-filter}" + + +async def _drain_and_coalesce_results(document_producers_to_drain): + all_results = [] + is_singleton = True + for dp in document_producers_to_drain: + all_results.append(await dp.peek()) + all_results.extend(dp._ex_context._buffer) + if len(document_producers_to_drain) > 1: + all_results = _coalesce_duplicate_rids(all_results) + is_singleton = False + return all_results, is_singleton + + +class _HybridSearchContextAggregator(_QueryExecutionContextBase): + """This class is a subclass of the query execution context base and serves for + non-streaming order by queries. It is very similar to the existing MultiExecutionContextAggregator, + but is needed since we're dealing with items and not document producers. + + This class builds upon the multi-execution aggregator, building a document producer per partition + and draining their results entirely in order to create the result set relevant to the filters passed + by the user. + """ + + def __init__(self, client, resource_link, options, partitioned_query_execution_info, + hybrid_search_query_info): + super(_HybridSearchContextAggregator, self).__init__(client, options) + + # use the routing provider in the client + self._routing_provider = client._routing_map_provider + self._client = client + self._resource_link = resource_link + self._partitioned_query_ex_info = partitioned_query_execution_info + self._hybrid_search_query_info = hybrid_search_query_info + self._final_results = [] + self._aggregated_global_statistics = None + self._document_producer_comparator = None + + async def _run_hybrid_search(self): + # Check if we need to run global statistics queries, and if so do for every partition in the container + if self._hybrid_search_query_info['requiresGlobalStatistics']: + target_partition_key_ranges = await self._get_target_partition_key_range(target_all_ranges=True) + global_statistics_doc_producers = [] + global_statistics_query = self._hybrid_search_query_info['globalStatisticsQuery'] + partitioned_query_execution_context_list = [] + for partition_key_target_range in target_partition_key_ranges: + # create a document producer for each partition key range + partitioned_query_execution_context_list.append( + document_producer._DocumentProducer( + partition_key_target_range, + self._client, + self._resource_link, + global_statistics_query, + self._document_producer_comparator, + self._options, + ) + ) + + # verify all document producers have items/ no splits + for target_query_ex_context in partitioned_query_execution_context_list: + try: + await target_query_ex_context.peek() + global_statistics_doc_producers.append(target_query_ex_context) + except exceptions.CosmosHttpResponseError as e: + if exceptions._partition_range_is_gone(e): + # repairing document producer context on partition split + global_statistics_doc_producers = await self._repair_document_producer(global_statistics_query, + target_all_ranges=True) + else: + raise + except StopAsyncIteration: + continue + + # Aggregate all partitioned global statistics + self._aggregate_global_statistics(global_statistics_doc_producers) + + # re-write the component queries if needed + component_query_infos = self._hybrid_search_query_info['componentQueryInfos'] + if self._aggregated_global_statistics: + rewritten_query_infos = _rewrite_query_infos(self._hybrid_search_query_info, + self._aggregated_global_statistics) + else: + rewritten_query_infos = component_query_infos + + component_query_execution_list = [] + # for each of the query infos, run the component queries for the target partitions + target_partition_key_ranges = await self._get_target_partition_key_range(target_all_ranges=False) + for rewritten_query in rewritten_query_infos: + for pk_range in target_partition_key_ranges: + component_query_execution_list.append( + document_producer._DocumentProducer( + pk_range, + self._client, + self._resource_link, + rewritten_query['rewrittenQuery'], + self._document_producer_comparator, + self._options, + ) + ) + # verify all document producers have items/ no splits + component_query_results = [] + for target_query_ex_context in component_query_execution_list: + try: + await target_query_ex_context.peek() + component_query_results.append(target_query_ex_context) + except exceptions.CosmosHttpResponseError as e: + if exceptions._partition_range_is_gone(e): + component_query_results = [] + # repairing document producer context on partition split + for rewritten_query in rewritten_query_infos: + component_query_results.extend(await self._repair_document_producer( + rewritten_query['rewrittenQuery'])) + else: + raise + except StopAsyncIteration: + continue + + # Drain all the results and coalesce on rid + drained_results, is_singleton = await _drain_and_coalesce_results(component_query_results) + # If we only have one component query, we format the response and return with no further work + if is_singleton: + self._format_final_results(drained_results) + return + + # Sort drained results by _rid + drained_results.sort(key=lambda x: x['_rid']) + + # Compose component scores matrix, where each tuple is (score, index) + component_scores = _retrieve_component_scores(drained_results) + + # Sort by scores in descending order + for score_tuples in component_scores: + score_tuples.sort(key=lambda x: x[0], reverse=True) + + # Compute the ranks + ranks = _compute_ranks(component_scores) + + # Compute the RRF scores and add them to output + _compute_rrf_scores(ranks, drained_results) + + # Finally, sort on the RRF scores to build the final result to return + drained_results.sort(key=lambda x: x['Score'], reverse=True) + self._format_final_results(drained_results) + + def _format_final_results(self, results): + skip = self._hybrid_search_query_info['skip'] or 0 + take = self._hybrid_search_query_info['take'] + self._final_results = results[skip:skip + take] + self._final_results.reverse() + self._final_results = [item["payload"]["payload"] for item in self._final_results] + + def _aggregate_global_statistics(self, global_statistics_doc_producers): + self._aggregated_global_statistics = {"documentCount": 0, + "fullTextStatistics": None} + for dp in global_statistics_doc_producers: + self._aggregated_global_statistics["documentCount"] += dp._cur_item['documentCount'] + if self._aggregated_global_statistics["fullTextStatistics"] is None: + self._aggregated_global_statistics["fullTextStatistics"] = dp._cur_item[ + 'fullTextStatistics'] + else: + all_text_statistics = self._aggregated_global_statistics["fullTextStatistics"] + curr_text_statistics = dp._cur_item['fullTextStatistics'] + assert len(all_text_statistics) == len(curr_text_statistics) + for i, all_stats in enumerate(all_text_statistics): + curr_stats = curr_text_statistics[i] + assert len(all_stats['hitCounts']) == len(curr_stats['hitCounts']) + all_stats['totalWordCount'] += curr_stats['totalWordCount'] + for j in range(len(all_text_statistics[i]['hitCounts'])): + all_text_statistics[i]['hitCounts'][j] += curr_text_statistics[i]['hitCounts'][j] + + async def __anext__(self): + """Returns the next item result. + + :return: The next result. + :rtype: dict + :raises StopAsyncIteration: If no more results are left. + """ + if len(self._final_results) > 0: + res = self._final_results.pop() + return res + raise StopAsyncIteration + + async def fetch_next_block(self): + raise NotImplementedError("You should use pipeline's fetch_next_block.") + + async def _repair_document_producer(self, query, target_all_ranges=False): + # refresh the routing provider to get the newly initialized one post-refresh + self._routing_provider = self._client._routing_map_provider + # will be a list of (partition_min, partition_max) tuples + target_partition_ranges = await self._get_target_partition_key_range(target_all_ranges) + + partitioned_query_execution_context_list = [] + for partition_key_target_range in target_partition_ranges: + # create and add the child execution context for the target range + partitioned_query_execution_context_list.append( + document_producer._DocumentProducer( + partition_key_target_range, + self._client, + self._resource_link, + query, + self._document_producer_comparator, + self._options, + ) + ) + + doc_producers = [] + for target_query_ex_context in partitioned_query_execution_context_list: + try: + await target_query_ex_context.peek() + doc_producers.append(target_query_ex_context) + except StopAsyncIteration: + continue + return doc_producers + + async def _get_target_partition_key_range(self, target_all_ranges): + if target_all_ranges: + return [item async for item in self._client._ReadPartitionKeyRanges(collection_link=self._resource_link)] + query_ranges = self._partitioned_query_ex_info.get_query_ranges() + return await self._routing_provider.get_overlapping_ranges( + self._resource_link, [routing_range.Range.ParseFromDict(range_as_dict) for range_as_dict in query_ranges] + ) diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/document_producer.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/document_producer.py index 77557c1635c7..2f3d562e290e 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/document_producer.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/document_producer.py @@ -52,6 +52,7 @@ def __init__(self, partition_key_target_range, client, collection_link, query, d self._is_finished = False self._has_started = False self._cur_item = None + self._query = query # initiate execution context path = _base.GetPathFromLink(collection_link, "docs") diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/endpoint_component.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/endpoint_component.py index 401e7531437c..d04f181a1886 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/endpoint_component.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/endpoint_component.py @@ -187,7 +187,7 @@ def __init__(self, execution_context, aggregate_operators): for operator in aggregate_operators: if operator == "Average": self._local_aggregators.append(_AverageAggregator()) - elif operator == "Count": + elif operator in ("Count", "CountIf"): self._local_aggregators.append(_CountAggregator()) elif operator == "Max": self._local_aggregators.append(_MaxAggregator()) diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/execution_dispatcher.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/execution_dispatcher.py index 9ed94b1ca5d9..8aa6e2d33f6f 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/execution_dispatcher.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/execution_dispatcher.py @@ -27,7 +27,7 @@ import os from azure.cosmos.exceptions import CosmosHttpResponseError from azure.cosmos._execution_context import endpoint_component, multi_execution_aggregator -from azure.cosmos._execution_context import non_streaming_order_by_aggregator +from azure.cosmos._execution_context import non_streaming_order_by_aggregator, hybrid_search_aggregator from azure.cosmos._execution_context.base_execution_context import _QueryExecutionContextBase from azure.cosmos._execution_context.base_execution_context import _DefaultQueryExecutionContext from azure.cosmos._execution_context.query_execution_info import _PartitionedQueryExecutionInfo @@ -42,6 +42,12 @@ def _is_partitioned_execution_info(e): e.status_code == StatusCodes.BAD_REQUEST and e.sub_status == SubStatusCodes.CROSS_PARTITION_QUERY_NOT_SERVABLE ) +def _is_hybrid_search_query(query, e): + # had to add this logic since error returned from service is different, will need to ask Neil + if e.status_code == StatusCodes.INTERNAL_SERVER_ERROR: + if "RRF" in query or "FullTextContains" in query or "FullTextScore" in query: + return True + return False def _get_partitioned_execution_info(e): error_msg = json.loads(e.http_error_message) @@ -98,10 +104,13 @@ def fetch_next_block(self): :return: List of results. :rtype: list """ + # TODO: NEED to change this - make every query retrieve a query plan + # also, we can't have this logic being returned to so often - there should be no need for this + # need to split up query plan logic and actual query iterating logic try: return self._execution_context.fetch_next_block() except CosmosHttpResponseError as e: - if _is_partitioned_execution_info(e): + if _is_partitioned_execution_info(e) or _is_hybrid_search_query(self._query, e): query_to_use = self._query if self._query is not None else "Select * from root r" query_execution_info = _PartitionedQueryExecutionInfo(self._client._GetQueryPlanThroughGateway (query_to_use, self._resource_link)) @@ -136,6 +145,22 @@ def _create_pipelined_execution_context(self, query_execution_info): self._query, self._options, query_execution_info) + elif query_execution_info.has_hybrid_search_query_info(): + hybrid_search_query_info = query_execution_info._query_execution_info['hybridSearchQueryInfo'] + if not hybrid_search_query_info['take']: + raise ValueError("Executing a hybrid search query without TOP or LIMIT can consume many" + + " RUs very fast and have long runtimes. Please ensure you are using one" + + " of the two filters with your hybrid search query.") + if hybrid_search_query_info['take'] > os.environ.get('AZURE_COSMOS_HYBRID_SEARCH_MAX_ITEMS', 1000): + raise ValueError("Executing a hybrid search query with more items than the max is not allowed." + + "Please ensure you are using a limit smaller than the max, or change the max.") + execution_context_aggregator = \ + hybrid_search_aggregator._HybridSearchContextAggregator(self._client, + self._resource_link, + self._options, + query_execution_info, + hybrid_search_query_info) + execution_context_aggregator._run_hybrid_search() else: execution_context_aggregator = multi_execution_aggregator._MultiExecutionContextAggregator(self._client, self._resource_link, diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/hybrid_search_aggregator.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/hybrid_search_aggregator.py new file mode 100644 index 000000000000..a70092546bed --- /dev/null +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/hybrid_search_aggregator.py @@ -0,0 +1,364 @@ +# The MIT License (MIT) +# Copyright (c) 2024 Microsoft Corporation + +"""Internal class for multi execution context aggregator implementation in the Azure Cosmos database service. +""" + +from azure.cosmos._execution_context.base_execution_context import _QueryExecutionContextBase +from azure.cosmos._execution_context import document_producer +from azure.cosmos._routing import routing_range +from azure.cosmos import exceptions + +# pylint: disable=protected-access +RRF_CONSTANT = 60 + + +class _Placeholders: + total_document_count = "{documentdb-formattablehybridsearchquery-totaldocumentcount}" + formattable_total_word_count = "{{documentdb-formattablehybridsearchquery-totalwordcount-{0}}}" + formattable_hit_counts_array = "{{documentdb-formattablehybridsearchquery-hitcountsarray-{0}}}" + formattable_order_by = "{documentdb-formattableorderbyquery-filter}" + + +def _retrieve_component_scores(drained_results): + component_scores_list = [] + for _ in drained_results[0]['payload']['componentScores']: + component_scores_list.append([]) + for index, result in enumerate(drained_results): + component_scores = result['payload']['componentScores'] + for component_score_index, component_score in enumerate(component_scores): + score_tuple = (component_score, index) + component_scores_list[component_score_index].append(score_tuple) + return component_scores_list + + +def _compute_rrf_scores(ranks, query_results): + component_count = len(ranks) + for index, result in enumerate(query_results): + rrf_score = 0.0 + for component_index in range(component_count): + rrf_score += 1.0 / (RRF_CONSTANT + ranks[component_index][index]) + # Add the score to the item to be returned + result['Score'] = rrf_score + + +def _compute_ranks(component_scores): + # initialize ranks as an N-D list with zeros + ranks = [[0] * len(component_scores[0]) for _ in range(len(component_scores))] + + for component_index, scores in enumerate(component_scores): + rank = 1 # ranks are 1-based + for index, score_tuple in enumerate(scores): + # Identical scores should have the same rank + if index > 0 and score_tuple[0] < scores[index - 1][0]: + rank += 1 + ranks[component_index][score_tuple[1]] = rank + + return ranks + + +def _coalesce_duplicate_rids(query_results): + unique_rids = {d['_rid']: d for d in query_results} + return list(unique_rids.values()) + + +def _drain_and_coalesce_results(document_producers_to_drain): + all_results = [] + is_singleton = True + for dp in document_producers_to_drain: + all_results.append(dp.peek()) + all_results.extend(dp._ex_context._buffer) + if len(document_producers_to_drain) > 1: + all_results = _coalesce_duplicate_rids(all_results) + is_singleton = False + return all_results, is_singleton + + +def _rewrite_query_infos(hybrid_search_query_info, global_statistics): + rewritten_query_infos = [] + for query_info in hybrid_search_query_info['componentQueryInfos']: + assert query_info['orderBy'] + assert query_info['hasNonStreamingOrderBy'] + rewritten_order_by_expressions = [] + for order_by_expression in query_info['orderByExpressions']: + rewritten_order_by_expressions.append( + _format_component_query_workaround(order_by_expression, global_statistics, + len(hybrid_search_query_info[ + 'componentQueryInfos']))) + rewritten_query = _format_component_query_workaround(query_info['rewrittenQuery'], + global_statistics, + len(hybrid_search_query_info[ + 'componentQueryInfos'])) + new_query_info = query_info.copy() + new_query_info['orderByExpressions'] = rewritten_order_by_expressions + new_query_info['rewrittenQuery'] = rewritten_query + rewritten_query_infos.append(new_query_info) + return rewritten_query_infos + + +def _format_component_query(format_string, global_statistics): + format_string = format_string.replace(_Placeholders.formattable_order_by, "true") + query = format_string.replace(_Placeholders.total_document_count, + str(global_statistics['documentCount'])) + + for i in range(len(global_statistics['fullTextStatistics'])): + full_text_statistics = global_statistics['fullTextStatistics'][i] + query = query.replace(_Placeholders.formattable_total_word_count.format(i), + str(full_text_statistics['totalWordCount'])) + hit_counts_array = f"[{','.join(map(str, full_text_statistics['hitCounts']))}]" + query = query.replace(_Placeholders.formattable_hit_counts_array.format(i), hit_counts_array) + + return query + + +def _format_component_query_workaround(format_string, global_statistics, component_count): + # TODO: remove this method once the fix is live and switch back to one above + format_string = format_string.replace(_Placeholders.formattable_order_by, "true") + query = format_string.replace(_Placeholders.total_document_count, + str(global_statistics['documentCount'])) + statistics_index = 0 + for component_index in range(component_count): + total_word_count_placeholder = _Placeholders.formattable_total_word_count.format(component_index) + hit_counts_array_placeholder = _Placeholders.formattable_hit_counts_array.format(component_index) + + if total_word_count_placeholder not in query: + continue + + full_text_statistics = global_statistics['fullTextStatistics'][statistics_index] + query = query.replace(total_word_count_placeholder, str(full_text_statistics['totalWordCount'])) + + hit_counts_array = f"[{','.join(map(str, full_text_statistics['hitCounts']))}]" + query = query.replace(hit_counts_array_placeholder, hit_counts_array) + + statistics_index += 1 + + return query + + +class _HybridSearchContextAggregator(_QueryExecutionContextBase): + """This class is a subclass of the query execution context base and serves for + non-streaming order by queries. It is very similar to the existing MultiExecutionContextAggregator, + but is needed since we're dealing with items and not document producers. + + This class builds upon the multi-execution aggregator, building a document producer per partition + and draining their results entirely in order to create the result set relevant to the filters passed + by the user. + """ + + def __init__(self, client, resource_link, options, + partitioned_query_execution_info, hybrid_search_query_info): + super(_HybridSearchContextAggregator, self).__init__(client, options) + + # use the routing provider in the client + self._routing_provider = client._routing_map_provider + self._client = client + self._resource_link = resource_link + self._partitioned_query_ex_info = partitioned_query_execution_info + self._hybrid_search_query_info = hybrid_search_query_info + self._final_results = [] + self._aggregated_global_statistics = None + self._document_producer_comparator = None + + def _run_hybrid_search(self): + # Check if we need to run global statistics queries, and if so do for every partition in the container + if self._hybrid_search_query_info['requiresGlobalStatistics']: + target_partition_key_ranges = self._get_target_partition_key_range(target_all_ranges=True) + global_statistics_doc_producers = [] + global_statistics_query = self._hybrid_search_query_info['globalStatisticsQuery'] + partitioned_query_execution_context_list = [] + for partition_key_target_range in target_partition_key_ranges: + # create a document producer for each partition key range + partitioned_query_execution_context_list.append( + document_producer._DocumentProducer( + partition_key_target_range, + self._client, + self._resource_link, + global_statistics_query, + self._document_producer_comparator, + self._options, + ) + ) + + # verify all document producers have items/ no splits + for target_query_ex_context in partitioned_query_execution_context_list: + try: + target_query_ex_context.peek() + global_statistics_doc_producers.append(target_query_ex_context) + except exceptions.CosmosHttpResponseError as e: + if exceptions._partition_range_is_gone(e): + # repairing document producer context on partition split + global_statistics_doc_producers = self._repair_document_producer(global_statistics_query, + target_all_ranges=True) + else: + raise + except StopIteration: + continue + + # Aggregate all partitioned global statistics + self._aggregate_global_statistics(global_statistics_doc_producers) + + # re-write the component queries if needed + if self._aggregated_global_statistics: + rewritten_query_infos = _rewrite_query_infos(self._hybrid_search_query_info, + self._aggregated_global_statistics) + else: + rewritten_query_infos = self._hybrid_search_query_info['componentQueryInfos'] + + component_query_execution_list = [] + # for each of the query infos, run the component queries for the target partitions + target_partition_key_ranges = self._get_target_partition_key_range(target_all_ranges=False) + for rewritten_query in rewritten_query_infos: + for pk_range in target_partition_key_ranges: + component_query_execution_list.append( + document_producer._DocumentProducer( + pk_range, + self._client, + self._resource_link, + rewritten_query['rewrittenQuery'], + self._document_producer_comparator, + self._options, + ) + ) + # verify all document producers have items/ no splits + component_query_results = [] + for target_query_ex_context in component_query_execution_list: + try: + target_query_ex_context.peek() + component_query_results.append(target_query_ex_context) + except exceptions.CosmosHttpResponseError as e: + if exceptions._partition_range_is_gone(e): + component_query_results = [] + # repairing document producer context on partition split + for rewritten_query in rewritten_query_infos: + component_query_results.extend(self._repair_document_producer( + rewritten_query['rewrittenQuery'])) + else: + raise + except StopIteration: + continue + + # Drain all the results and coalesce on rid + drained_results, is_singleton = _drain_and_coalesce_results(component_query_results) + # If we only have one component query, we format the response and return with no further work + if is_singleton: + self._format_final_results(drained_results) + return + + # Sort drained results by _rid + drained_results.sort(key=lambda x: x['_rid']) + + # Compose component scores matrix, where each tuple is (score, index) + component_scores = _retrieve_component_scores(drained_results) + + # Sort by scores in descending order + for score_tuples in component_scores: + score_tuples.sort(key=lambda x: x[0], reverse=True) + + # Compute the ranks + ranks = _compute_ranks(component_scores) + + # Compute the RRF scores and add them to output + _compute_rrf_scores(ranks, drained_results) + + # Finally, sort on the RRF scores to build the final result to return + drained_results.sort(key=lambda x: x['Score'], reverse=True) + self._format_final_results(drained_results) + + def _format_final_results(self, results): + skip = self._hybrid_search_query_info['skip'] or 0 + take = self._hybrid_search_query_info['take'] + self._final_results = results[skip:skip + take] + self._final_results.reverse() + self._final_results = [item["payload"]["payload"] for item in self._final_results] + + def _rewrite_query_infos(self): + rewritten_query_infos = [] + for query_info in self._hybrid_search_query_info['componentQueryInfos']: + assert query_info['orderBy'] + assert query_info['hasNonStreamingOrderBy'] + rewritten_order_by_expressions = [] + for order_by_expression in query_info['orderByExpressions']: + rewritten_order_by_expressions.append( + _format_component_query_workaround(order_by_expression, self._aggregated_global_statistics, + len(self._hybrid_search_query_info[ + 'componentQueryInfos']))) + + rewritten_query = _format_component_query_workaround(query_info['rewrittenQuery'], + self._aggregated_global_statistics, + len(self._hybrid_search_query_info[ + 'componentQueryInfos'])) + new_query_info = query_info.copy() + new_query_info['orderByExpressions'] = rewritten_order_by_expressions + new_query_info['rewrittenQuery'] = rewritten_query + rewritten_query_infos.append(new_query_info) + return rewritten_query_infos + + def _aggregate_global_statistics(self, global_statistics_doc_producers): + self._aggregated_global_statistics = {"documentCount": 0, + "fullTextStatistics": None} + for dp in global_statistics_doc_producers: + self._aggregated_global_statistics["documentCount"] += dp._cur_item['documentCount'] + if self._aggregated_global_statistics["fullTextStatistics"] is None: + self._aggregated_global_statistics["fullTextStatistics"] = dp._cur_item['fullTextStatistics'] + else: + all_text_statistics = self._aggregated_global_statistics["fullTextStatistics"] + curr_text_statistics = dp._cur_item['fullTextStatistics'] + assert len(all_text_statistics) == len(curr_text_statistics) + for i, all_stats in enumerate(all_text_statistics): + curr_stats = curr_text_statistics[i] + assert len(all_stats['hitCounts']) == len(curr_stats['hitCounts']) + all_stats['totalWordCount'] += curr_stats['totalWordCount'] + for j in range(len(all_stats['hitCounts'])): + all_stats['hitCounts'][j] += curr_stats['hitCounts'][j] + + def __next__(self): + """Returns the next item result. + + :return: The next result. + :rtype: dict + :raises StopIteration: If no more results are left. + """ + if len(self._final_results) > 0: + res = self._final_results.pop() + return res + raise StopIteration + + def fetch_next_block(self): + raise NotImplementedError("You should use pipeline's fetch_next_block.") + + def _repair_document_producer(self, query, target_all_ranges=False): + # refresh the routing provider to get the newly initialized one post-refresh + self._routing_provider = self._client._routing_map_provider + # will be a list of (partition_min, partition_max) tuples + target_partition_ranges = self._get_target_partition_key_range(target_all_ranges) + + partitioned_query_execution_context_list = [] + for partition_key_target_range in target_partition_ranges: + # create and add the child execution context for the target range + partitioned_query_execution_context_list.append( + document_producer._DocumentProducer( + partition_key_target_range, + self._client, + self._resource_link, + query, + self._document_producer_comparator, + self._options, + ) + ) + + doc_producers = [] + for target_query_ex_context in partitioned_query_execution_context_list: + try: + target_query_ex_context.peek() + doc_producers.append(target_query_ex_context) + except StopIteration: + continue + return doc_producers + + def _get_target_partition_key_range(self, target_all_ranges): + if target_all_ranges: + return list(self._client._ReadPartitionKeyRanges(collection_link=self._resource_link)) + query_ranges = self._partitioned_query_ex_info.get_query_ranges() + return self._routing_provider.get_overlapping_ranges( + self._resource_link, [routing_range.Range.ParseFromDict(range_as_dict) for range_as_dict in query_ranges] + ) diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/query_execution_info.py b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/query_execution_info.py index 6854a3b0611d..60e7b4ce6b01 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/query_execution_info.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/query_execution_info.py @@ -41,6 +41,7 @@ class _PartitionedQueryExecutionInfo(object): QueryRangesPath = "queryRanges" RewrittenQueryPath = [QueryInfoPath, "rewrittenQuery"] HasNonStreamingOrderByPath = [QueryInfoPath, "hasNonStreamingOrderBy"] + HybridSearchQueryInfoPath = "hybridSearchQueryInfo" def __init__(self, query_execution_info): """ @@ -115,6 +116,13 @@ def get_non_streaming_order_by(self): """ return self._extract(_PartitionedQueryExecutionInfo.HasNonStreamingOrderByPath) + def has_hybrid_search_query_info(self): + """Returns if the query is a hybrid search query. + :returns: Query is a hybrid search query. + :rtype: bool + """ + return self._extract(_PartitionedQueryExecutionInfo.HybridSearchQueryInfoPath) + def has_select_value(self): return self._extract(self.HasSelectValue) diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/aio/_cosmos_client_connection_async.py b/sdk/cosmos/azure-cosmos/azure/cosmos/aio/_cosmos_client_connection_async.py index b942c37e92a6..2e25e4cbc331 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/aio/_cosmos_client_connection_async.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/aio/_cosmos_client_connection_async.py @@ -3149,7 +3149,8 @@ async def _GetQueryPlanThroughGateway(self, query: str, resource_link: str, **kw documents._QueryFeature.OffsetAndLimit + "," + documents._QueryFeature.OrderBy + "," + documents._QueryFeature.Top + "," + - documents._QueryFeature.NonStreamingOrderBy) + documents._QueryFeature.NonStreamingOrderBy+ "," + + documents._QueryFeature.HybridSearch) if os.environ.get('AZURE_COSMOS_DISABLE_NON_STREAMING_ORDER_BY', False): supported_query_features = (documents._QueryFeature.Aggregate + "," + documents._QueryFeature.CompositeAggregate + "," + diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/documents.py b/sdk/cosmos/azure-cosmos/azure/cosmos/documents.py index bc9b7755d9e8..f42dd60e1c81 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/documents.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/documents.py @@ -412,6 +412,7 @@ class _QueryFeature: OrderBy: Literal["OrderBy"] = "OrderBy" Top: Literal["Top"] = "Top" NonStreamingOrderBy: Literal["NonStreamingOrderBy"] = "NonStreamingOrderBy" + HybridSearch: Literal["HybridSearch"] = "HybridSearch" class _DistinctType: diff --git a/sdk/cosmos/azure-cosmos/azure/cosmos/exceptions.py b/sdk/cosmos/azure-cosmos/azure/cosmos/exceptions.py index 4de3e33401b0..15b6d72b5978 100644 --- a/sdk/cosmos/azure-cosmos/azure/cosmos/exceptions.py +++ b/sdk/cosmos/azure-cosmos/azure/cosmos/exceptions.py @@ -39,7 +39,7 @@ def __init__(self, status_code=None, message=None, response=None, **kwargs): :param str message: Error message. """ self.headers = response.headers if response else {} - self.sub_status = None + self.sub_status = kwargs.pop('sub_status', None) self.http_error_message = message status = status_code or (int(response.status_code) if response else 0) diff --git a/sdk/cosmos/azure-cosmos/samples/index_management.py b/sdk/cosmos/azure-cosmos/samples/index_management.py index 2e71f6324385..7fcc4af5208e 100644 --- a/sdk/cosmos/azure-cosmos/samples/index_management.py +++ b/sdk/cosmos/azure-cosmos/samples/index_management.py @@ -770,10 +770,6 @@ def use_full_text_policy(db): { "path": "/text1", "language": "en-US" - }, - { - "path": "/text2", - "language": "en-US" } ] } @@ -791,12 +787,28 @@ def use_full_text_policy(db): print_dictionary_items(properties["indexingPolicy"]) print_dictionary_items(properties["fullTextPolicy"]) + sample_texts = ["Common popular pop music artists include Taylor Swift and The Weekend.", + "The weekend is coming up soon, do you have any plans?", + "Depending on the artist, their music can be very different.", + "Mozart and Beethoven are some of the most recognizable names in classical music.", + "Taylor acts in many movies, and is considered a great artist."] + # Create some items to use with full text search - for i in range(10): - created_container.create_item({"id": "full_text_item" + str(i), "text1": "some-text"}) + for i in range(5): + created_container.create_item({"id": "full_text_item" + str(i), "text1": sample_texts[i], + "vector": [1, 2, 3]}) + + # Run full text search queries using full text score ranking + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK FullTextScore(c.text1, ['artist']))" + query_documents_with_custom_query(created_container, query) + + # Run full text search queries using RRF ranking + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK RRF(FullTextScore(c.text1, ['music'])))" + query_documents_with_custom_query(created_container, query) - # Run full text search queries using ranking - query = "select * from c" + # Run hybrid search queries using RRF ranking wth vector distances + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK RRF(FullTextScore(c.text1, ['music'])," \ + " VectorDistance(c.vector, [1, 2, 3]))" query_documents_with_custom_query(created_container, query) # Cleanup diff --git a/sdk/cosmos/azure-cosmos/samples/index_management_async.py b/sdk/cosmos/azure-cosmos/samples/index_management_async.py index 2b91bfae8313..3519457e5f04 100644 --- a/sdk/cosmos/azure-cosmos/samples/index_management_async.py +++ b/sdk/cosmos/azure-cosmos/samples/index_management_async.py @@ -787,11 +787,28 @@ async def use_full_text_policy(db): print_dictionary_items(properties["fullTextPolicy"]) # Create some items to use with full text search - for i in range(10): - created_container.create_item({"id": "full_text_item" + str(i), "text1": "some-text"}) + sample_texts = ["Common popular pop music artists include Taylor Swift and The Weekend.", + "The weekend is coming up soon, do you have any plans?", + "Depending on the artist, their music can be very different.", + "Mozart and Beethoven are some of the most recognizable names in classical music.", + "Taylor acts in many movies, and is considered a great artist."] + + # Create some items to use with full text search + for i in range(5): + created_container.create_item({"id": "full_text_item" + str(i), "text1": sample_texts[i], + "vector": [1, 2, 3]}) + + # Run full text search queries using full text score ranking + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK FullTextScore(c.text1, ['artist']))" + await query_documents_with_custom_query(created_container, query) + + # Run full text search queries using RRF ranking + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK RRF(FullTextScore(c.text1, ['music'])))" + await query_documents_with_custom_query(created_container, query) - # Run full text search queries using ranking - query = "select * from c" + # Run hybrid search queries using RRF ranking wth vector distances + query = "SELECT TOP 3 c.text1 FROM c ORDER BY RANK RRF(FullTextScore(c.text1, ['music'])," \ + " VectorDistance(c.vector, [1, 2, 3]))" await query_documents_with_custom_query(created_container, query) # Cleanup diff --git a/sdk/cosmos/azure-cosmos/test/hybrid_search_data.py b/sdk/cosmos/azure-cosmos/test/hybrid_search_data.py new file mode 100644 index 000000000000..4d1b63ec8965 --- /dev/null +++ b/sdk/cosmos/azure-cosmos/test/hybrid_search_data.py @@ -0,0 +1,3 @@ +# cspell: disable +def get_full_text_items(): + return {"items": [{"title": "Parabolic reflector", "text": "A parabolic (or paraboloid or paraboloidal) reflector (or dish or mirror) is a reflective surface used to collect or project energy such as light, sound, or radio waves. Its shape is part of a circular paraboloid, that is, the surface generated by a parabola revolving around its axis. The parabolic reflector transforms an incoming plane wave traveling along the axis into a spherical wave converging toward the focus.", "vector": [-0.02738949842751026, 0.03491175174713135, -0.021398993209004402, -0.018760139122605324, -0.042221687734127045, 0.019897576421499252, -0.024750644341111183, -0.015590478666126728, -0.03924918174743652, 0.0045838737860322, -0.004727949388325214, 0.005251170601695776, 0.008606611751019955, -0.040553443133831024, 0.0018720327643677592, 0.03312218561768532, 0.024614151567220688, -0.004254017025232315, 0.026919357478618622, -0.009835043922066689, -0.00032867208938114345, -0.046255797147750854, -0.08153153210878372, -0.021019848063588142, -0.019017957150936127, 0.018744973465800285, 0.032121241092681885, -0.039340175688266754, -0.05620458722114563, -0.025508934631943703, 0.06970217823982239, 0.011510869488120079, 0.010593336075544357, -0.03545772284269333, -0.040735434740781784, -0.01607578620314598, -0.03160560131072998, -0.06051168218255043, 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He had been a member of the federal cabinet, in various positions, since 2006. Previously he was a provincial cabinet minister in Ontario during the governments of Premiers Mike Harris and Ernie Eves. Baird resigned from cabinet on February 3, 2015, and as a Member of Parliament on March 16, 2015.", "vector": [-0.010904606431722641, -0.013850467279553413, -0.008957103826105595, 6.772535562049598e-05, 0.006471754051744938, 0.02263883501291275, 0.00030825199792161584, -0.001327922334894538, -0.08166854083538055, 0.05962028354406357, -0.013105213642120361, -0.006485815159976482, -0.03866881877183914, 0.00401452649384737, -0.026561962440609932, 0.01598779857158661, -0.0026312372647225857, 0.016395578160881996, -0.05258959159255028, -0.032706789672374725, 0.03509722277522087, -0.006485815159976482, 0.007944684475660324, 0.046093229204416275, 0.02016402967274189, 0.025929199531674385, 0.026758821681141853, 0.009273485280573368, 0.002865007845684886, -0.0007228432223200798, -0.011277233250439167, 0.02578858658671379, 0.046740055084228516, 0.010932729579508305, 0.00228321785107255, -0.004858209751546383, 0.015678448602557182, 0.00958283618092537, -0.02761656604707241, 0.019278163090348244, 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Peter Elbling, with art direction by Michael Gross. 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-0.0148415332660079, 0.00746854767203331, -0.0002167376660509035, -0.006762858014553785, 0.0005949661135673523, 0.006127002649009228, 0.0055977352894842625, -0.0005003228434361517, -0.020685525611042976, -0.03793081268668175, -0.010974942706525326, -0.011349840089678764, 0.028139371424913406, -0.01483418233692646, -0.002447860548272729, 0.019127126783132553, 0.01980341225862503, 0.018465543165802956, 0.006575409322977066, -0.018774282187223434, 0.0002199536975240335, 0.016054436564445496, -0.011629175394773483, -0.045722801238298416, -0.0543086901307106, -0.016025032848119736, 0.0017881144303828478, -0.008968138135969639, -0.038489483296871185], "index": 3}, {"title": "Shin Sang-ok", "text": "Shin Sang-ok (October 18, 1926 \u2013 April 11, 2006) was a prolific South Korean film producer and director with more than 100 producer and 70 director credits to his name. His best-known films were made in the 1950s and 60s when he was known as the \"Prince of Korean Cinema\". He received the Gold Crown Cultural Medal, the country's top honor for an artist.", "vector": [0.041343480348587036, -0.008456620387732983, -0.021819371730089188, -0.022823551669716835, -0.014460176229476929, -0.002359820296987891, -0.013549242168664932, -0.02652466855943203, -0.03626520186662674, 0.011756065301597118, 0.00045994980609975755, -0.02861909754574299, -0.03319528326392174, -0.01073036901652813, 0.01159826572984457, 0.003980852197855711, -0.03959333896636963, 0.0111248679459095, -0.023612549528479576, -0.0214033555239439, 0.07172705978155136, -0.04237635061144829, -0.005200211890041828, -0.00976205337792635, 0.012114700861275196, 0.03118692710995674, -0.02936505898833275, 0.012494854629039764, 0.038359634578228, -0.011734547093510628, 0.0002224659692728892, -0.015736917033791542, 0.02831784449517727, 0.060480259358882904, 0.035834841430187225, -0.0009459006250835955, 0.000751789310015738, 0.027543192729353905, 0.019151125103235245, -0.012896525673568249, 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A celebrated interpreter of classical and romantic repertoire, particularly noted for his performances and recordings of Mozart, he was also a tremendous interpreter of Beethoven, Schumann, Brahms and Bart\u00f3k.In his heyday he was regarded as an amazing artist, possessed of a beautiful, natural and flawless technique that gave his concerts a unique quality.", "vector": [-0.016788292676210403, 0.008837295696139336, -0.019498568028211594, -0.02080874890089035, -0.0061591328121721745, 0.007006896659731865, 0.016672689467668533, -0.012228351086378098, 0.0063453842885792255, 0.009569455869495869, -0.051456697285175323, -0.008124403655529022, -0.002411631401628256, 0.03108467534184456, 0.007276639807969332, 0.031932439655065536, -0.06689627468585968, -0.01726355589926243, -0.0675642117857933, -0.030596569180488586, 0.02561274543404579, -0.053588952869176865, -0.013121072202920914, -0.03455280140042305, 0.04631873592734337, 0.03313986212015152, 0.009209798648953438, 0.037635575979948044, 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Monorail", "text": "\"Marge vs. the Monorail\" is the twelfth episode of The Simpsons\u2019 fourth season and originally aired on January 14, 1993. The plot revolves around Springfield's purchase of a monorail from a conman, and Marge's dislike of the purchase. It was written by Conan O'Brien and directed by Rich Moore. Guest stars include Leonard Nimoy as himself and Phil Hartman as Lyle Lanley.", "vector": [-0.019495300948619843, -0.020162204280495644, -0.025202756747603416, 0.006118453573435545, -0.008142429403960705, -0.013849884271621704, -0.009445217438042164, 0.017618665471673012, -0.029638441279530525, 0.0849914476275444, -0.0018650039564818144, 0.012267926707863808, -0.03560955449938774, 0.012089568190276623, 0.035237330943346024, 0.009476236067712307, -0.032104432582855225, 0.0029758638702332973, 0.009724386967718601, 0.01561019942164421, 0.00892565306276083, 0.0330970361828804, 0.004579146858304739, 0.05797409638762474, 0.005121975671499968, 0.009522764943540096, -0.009111765772104263, 0.007669392507523298, -0.02442728728055954, -0.004931985400617123, -0.039393845945596695, -0.004579146858304739, 0.004334873985499144, 0.008235485292971134, 0.006102944258600473, 0.013772336766123772, 0.01592814177274704, 0.02241106703877449, -0.0321974903345108, -0.002266309456899762, 0.014989824034273624, 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0.01246179360896349, -0.02680022269487381, 0.02227148227393627, 0.00545930489897728, -0.035671595484018326, 0.0088325971737504, 0.011717342771589756, -0.019448773935437202, -0.006459660362452269, -0.0015703255776315928, 0.0032530941534787416, -0.013958449475467205, -0.029995158314704895, 0.02689328044652939, 0.014408222399652004, 0.03520631045103073, 0.008313031867146492, -0.03734660893678665, -0.020022621378302574, -0.013159716501832008, 0.0447290763258934, -0.044667039066553116, -0.01963488571345806, 0.0019163788529112935, -0.016486480832099915, -0.022876348346471786, -0.02008465863764286, 0.0150983901694417, -0.030134741216897964, 0.03750170022249222, -0.023202044889330864], "index": 6}, {"title": "Quebec general election, 1989", "text": "The Quebec general election of 1989 was held on September 25, 1989, to elect members of the National Assembly of the Province of Quebec, Canada. The incumbent Quebec Liberal Party, led by Robert Bourassa, won re-election, defeating the Parti Qu\u00e9b\u00e9cois, led by Jacques Parizeau.This election was notable for the arrival of the Equality Party, which advocated English-speaking minority rights. It won four seats, but never had any success in any subsequent election.", "vector": [0.03476601466536522, 0.007190298289060593, -0.01965864561498165, 0.016584748402237892, 0.003618977963924408, 0.015810316428542137, 0.037077397108078, 0.02412651851773262, 0.030524514615535736, 0.0353379026055336, -0.05061207711696625, -0.029356909915804863, -0.0020924543496221304, -0.003788757137954235, -0.026473641395568848, 0.03128703311085701, -0.042176730930805206, 0.008608103729784489, -0.00694009754806757, -0.011610515415668488, -0.04336816072463989, -0.023471230641007423, -0.017275778576731682, 0.006153751630336046, 0.00021538874716497958, 0.012140702456235886, 0.007476242259144783, 0.02257765643298626, 0.016465604305267334, 0.03393201157450676, 0.014261453412473202, -0.006123965606093407, 0.051803506910800934, -0.02552049607038498, -0.0023054229095578194, -0.049325328320264816, 0.032883550971746445, -0.00614183722063899, 0.007214127108454704, -0.01494057010859251, 0.013701479882001877, 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P. Todd Secondary School", "text": "D.P. Todd Secondary School is a public high school in Prince George, British Columbia and is part of School District 57 Prince George.", "vector": [0.030391348525881767, 0.004553459584712982, -0.024085406213998795, 0.015098313800990582, 0.03978285938501358, 0.011728154495358467, 0.01950198784470558, 0.003330840729176998, -0.026077544316649437, 0.07231613248586655, 0.022123223170638084, -0.030181650072336197, -0.006545598153024912, 0.016296593472361565, -0.06530620157718658, 0.005856588017195463, -0.0421794168651104, 0.023201674222946167, 0.050327714532613754, -0.044366274029016495, 0.0013555529294535518, -0.042329199612140656, 0.000637053744867444, 0.01837860234081745, 0.014409303665161133, 0.019531946629285812, -0.03978285938501358, -0.009286661632359028, -0.0006927549839019775, 0.0319940447807312, -0.013218513689935207, 0.025208791717886925, 0.03714664652943611, -0.042538899928331375, 0.01996632106602192, 0.009354064241051674, 0.013188556768000126, 0.0040329573675990105, 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In 1970 he became one of the first prominent South African cricketers to speak out in favour of mixed-race sport in South Africa. Shortly afterwards he founded the Cricket Club of South Africa, one of the country's first multi-racial teams.", "vector": [0.029236363247036934, 0.020947067067027092, -0.024204127490520477, 0.004287433810532093, -0.01691819168627262, 0.06909290701150894, -0.0037741768173873425, -0.009200038388371468, 0.0289276372641325, 0.026226283982396126, -0.05458277836441994, -0.000350211194017902, -0.013823212124407291, 0.016285302117466927, -0.007143150549381971, 0.008644331246614456, -0.023231640458106995, 0.014780262485146523, 0.015305097214877605, -0.03507128730416298, 0.030857175588607788, -0.008698358200490475, 0.03173704445362091, -0.02588668465614319, 0.02793971262872219, 0.03152093663811684, 0.007532916963100433, 0.003091120161116123, -0.0069579146802425385, -0.04411696270108223, 0.0028672937769442797, 0.036584045737981796, 0.05214384198188782, -0.046957243233919144, -0.04600019007921219, -0.013792338781058788, -0.043623000383377075, -0.01852356642484665, 0.010118498466908932, 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It was originally formed as part of the Royal Navy's Fleet Air Arm for service during World War II and took part in combat operations in Norway, North Africa, Sicily and off the coast of France. Following the conclusion of hostilities, the squadron was disbanded in 1945. In 1950, it was re-raised as part of the Royal Australian Navy and subsequently took part in the Korean War.", "vector": [-0.03873995319008827, 0.019384324550628662, -0.01606990583240986, -0.022784831002354622, -0.0018580828327685595, -0.025754893198609352, 0.014262041077017784, 0.018193429335951805, 0.009670639410614967, 0.015539024956524372, 0.030360642820596695, -0.03552597016096115, -0.017691245302557945, 0.06640314310789108, 0.018021252006292343, 0.04938626289367676, -0.039945196360349655, 0.030963264405727386, 0.010402394458651543, -0.03564075380563736, 0.007374939043074846, 4.141901808907278e-05, 0.021522196009755135, -0.03739122673869133, -0.01402529701590538, 0.011815684847533703, -0.028638867661356926, 0.02683100290596485, -0.02021651528775692, -0.039514750242233276, 0.004272155929356813, -0.02124958112835884, 0.001189101254567504, 0.015653809532523155, -0.009455418214201927, 0.009663465432822704, 0.007335481699556112, 0.03739122673869133, -0.04783666506409645, 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It is owned by the Romualdez family. Romualdezes also owns Journal Publications, Inc., the proprietor of the People's Journal, a tabloid newspaper.Initially established as the Manila Standard, it merged with another newspaper of record, Today, on March 6, 2005 and became Manila Standard Today or MST and recently rebranded as The Standard.", "vector": [-0.001696532592177391, -0.02142198197543621, -0.025242570787668228, 0.0060270181857049465, -0.011845489032566547, -0.033083949238061905, -0.023273883387446404, -0.018168644979596138, -0.004170946776866913, 0.00034462448093108833, 0.062297262251377106, 0.02527593821287155, -0.032766956835985184, -0.0422433502972126, -0.036003611981868744, -0.019970493391156197, -0.01796843856573105, -0.0033075606916099787, 0.03700463846325874, 0.02150540240108967, 0.003680860623717308, -0.007849722169339657, -0.03677106648683548, 0.016441872343420982, 0.010727674700319767, 0.017534660175442696, -0.004450400359928608, -0.03970741480588913, -0.01414785161614418, -0.0008607791387476027, 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Wigtown Burghs 1708-1713.", "vector": [0.0335075706243515, -0.059773098677396774, -0.01916780136525631, -0.024586213752627373, 0.016766905784606934, 0.029912788420915604, -0.04906747117638588, -0.03432099148631096, -0.03941141068935394, 0.056099601089954376, -0.06360403448343277, 0.0534231923520565, -0.016399554908275604, 0.013552593067288399, 0.041221924126148224, 0.01248990185558796, 0.0005944838630966842, 0.009544541127979755, -0.01267357636243105, 0.006008797325193882, 0.049172427505254745, 0.0004247484903316945, 0.014969514682888985, 0.009938131086528301, 0.03227432444691658, 0.009026315063238144, 0.0028158037457615137, 0.004437719937413931, 0.020348569378256798, -0.013362357392907143, 0.00047763704787939787, 0.03930645436048508, 0.029886549338698387, -0.017672160640358925, -0.01540246233344078, -0.04169423133134842, 0.002702646655961871, -0.0799773558974266, 0.048385247588157654, 0.019351474940776825, -0.007891465909779072, -0.021555576473474503, -0.03453090414404869, 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The Clovis culture appears around 11,500\u201311,000 uncal RCYBP (uncalibrated radiocarbon years before present), at the end of the last glacial period, and is characterized by the manufacture of \"Clovis points\" and distinctive bone and ivory tools.", "vector": [-0.06872909516096115, -0.0008887971634976566, -0.02674921229481697, 0.011020402424037457, -0.04705677554011345, -0.027977492660284042, 0.042880624532699585, -0.032617662101984024, -0.004844882525503635, 0.031553152948617935, -0.008011115714907646, 0.019993670284748077, -0.030270282179117203, -0.008434190414845943, 0.05205178260803223, 0.04389054328203201, -0.022013509646058083, -0.004012381657958031, 0.005121245980262756, -0.008898206986486912, -0.0004077207704540342, -0.04329004883766174, 0.017455225810408592, -0.022805066779255867, 0.028059376403689384, 0.025957653298974037, -0.022040804848074913, -0.011695955879986286, -0.04189800098538399, -0.014097926206886768, 0.04588308557868004, -0.009901302866637707, 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Secondary Education (OESE) that administers grant programs that provide academic and supportive services to the children of families who migrate to find work in the agricultural and fishing industries. 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The conference is held on the first Friday in August (hence its name), usually in the Tel Aviv area. It lasts one day and includes technical talks, projects' status updates, social meetings and followed by a keysigning party.During the conference, the winner of Hamakor Prize for free software-related achievements is announced.", "vector": [-0.046535201370716095, 0.022717414423823357, -0.021049104630947113, -0.0025867680087685585, -0.028041807934641838, 0.03436008840799332, -0.030845988541841507, 0.042240191251039505, 0.005089233163744211, 0.042701639235019684, -0.023551568388938904, -0.08597121387720108, 0.016434628516435623, 0.010764149948954582, -0.03409386798739433, -0.009903372265398502, -0.021066851913928986, -0.01883060671389103, 0.02085387520492077, -0.01477519329637289, 0.022628674283623695, 0.03608164191246033, -0.0627213567495346, 0.015059160999953747, 0.018076317384839058, 0.001227938337251544, 0.051291659474372864, -0.0014808470150455832, 0.0054086968302726746, 0.028574246913194656, 0.04078485816717148, 0.0055107478983700275, 0.06673240661621094, -0.007316604722291231, 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playwright, screenwriter, and film director.", "vector": [0.00044372514821588993, 0.04317275434732437, -0.030205989256501198, 0.006393750198185444, -0.035494279116392136, 0.01280990894883871, -0.04580195993185043, -0.008888508193194866, -0.057304736226797104, 0.041738640516996384, 0.020152265205979347, 0.08658452332019806, -0.03274556249380112, 0.006434831768274307, 0.013325292617082596, 0.005710306111723185, -0.03991612419486046, 0.013063866645097733, -0.0015060045989230275, -0.030594393610954285, 0.1147887334227562, -0.035285137593746185, -0.07003247737884521, 0.0316699780523777, 0.08377605676651001, 0.0423959419131279, -0.0023677791468799114, 0.043202631175518036, 0.019943123683333397, 0.016776125878095627, -0.033701635897159576, 0.006457239855080843, 0.011973343789577484, -0.02278147079050541, 0.019987938925623894, 0.039348453283309937, -0.03140108287334442, 0.05058233439922333, -0.010449599474668503, 0.041141096502542496, -0.014057287946343422, -0.005056739319115877, 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As described by the biographer of the FEA's chief, Leo Crowley, the agency was designed and run by \"The Nation's #1 Pinch-hitter\".S. 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-0.013893661089241505, 0.011766515672206879, 0.013442927971482277, -0.02078118547797203, -0.010319423861801624, 0.0029613978695124388, -0.00887233205139637, -0.04383976012468338, 0.02718634530901909, 0.03196253627538681, 0.008729995228350163, 0.038209546357393265, -0.009615647606551647, -0.0006795597728341818, -0.015609611757099628, -0.0012869626516476274, -0.009536570869386196, -0.01004265807569027, -0.02729705162346363, -0.011655809357762337, -0.006417021155357361, -0.010888771153986454, 0.00013714752276428044, -0.001360108028165996, 0.029179060831665993, -0.007911558263003826, -0.0065435427241027355, 0.017554882913827896], "index": 19}, {"title": "Wenceslaus III of Bohemia", "text": "Wenceslaus III (Czech: V\u00e1clav III., Hungarian: Vencel, Polish: Wac\u0142aw, Slovak: V\u00e1clav; 6 October 1289 \u2013 4 August 1306) was King of Hungary between 1301 and 1305, and King of Bohemia and Poland from 1305. He was the son of Wenceslaus II, King of Bohemia, who was later also crowned king of Poland, and Judith of Habsburg. Still a child, Wenceslaus was betrothed to Elizabeth, the sole daughter of Andrew III of Hungary.", "vector": [0.0009226285619661212, -0.005976993124932051, -0.01476205699145794, 0.03747594356536865, 0.04673995450139046, 0.0049010030925273895, 0.0018583789933472872, -0.05267101898789406, 0.01840992644429207, -0.01265600323677063, -0.0056587886065244675, 0.04482416808605194, -0.045244064182043076, 0.018974164500832558, 0.013948503881692886, 0.0277657900005579, -0.03545518219470978, 0.037370968610048294, -0.054481834173202515, 0.003365749027580023, -0.06015046313405037, 0.005055184476077557, -0.058470867574214935, 0.004914124961942434, 0.053327109664678574, -0.022307109087705612, 0.011101067066192627, 0.0201288852840662, -0.07731381058692932, 0.04532279446721077, 0.0002995467511937022, -0.0006741339457221329, 0.014276549220085144, -0.020325712859630585, -0.0012383725261315703, -0.07789117097854614, 0.047920916229486465, -0.03821076452732086, 0.0103793665766716, -0.005609581712633371, 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in numerous commercials and guest starring roles on television. From 1974 to 1984, she starred as Laura Ingalls Wilder on the NBC series Little House on the Prairie.", "vector": [0.023501215502619743, -0.0014370293356478214, -0.02314792014658451, -0.002298187231644988, -0.03679925948381424, -0.00917155109345913, -0.03532954677939415, -0.011128807440400124, 0.05986238643527031, 0.07670751214027405, -0.046521950513124466, -0.036120928823947906, -0.02525356039404869, 0.0547749325633049, -0.032842349261045456, -0.0002612178504932672, -0.028857175260782242, -0.001039571943692863, 0.045956674963235855, 0.001017490983940661, 0.03066604770720005, 0.015643924474716187, 0.00459990743547678, 0.035668712109327316, 0.05002664029598236, 0.03490559384226799, -0.003165527479723096, 0.0022928877733647823, -0.0010510541032999754, -0.030920421704649925, -0.0055184755474328995, 0.013771457597613335, -0.001714366371743381, -0.014640565030276775, -0.034679483622312546, -0.018258310854434967, -0.05324869602918625, 0.0050450596027076244, 0.004183018580079079, 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Javits Federal Building", "text": "The Jacob K. Javits Federal Office Building at 26 Federal Plaza on Foley Square in the Civic Center district of Manhattan, New York City houses many Federal government agencies, and, at over 41 stories, is the tallest federal building in the United States. 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Iron-sulfur clusters are found in a variety of metalloproteins, such as the ferredoxins, as well as NADH dehydrogenase, hydrogenases, Coenzyme Q - cytochrome c reductase, Succinate - coenzyme Q reductase and nitrogenase.", "vector": [0.0017397718038409948, 0.024693535640835762, -0.027004428207874298, 0.030134037137031555, -0.0013097807532176375, -0.006054538302123547, 0.012346767820417881, -0.06491626799106598, 0.02242225967347622, 0.030398139730095863, -0.033567361533641815, 0.008332417346537113, 0.04101504012942314, 0.018632395192980766, 0.03142813593149185, 0.025102894753217697, -0.003322733100503683, 0.008325815200805664, -0.018183421343564987, 0.00779761141166091, 0.03924555703997612, -0.002695490838959813, -0.05551423877477646, 0.02038867399096489, 0.0066850814037024975, -0.012696702964603901, -0.005047649145126343, 0.028417373076081276, -0.10770078748464584, 0.053639113903045654, 0.04109426960349083, -0.010821579024195671, 0.008517289534211159, 0.007791008800268173, 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Osborn", "text": "Thomas Ward Osborn (March 9, 1833 \u2013 December 18, 1898) was a Union Army officer and United States Senator representing Florida.", "vector": [0.019104544073343277, -0.03285294026136398, -0.018417123705148697, 0.004163902718573809, 0.011328106746077538, 0.0011752373538911343, 0.03989899531006813, -0.016741538420319557, -0.02066555991768837, 0.061524078249931335, -0.03763623908162117, 0.020722845569252968, -0.01825959049165249, 0.019763320684432983, -0.0496947281062603, 0.050954997539520264, -0.03434235230088234, 0.011951080523431301, 0.013046656735241413, 0.012130096554756165, 0.04708826169371605, 0.028842991217970848, 0.010117961093783379, 0.024331798776984215, 0.029315592721104622, 0.051928844302892685, 0.017443278804421425, 0.01634054258465767, 0.03302479535341263, 0.013576542027294636, -0.014643475413322449, 0.023114493116736412, 0.025420213118195534, 0.03457149118185043, 0.0011868734145537019, -0.012144417501986027, -0.00537404790520668, 0.030045976862311363, 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It was created on 25 January 1938 for Sir William Birdwood, 1st Baronet. He is chiefly remembered as the commander of the Australian and New Zealand Army Corps (ANZAC) during the Gallipoli Campaign of 1915. Birdwood had already been created a Baronet, of Anzac and Totnes, on 6 October 1919.", "vector": [0.015234222635626793, 0.005028111394494772, -0.028315488249063492, 0.002980757039040327, 0.0014648291980847716, 0.04186004772782326, -0.0008469608146697283, -0.022238150238990784, -0.004067455884069204, 0.06001030281186104, 0.0016087570693343878, 0.04537563771009445, -0.059356238692998886, 0.008305240422487259, 0.028015708550810814, 0.026489561423659325, -0.04867320507764816, 0.003798336023464799, -0.0495452918112278, -0.01648784428834915, 0.05197077617049217, 0.005290417931973934, 0.004360421560704708, -0.02861526608467102, 0.009919959120452404, 0.022578807547688484, 0.029214825481176376, 0.005716240033507347, 0.048209913074970245, -0.0008635678677819669, -0.03752687945961952, -0.039134785532951355, 0.028588013723492622, -0.02790669910609722, 0.0329756885766983, -0.02559022419154644, -0.03401128947734833, 0.01561576034873724, 0.013381043449044228, -0.0021972437389194965, 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He was born in Tyler, Texas, where he was raised by his single mother and five older siblings. Among his siblings was older brother Gilbert Johnson, who played quarterback at Southern Methodist University with the iconic running back Doak Walker.", "vector": [0.07187927514314651, -0.03665780648589134, -0.014136985875666142, -0.007833498530089855, -0.03672025352716446, 0.04143518581986427, 0.0021954872645437717, -0.0465872623026371, 0.01088961586356163, 0.0881161242723465, -0.06207471713423729, 0.0063581308349967, -0.022060254588723183, 0.044776227325201035, -0.02248178794980049, 0.054799359291791916, -0.04302764683961868, 0.04274662211537361, 0.04440153390169144, -0.028773566707968712, 0.04768012464046478, -0.007404158357530832, 0.02081126719713211, -0.004839829634875059, 0.05973286181688309, 0.011826357804238796, 0.018375739455223083, -0.003979198634624481, -0.013028508983552456, -0.07394010573625565, 0.003674757666885853, 0.012880191206932068, 0.03703249990940094, -0.000524477509316057, 0.02499537728726864, 0.003684515366330743, -0.04646236449480057, -0.019890137016773224, 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The main purpose is the dissemination of EUMETSAT's own data, but various data from other providers are broadcast as well.EUMETCast is a contribution to GEONETCast and IGDDS (WMO's Integrated Global Data Dissemination Service) and provides data for GEOSS and GMES.", "vector": [-0.05129781365394592, 0.025064459070563316, -0.029005305841565132, -0.0011000141967087984, -0.024079246446490288, -0.009493101388216019, -0.060916151851415634, 0.02346140146255493, -0.04485218971967697, -0.020505767315626144, 0.02048906870186329, -0.05527205765247345, -0.029756739735603333, -0.023745276033878326, 0.020205194130539894, -0.03523384779691696, 0.0059154462069272995, -0.013283662497997284, 0.019303474575281143, 0.060648977756500244, 0.023711880668997765, -0.04271478205919266, 0.03967565298080444, 0.004817519336938858, 0.00010325678158551455, 0.002686372259631753, 0.02139078825712204, -0.006583386566489935, -0.0032562087289988995, 0.021490978077054024, 0.013074930757284164, 0.001496603712439537, 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MP4 (band), a band made up of UK Members of Parliament Mammal Paleogene zone 4, a division of the Paleogene period McLaren MP4/1, the McLaren team's Formula One car MP4: Days Since a Lost Time Accident, the fourth album by Michael Penn", "vector": [-0.02004411444067955, 0.057410698384046555, -0.030754586681723595, 0.03198733180761337, -0.028945494443178177, -0.00789677258580923, -0.07326027750968933, 0.009349650703370571, 0.018571224063634872, 0.036502059549093246, 0.04831720143556595, 0.008765297941863537, 0.043674394488334656, 0.0197239201515913, -0.029137609526515007, -0.030226267874240875, -0.06864949315786362, 0.023214029148221016, 0.0016279838746413589, 0.03169915825128555, -0.026271877810359, -0.023053932934999466, -0.03458090126514435, 0.0016089724376797676, -0.012423508800566196, 0.009429698809981346, 0.043482281267642975, 0.004546748008579016, -0.02667211927473545, 0.02596769481897354, 0.001192720839753747, -0.003071856452152133, 0.04101679101586342, 0.007212358992546797, 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region of Veneto, in the northernmost part of the province of Belluno bordering on Austria, the Trentino-Alto Adige/S\u00fcdtirol and Friuli-Venezia Giulia. 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Fungi enter the tree through wounds in the bark and decay the heartwood. The diseased heartwood softens resulting in trees being structurally weaker and prone to breakage. Heart rot is a major factor in the economics of logging and the natural growth dynamic of many older forests.", "vector": [-0.015310668386518955, 0.005258948542177677, -0.01632007770240307, -0.00492376321926713, -0.024703575298190117, -0.024272071197628975, -0.020943330600857735, -0.06756111979484558, 0.012582950294017792, -0.008707123808562756, -0.026198426261544228, 0.06552688777446747, -0.0003390384663362056, 0.006179746240377426, -0.018832044675946236, -0.002571683842688799, -0.014794405549764633, 0.002344373846426606, 0.03892777860164642, -0.008036752231419086, 0.019217316061258316, -0.0011683342745527625, -0.03516753390431404, 0.006961846258491278, 0.011049571447074413, 0.010379199869930744, 0.013191677629947662, -0.01753753423690796, -0.05624956265091896, 0.05436943843960762, 0.05310574918985367, 0.014470777474343777, 0.03102201782166958, 0.031253181397914886, -0.005551754496991634, -0.003559903707355261, -0.02240736037492752, 0.08284866809844971, -0.008969108574092388, 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With 900 stage roles to his credit, he became one of the most successful actors in the developing field of radio drama. A friend and associate of Orson Welles for many years, Collins went to Hollywood with the Mercury Theatre company and made his feature film debut in Citizen Kane, as Kane's ruthless political rival.", "vector": [0.007792048156261444, 0.013407074846327305, -0.028745872899889946, -0.006002138368785381, -0.041455380618572235, -0.028623223304748535, -0.017324179410934448, 8.85582539922325e-06, -0.028362594544887543, 0.04121008515357971, -0.060312673449516296, 0.05053141340613365, -0.01983848586678505, -0.023594612255692482, -0.0034763342700898647, -0.018336033448576927, -0.029497098177671432, 0.036733392626047134, -0.04577876254916191, 0.019240571185946465, 0.0677022784948349, -0.046116046607494354, -0.013529724441468716, 0.054272208362817764, 0.020651035010814667, 0.002437649993225932, -0.032042067497968674, -0.052279163151979446, -0.01755414716899395, -0.00985025241971016, 0.0560506209731102, 0.019424544647336006, 0.04436829686164856, 0.014464923180639744, -0.015001513063907623, 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pterodactyloid pterosaur from the late Cretaceous Period of the Bissekty Formation (middle Turonian stage, about 92 million years ago) of Uzbekistan. It is known from fragmentary remains including the distinctive, elongated neck vertebrae that characterizes members of the family Azhdarchidae, which also includes such giant pterosaurs as Quetzalcoatlus.", "vector": [0.0036942523438483477, 0.0021034819073975086, -0.028384335339069366, -0.009568016044795513, 0.02500004880130291, -0.02737060934305191, 0.005770441610366106, -0.02774490788578987, -0.019089244306087494, 0.041640754789114, -0.0025596588384360075, -0.005770441610366106, -0.023877151310443878, 0.0166563019156456, 0.04532136023044586, 0.027838481590151787, -0.06618852913379669, -0.01304587721824646, 0.016157235950231552, -0.056425563991069794, 0.03462265059351921, 0.02155338041484356, 0.03683725371956825, -0.02389274723827839, 0.0197442676872015, 0.021116698160767555, -0.013427973724901676, 7.980657392181456e-05, -0.0616033636033535, -0.025421135127544403, -0.021444208920001984, -0.01476141344755888, 0.04613234102725983, 0.039488535374403, 0.019806651398539543, 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She dominated the women's squash game in the 1960s and 1970s, winning 16 consecutive British Open titles between 1962 and 1977, and capturing the inaugural women's World Open title in 1979, whilst remaining undefeated during that period.", "vector": [0.0002245446521556005, 0.015260408632457256, -0.020244965329766273, 0.042084988206624985, -0.028726378455758095, -0.008067311719059944, 0.016702095046639442, -0.04285184293985367, 0.021211201325058937, 0.03659430891275406, -0.05475342646241188, 0.037023745477199554, -0.014378526248037815, 0.007208434399217367, -0.005705398973077536, 0.006798167247325182, 0.000541111861821264, 0.03288273140788078, -0.03996846824884415, -0.045183081179857254, 0.03177845850586891, 0.0047391620464622974, -0.002509532030671835, -0.07214569300413132, 0.034385766834020615, 0.03269868344068527, 0.004585791379213333, -0.010651611723005772, 0.00537948589771986, -0.03613419458270073, -0.025474913418293, 0.038864195346832275, -0.0382813885807991, 0.009493661113083363, 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-0.006156183313578367, -0.00408342806622386, -0.0070293438620865345, -0.003931225743144751, 0.021404452621936798, 0.01977027952671051, -0.027396416291594505, 0.013570037670433521, 0.010854428634047508, 0.011038673110306263, -0.0031862352043390274, -0.013570037670433521, -0.0012917170533910394, -0.037201449275016785, -0.025537947192788124, -0.045308224856853485, -0.028085332363843918, 0.017831703647971153, -0.02598654292523861, 0.01587710529565811, -0.01377030462026596, -0.019065342843532562, 0.03161001577973366, 0.009052032604813576, -0.03396514803171158, -0.006408518645912409], "index": 36}, {"title": "Dale Reid", "text": "Dale Reid OBE (born 20 March 1959) is a Scottish professional golfer from Ladybank, Fife. She is one of the most successful players in the history of the Ladies European Tour, with 21 tournament victories. She topped the Order of Merit in 1984 and 1987 and was made a life member of the tour after collecting her 20th title at the 1991 Ford Classic. She played for Europe in the first four Solheim Cups (1990, 1992, 1994 and 1996) and was Europe's non-playing captain in 2000 and 2002.", "vector": [0.05349265784025192, -0.01442507840692997, -0.02503391169011593, 0.022082030773162842, -0.033432912081480026, 0.02674632892012596, 0.030317943543195724, -0.014147830195724964, 0.007758881896734238, 0.03020378202199936, -0.047654129564762115, 0.01658598706126213, 0.012606654316186905, -0.0024646578822284937, -0.01751558482646942, -0.0060953907668590546, -0.03103552758693695, 0.009899403899908066, -0.05251413583755493, -0.050589703023433685, 0.03193250671029091, 0.013095916248857975, 0.03477022796869278, 0.0027887942269444466, 0.01999451220035553, 0.032552238553762436, 0.006637656129896641, -0.002529892837628722, -0.004484903067350388, 0.030790897086262703, 0.05029614642262459, 0.02762700244784355, 0.02041853964328766, -0.0036633501295000315, -0.02963297627866268, 0.015860246494412422, -0.03538995981216431, -0.01761343702673912, 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A statistical hypothesis test is a method of statistical inference. Commonly, two statistical data sets are compared, or a data set obtained by sampling is compared against a synthetic data set from an idealized model.", "vector": [-0.020572399720549583, -0.01049450971186161, -0.02618958242237568, 0.0066335927695035934, 0.027870427817106247, -0.019078314304351807, -0.05321240425109863, 0.01196704525500536, 0.007542255334556103, -0.04335719347000122, 0.03485240042209625, -0.0026020780205726624, -0.02070169523358345, 0.011263101361691952, 0.06924508512020111, -0.012024509720504284, 0.00013917256728745997, 0.013504228554666042, 0.06441804021596909, 0.015673523768782616, 0.003950705286115408, 0.006306761875748634, -0.03468000888824463, 0.0008740935008972883, 0.03827155753970146, -0.010350847616791725, -0.04916113615036011, -0.01640620082616806, -0.05324113741517067, -0.002673909068107605, 0.05852790176868439, 0.05401691421866417, 0.016750989481806755, -0.02726704813539982, 0.004011761397123337, -0.025471273809671402, 0.00393633870407939, 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-0.014879759401082993, 0.03959432989358902, -0.01210928987711668, -0.03041139431297779, 0.00471900962293148, 0.013845262117683887, 0.00332137499935925, -0.0055161393247544765, -0.0043576438911259174, -0.017458917573094368, -0.006323897745460272, -0.007074971217662096, -0.033160608261823654, -0.027562983334064484, 0.0011514099314808846, 0.011563698761165142, 0.014582164585590363, -0.03381248190999031, -0.022631404921412468, 0.024416977539658546, 0.03585313633084297, 0.000994641100987792, 0.006309726741164923], "index": 40}, {"title": "Shaun Young", "text": "Shaun Young (born 13 June 1970, Burnie, Tasmania) is a former Australian cricketer.He played in one Test at The Oval in London in 1997. He was called into the test team as a replacement as he happened to be in England at the time. He played in 138 first-class cricket matches for Tasmania and Gloucestershire taking 274 wickets with his best bowling 7/64. He was dropped from the Tasmanian team in 2002.", "vector": [0.012097458355128765, 0.030350737273693085, -0.014826327562332153, -0.0204189233481884, -0.0037938421592116356, 0.03649069368839264, -0.02919255569577217, -0.02049824967980385, -0.022513171657919884, 0.05054754391312599, -0.036332037299871445, 0.013715741224586964, 0.024401167407631874, 0.021529508754611015, 0.01913381554186344, 0.015619602985680103, -0.05410141870379448, -0.007916893810033798, -0.054513923823833466, -0.004831050522625446, 0.04204362630844116, -0.007254508323967457, -0.041980162262916565, -0.021640567108988762, 0.011478702537715435, 0.03303201124072075, -0.04597827419638634, -0.0298747718334198, -0.02290980890393257, -0.026003586128354073, 0.007750305812805891, 0.026987247169017792, 0.030921896919608116, -0.011843609623610973, -0.035031065344810486, 0.0014407874550670385, -0.018784774467349052, 0.01055850274860859, -0.039187829941511154, 0.008186607621610165, -0.007234676741063595, -0.007663045544177294, 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0.02387760579586029, 0.003060061950236559, 0.019070353358983994, -0.005584662780165672, 0.007155349012464285, -0.055148541927337646, 0.0004541504895314574, -0.03363490104675293, 0.008543581701815128, 0.01694437488913536, -0.0266699381172657, 0.008305598981678486, 0.010027008131146431, 0.0377282053232193, -0.02641608938574791, -0.006695249117910862, -0.029398806393146515, 0.009320992045104504, 0.021878549829125404, 0.008876757696270943, 0.01734101213514805, -0.019244873896241188], "index": 41}, {"title": "Fichtelberg", "text": "The Fichtelberg (German pronunciation: [\u02c8f\u026a\u00e7t\u0259lb\u025b\u0250\u032fk]) is a mountain with two main peaks in the middle of the Ore Mountains in the east German state of Saxony, near the Czech border. At 1,214.6 m (3,985 ft) above sea level, the Fichtelberg is the highest mountain in Saxony, the second highest in the Ore Mountains and used to be the highest mountain in East Germany. Its subpeak is 1,206 m (3,957 ft) high.", "vector": [0.02628307417035103, 0.04610802233219147, -0.007010071538388729, -0.0029493365436792374, -0.0032196766696870327, -0.00965715292841196, -0.03682634234428406, -0.0024630995467305183, -0.012818630784749985, 0.03442331776022911, -0.046017907559871674, 0.03223055973649025, 0.0032440824434161186, 0.024105334654450417, -0.033402033150196075, 0.023819975554943085, 0.016460714861750603, 0.012886215932667255, -0.02485627867281437, -0.05046350136399269, 0.0010372428223490715, -0.04703919589519501, -0.0456274189054966, 0.009784813039004803, -0.01281112153083086, 0.013659689575433731, -0.00562457786872983, -0.019885024055838585, -0.035594791173934937, -0.027094095945358276, 0.045807644724845886, 0.03190014138817787, 0.017737319692969322, -0.0005181520245969296, -0.00928167998790741, -0.0037265645805746317, 0.03901910036802292, -0.03430316597223282, 0.014027652330696583, -0.02372986078262329, 0.0030150441452860832, 0.012623385526239872, 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idea of green anarchism.", "vector": [-0.0031693733762949705, 0.006851681508123875, -0.035086631774902344, -0.04351947084069252, -0.014541000127792358, 0.03900187835097313, -0.026653794571757317, -0.001064104726538062, -0.03945364058017731, 0.04973116144537926, -0.024677347391843796, 0.005999927408993244, 0.011971619911491871, 0.02872435748577118, 0.020385634154081345, 0.02861141785979271, 0.018315071240067482, -0.029910225421190262, -0.015896277502179146, -0.03224431350827217, 0.03058786503970623, -0.031754907220602036, -0.031510207802057266, -0.01833389513194561, -0.01518099196255207, 0.00797637365758419, 0.04231477901339531, 3.306945291114971e-05, -0.0006446980405598879, 0.035274866968393326, -0.04841352999210358, 0.0015917454147711396, -0.014992759563028812, -0.003527016146108508, -0.009162241593003273, -0.006842270027846098, -0.020950334146618843, 0.002163503086194396, -0.0331290103495121, -0.022380905225872993, -0.028649063780903816, 0.01647038757801056, -0.025354987010359764, 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-0.009985760785639286, 0.012018677778542042, 0.004515239503234625, -0.02751966565847397, 0.06121337413787842, -0.015849219635128975, -0.014653939753770828, -0.04419711232185364, 0.01640450768172741, -0.006108161062002182, 0.02087504044175148, 0.018842123448848724, 0.01153868343681097, -0.025336163118481636, 0.005402287468314171, -0.014286885038018227, -0.03608426824212074, -0.040470097213983536, -0.02076210081577301, 0.02586321532726288, -0.017119793221354485, -0.022343257442116737, 0.029420819133520126, -0.021063273772597313, -0.013901007361710072, -0.00789637491106987, -0.015369225293397903, -0.020159754902124405, 0.013665716163814068, -0.04464887082576752], "index": 43}, {"title": "Menora Mivtachim Arena", "text": "Menora Mivtachim Arena (Hebrew: \u05d4\u05d9\u05db\u05dc \u05de\u05e0\u05d5\u05e8\u05d4 \u05de\u05d1\u05d8\u05d7\u05d9\u05dd\u200e) is a large multi-purpose sports arena in southern Tel Aviv, Israel. It is one of the major sporting facilities in the Greater Tel Aviv Area.The arena is home to the Maccabi Tel Aviv basketball club, a member of the Maccabi Tel Aviv sports club. It hosted the Israeli Super League final four, the State Cup final four and most of the Israeli national basketball team home games.", "vector": [0.05847686529159546, 0.007657866925001144, -0.021507851779460907, 0.013256796635687351, -0.0230539683252573, 0.04788367450237274, -0.020283205434679985, 0.0104936882853508, -0.00013119503273628652, 0.015859169885516167, -0.043444328010082245, -0.030294690281152725, -0.02092614397406578, 0.0645388662815094, 0.019288180395960808, -0.01665518991649151, 0.0025985464453697205, -0.033340997993946075, -0.01246077660471201, -0.04234214872121811, -0.003113280748948455, 0.002495216904208064, -0.007332569919526577, 0.013203218579292297, -0.014006893150508404, -0.00342900981195271, -0.03765787556767464, -0.0007362229516729712, -0.007347878068685532, 0.02962113358080387, -0.006345198955386877, 0.016349028795957565, 0.036494459956884384, -0.042495228350162506, -0.012996559962630272, 0.05027173459529877, -0.02141600288450718, 0.019089175388216972, 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The title plays on the idiom \"monkey's uncle\" and refers to a chimpanzee named Stanley, Merlin's legal \"nephew\" (a legal arrangement resulting from an experiment to raise Stanley as a human); Stanley otherwise has little relevance to the plot. Jones invents a man-powered airplane and a sleep-learning system.", "vector": [-0.006288918666541576, -0.010909094475209713, -0.027995027601718903, 0.0008603157475590706, -0.02231632173061371, 0.009315071627497673, -0.04423413798213005, -0.01894562691450119, -0.006317976396530867, 0.023312585428357124, 0.029389798641204834, -0.01228726003319025, -0.08468246459960938, -0.007260276470333338, -0.011033627204596996, 0.012445001862943172, -0.044134508818387985, 0.03420507535338402, -0.04516398161649704, 0.027181411162018776, 0.007546702399849892, 0.008024078793823719, -0.003127854783087969, -0.010103780776262283, 0.0308343805372715, 0.02055625431239605, -0.023777509108185768, 0.0160896684974432, -0.0028310511261224747, -0.01891241781413555, -0.019227901473641396, 0.006180990021675825, 0.010585308074951172, 0.030668336898088455, -0.0003821607679128647, 0.008509757928550243, -0.01470320113003254, -0.04831882193684578, -0.055392295122146606, -0.026218356564641, -0.006849317345768213, 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The company provides custom, hosted, turnkey solutions for its clients using the software as a service (SaaS) delivery model. Northern Light markets its strategic research portals under the tradename SinglePoint.", "vector": [0.014532499946653843, -0.01595800556242466, -0.024147484451532364, -0.034728750586509705, 0.01582406461238861, -0.022119248285889626, 0.009681954979896545, 0.02110513113439083, -0.029715565964579582, 0.04048817604780197, 0.014551633968949318, 0.018923820927739143, -0.034422602504491806, -0.013690590858459473, -0.006343020126223564, 0.005783341825008392, -0.06394682824611664, -0.00963411945849657, -0.020856386050581932, -0.0009387765312567353, 0.016895584762096405, -0.06356413662433624, 0.013604486361145973, 0.04951956495642662, 0.015230901539325714, 0.006744840182363987, 0.007247115485370159, -0.0026213990058749914, -0.0705672949552536, 0.006175594870001078, 0.025199871510267258, 0.008825695142149925, 0.049022071063518524, 0.0353601835668087, -0.029084132984280586, -0.07714949548244476, 0.02301856130361557, -0.03007911704480648, -0.009629336185753345, -0.00965803675353527, 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After a promising start in Formula 3, his single attempt at Formula One was at the 1977 British Grand Prix with the RAM team, in a March 761. He failed to pre-qualify.", "vector": [0.023267796263098717, 0.0511021688580513, -0.024106554687023163, -0.03892463073134422, -0.01671304926276207, 0.06703858822584152, 0.014018148183822632, -0.018312904983758926, -0.024261880666017532, -0.030537040904164314, -0.052966076880693436, 0.008566214703023434, 0.017489679157733917, 0.04137877747416496, 0.014654983766376972, 0.05076045170426369, -0.020456399768590927, 0.02565981261432171, -0.06747350096702576, -0.05697348341345787, 0.05231371149420738, -0.013629834167659283, -0.04016723856329918, 0.030987486243247986, -0.011129089631140232, 0.008340992033481598, 0.0024910366628319025, 0.010204900987446308, -0.008931229822337627, -0.06958593428134918, -0.03373675048351288, 0.012620216235518456, 0.042994167655706406, -0.003504537045955658, -0.018576959148049355, 0.007020723540335894, 0.041782625019550323, -0.02499191276729107, -0.040136173367500305, 0.06865397840738297, -0.02825375273823738, -0.019664239138364792, -0.026902418583631516, 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According to the pertinent legend, the asura had attempted to join Krishna and Balarama in a game of jumping, whose conditions dictated that the loser carry the victor on his back. Pralamba promptly lost, and was forced to carry Balarama on his back.", "vector": [-0.00600378168746829, -0.025160886347293854, -0.010686120018362999, 0.020333418622612953, -0.01752248778939247, 0.027895433828234673, -0.012939448468387127, -0.04873298481106758, -0.017965514212846756, 0.026352476328611374, -0.019462641328573227, 0.05964061990380287, -0.017782192677259445, -0.03495331481099129, 0.027360746636986732, 0.004193481057882309, -0.028812041506171227, 0.013481774367392063, -0.06342926621437073, 0.009952833876013756, 0.01930987276136875, -0.001443657441996038, -0.004338610917329788, -0.026077494025230408, -0.013542881235480309, 0.017537765204906464, -0.009104971773922443, -0.010342392139136791, -0.010479883290827274, -0.009547999128699303, 0.014963624067604542, -0.01698780059814453, 0.021066704764962196, 0.0260927714407444, -0.024824798107147217, -0.01740027405321598, 0.015437204390764236, -0.01435255166143179, -0.044883232563734055, -0.03712261840701103, -0.009479253552854061, 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Part of the area is taken up by the racecourse, the gallops are part of the land purchased by Stanly Wootton in 1925 in order that racehorses can be trained without interference. It is open to users such as ramblers, model aircraft flyers, golfers and cyclists. But all users are subject to the controls laid down by the purchase order; see 'The Wootton Family - Australia to Epsom' by Bill Eacott page 66/67.", "vector": [-0.018810689449310303, 0.03345569223165512, -0.017085833474993706, -0.017264828085899353, -0.01608509197831154, 0.04077818989753723, 0.024196796119213104, -0.02167460136115551, 0.019982289522886276, 0.0006885184557177126, -0.021804779767990112, -0.019331401214003563, -0.003205627901479602, -0.020047379657626152, 0.04761252552270889, 0.0410710908472538, -0.056822601705789566, 0.008294765837490559, 0.0036510799545794725, 0.027890590950846672, 0.04207997024059296, -0.0038707549683749676, -0.0302500631660223, -0.02063317969441414, -0.020372822880744934, 0.04728708043694496, -0.017199739813804626, 0.018729329109191895, -0.019754478707909584, -0.007538107223808765, 0.0016831581015139818, -0.017883174121379852, -0.015312162227928638, 0.025303306058049202, -0.030900951474905014, 0.04279594495892525, 0.008225608617067337, 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0.023301823064684868, 0.008648687042295933, -0.014701953157782555, 0.010764075443148613, 0.0016445115907117724, 0.025108039379119873, 0.03046160191297531, -0.017704179510474205, -0.023187918588519096, -0.023187918588519096, 0.050834424793720245, 0.0038219382986426353, -0.028443846851587296, 0.004047715570777655, -0.005272200331091881, 0.010048097930848598, -0.04510660097002983, 0.004507405683398247, 0.01672784611582756, 0.0017919786041602492, -0.022667206823825836, -0.0001021463394863531, -0.027125796303153038, -0.029176095500588417, -0.01910359039902687, -0.01175668090581894, 0.014335828833281994, -0.020372822880744934], "index": 52}, {"title": "Vichitravirya", "text": "In the epic Mahabharata, Vichitravirya (Sanskrit: \u0935\u093f\u091a\u093f\u0924\u094d\u0930\u0935\u0940\u0930\u094d\u092f, vicitrav\u012brya) is the younger son of queen Satyavat\u012b and king \u015aa\u1e45tanu and grandfather of the Pandavas and Kaurava. His elder brother, Chitr\u0101ngada, had initially succeeded their father to the throne of Hastinapura, but when he died childless, Vichitravirya succeeded him.Vichitravirya was still a child when he was crowned king, hence Bhishma ruled as his regent.", "vector": [0.024954576045274734, 0.006638835649937391, -0.016168976202607155, 0.04166955128312111, 0.028987513855099678, 0.0384928360581398, -0.022299041971564293, -0.06968916207551956, -0.02660497836768627, -0.00312552647665143, 0.02460712380707264, 0.014853619039058685, -0.056088853627443314, -0.02274576760828495, 0.04789888858795166, 0.04554117098450661, -0.02485530450940132, 0.02573634497821331, -0.04896606504917145, -0.017856605350971222, -0.04616162180900574, 0.018278513103723526, -0.029831327497959137, -0.030278053134679794, -0.01458062045276165, -0.02026395872235298, -0.042488548904657364, -0.021827498450875282, -0.015151435509324074, 0.004439333453774452, 0.021666180342435837, 0.03583730384707451, 0.005785713903605938, 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The population was 473 at the 2010 census. 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It has 37 floors, it is 531 ft (162 m) tall and is connected to a mall (called the Newport Centre Mall) within the complex. The mall is one of the few enclosed, regional shopping facilities in Hudson County. The building was developed by Melvin Simon & Associates in 1990.", "vector": [-0.018348103389143944, -0.03591682016849518, -0.01979321986436844, 0.005041669122874737, -0.029860321432352066, -0.03724827244877815, 0.00991284754127264, 0.025557447224855423, -0.034098245203495026, 0.08540798723697662, -0.01596122607588768, -0.025963379070162773, 0.00849208701401949, -0.03796271234750748, 0.027960561215877533, -0.016708141192793846, -0.03374102711677551, 0.010781540535390377, -0.0007687327452003956, 0.018185731023550034, -0.008289121091365814, 0.0010325881885364652, -0.03627403825521469, 0.03893695026636124, 0.030672183260321617, 0.007822300307452679, -0.006669454276561737, -0.005565320607274771, -0.06410469859838486, -0.047575172036886215, -0.03877457603812218, 0.017568714916706085, 0.0516994372010231, -0.01795841008424759, -0.006563912145793438, 0.05098499730229378, 0.017032885923981667, -0.008240409195423126, -0.035721972584724426, -0.011244302615523338, 0.03089950606226921, 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-0.04923137277364731, -0.015003228560090065, -0.00877623911947012, 0.013712366111576557, 0.014889567159116268, -0.009076627902686596, 0.037767864763736725, 0.046438563615083694, -0.0031540878117084503, -0.008914255537092686, 0.004118175245821476, 0.005585617385804653, -0.03721579909324646, 0.013614942319691181, -0.021595556288957596, -0.011203709058463573, 0.013801670633256435, -0.025151515379548073, -0.0038807052187621593, 0.010489270091056824, 0.024989143013954163, 0.006405598949640989, -0.006251344922930002, 0.009092865511775017, -0.023625213652849197, -0.007830418646335602, 0.010481150820851326, 0.03037991374731064], "index": 56}, {"title": "Thomas P. Hughes", "text": "Thomas Parke Hughes (September 13, 1923 - February 3, 2014) was an American historian of technology. He was an emeritus professor of history at the University of Pennsylvania and a visiting professor at MIT and Stanford.He received his Ph.D. from the University of Virginia in 1953.He, along with John B. 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The 3.85-square-kilometre (1.49 sq mi) lake lies about 7 kilometres (4.3 mi) south of the village of Sulitjelma near the border with Junkerdal National Park. Water flows into the lake from the large lake Balvatnet (in Saltdal) and it flows out of the lake to the north to the lake Langvatnet.", "vector": [-0.005133721977472305, -0.0011205541668459773, 0.00229629036039114, 0.049728039652109146, -0.002314091194421053, 0.0010653719073161483, -0.04172484204173088, -0.032041262835264206, -0.05878503620624542, 0.016903545707464218, 0.017060192301869392, 0.007383730728179216, -0.018996907398104668, -0.006767826620489359, -0.061690110713243484, 0.06402555853128433, 0.0158782247453928, 0.00165902532171458, -0.002232207916676998, -0.021303879097104073, -0.043348267674446106, -0.03981660678982735, 0.06863950192928314, 0.036940015852451324, 0.006486575584858656, 0.015123475342988968, -0.005899152252823114, 0.03443367779254913, -0.010630578733980656, -0.04175332561135292, 0.045057132840156555, -0.019965266808867455, -0.011833906173706055, 0.016034871339797974, 0.0285808052867651, 0.02368205226957798, -0.016846584156155586, 0.003556580049917102, 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As a boxer he was a three-time world champion, and has regularly been cited as one of the greatest fighters of his era, having never lost any of his world titles in the ring, instead relinquishing them each time in pursuit of titles in higher weight classes. His trainer was Daniel Lozano.", "vector": [0.05211864411830902, 0.020026104524731636, -0.011991768144071102, -0.012148572131991386, -0.023879000917077065, 0.01432142686098814, 0.007007643114775419, -0.012297909706830978, -0.023834198713302612, -0.004621983040124178, -0.07520616054534912, 0.03527342155575752, -0.02779163233935833, -0.012596583925187588, 0.018562600016593933, 0.03760308027267456, -0.047847602516412735, 0.00825087446719408, -0.05531445890665054, -0.07867077738046646, 0.00013743678573518991, 0.00100242521148175, -0.005189463961869478, 0.008400211110711098, 0.04512966796755791, 0.02590998448431492, -0.005827879998832941, 0.007877531461417675, -0.019413821399211884, 0.017576975747942924, -0.02556650899350643, 0.019249550998210907, 0.026223592460155487, 0.03864843770861626, 0.0020701854955404997, -0.03145039081573486, 0.0540301576256752, 0.025581443682312965, 0.00835540983825922, 0.005663609132170677, 0.02422247640788555, -0.05501578375697136, -0.041694916784763336, 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Ogrons are low-intelligence, ape-like hominids who live in scattered communities on an unnamed planet on the outer fringes of the Milky Way, far from the central spaceways. The dominant lifeform on their home planet is a giant slug-like lizard named the Eater, which preys on and is prayed to by the Ogrons. Ogrons are hired mercenaries.", "vector": [-0.020616374909877777, -0.020223993808031082, -0.02184256725013256, -0.03233877196907997, -0.01177961751818657, 0.003856373718008399, 0.01400311291217804, -0.055652767419815063, -0.029771940782666206, 0.0008685526554472744, -0.037701316177845, 0.056993402540683746, -0.02800622582435608, 0.01667621172964573, 0.024327648803591728, 0.015204780735075474, -0.01393771544098854, 0.03691655397415161, -0.02651844546198845, -0.010136520490050316, 0.03449686989188194, -0.00145610305480659, -0.01051255315542221, -0.04303116351366043, 0.055521972477436066, 0.023232251405715942, 0.037308935075998306, 0.00985858403146267, 0.019897008314728737, -0.012400888837873936, 0.01728113181889057, 0.008195050060749054, 0.006748143117874861, 0.04659529775381088, -0.022839870303869247, -0.04993053898215294, -0.002352244919165969, -0.014117557555437088, 0.0265511441975832, -0.017133990302681923, 0.03318893164396286, -0.015899622812867165, 0.005530125927180052, 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0.01688249222934246, 0.007507725153118372, -0.015956882387399673, 0.011210164986550808, -0.032388437539339066, -0.025758855044841766, -0.0012529357336461544, -0.01922420784831047, 0.01735716499388218, 0.02098049223423004, 0.001587183796800673, 0.0014457710785791278, -0.0012915028491988778, -0.022531086578965187, -0.011067763902246952, -0.010070952586829662, -0.002846052870154381, 0.008097109384834766], "index": 61}, {"title": "Shining Tears", "text": "Shining Tears (\u30b7\u30e3\u30a4\u30cb\u30f3\u30b0\u30fb\u30c6\u30a3\u30a2\u30fc\u30ba, Shainingu Ti\u0101zu) is an action role-playing game co-developed by Nextech and Amusement Vision and published by Sega in 2004 for the PlayStation 2 as a part of the Shining Force video game series. It tells the story of a mysterious boy named Xion.An anime adaptation for the game was announced by Sega, entitled Shining Tears X Wind. It is produced by Studio Deen and began airing in early April 2007.", "vector": [-0.017639024183154106, 0.018688242882490158, -0.022535374388098717, 0.020056787878274918, 0.007146846037358046, -0.040873877704143524, 0.023827889934182167, -0.0217902772128582, 0.004938166588544846, 0.05346449092030525, -0.027340488508343697, -0.03054896555840969, 0.020452145487070084, -0.021927133202552795, 0.0217902772128582, 0.009503784589469433, -0.037194013595581055, 0.017182843759655952, -0.028252851217985153, -0.0009584567160345614, -0.022261666133999825, 0.031111590564250946, 0.036342471837997437, -0.01329009234905243, 0.0220335740596056, -0.005135845392942429, -0.020452145487070084, -0.031202826648950577, -0.05997268483042717, 0.05136605724692345, -0.020391320809721947, -0.027735846117138863, 0.02375185862183571, 0.02084750309586525, -0.019250866025686264, 0.010887536220252514, -0.008036400191485882, 0.026808276772499084, 0.005284104496240616, -0.005181463435292244, 0.009017190895974636, 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Developed during the 1960s, it was used for four launches between 1969 and 1971. Its final flight was the first and only successful orbital launch to be conducted by the United Kingdom, and placed the Prospero satellite into low Earth orbit.Black Arrow originated from studies by the Royal Aircraft Establishment for carrier rockets based on the Black Knight rocket, with the project being authorised in 1964.", "vector": [-0.014135890640318394, 0.03546791151165962, -0.020262327045202255, -0.057675138115882874, -0.02767062932252884, 0.001184621243737638, -0.028501631692051888, 0.021641438826918602, -0.07178451120853424, 0.007664675824344158, 0.02689266949892044, -0.011519115418195724, -0.024258213117718697, -0.021234776824712753, -0.0010912438156083226, 0.07192595303058624, -0.030004510655999184, 0.03173723816871643, 0.020280007272958755, -0.020527539774775505, 0.019519727677106857, -0.03336388245224953, -0.030216680839657784, -0.01761903055012226, -0.006926497910171747, 0.023480253294110298, -0.006011510733515024, 0.01863568276166916, -0.03702383115887642, 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-0.0008741001365706325, 0.016319483518600464, -0.01741570048034191, -0.01904234290122986, -0.024346617981791496, 0.005326375365257263, 0.0024686974938958883, -0.02669817954301834, -0.00946812890470028, -0.013039673678576946, -0.0012951268581673503, -0.011846211738884449, -0.02784743905067444, -0.019979432225227356, 0.006303245667368174, -0.042575638741254807, 0.017088603228330612, -0.008102278225123882, -0.00448432145640254, -0.0018609161488711834, -0.019891027361154556, 0.006373969372361898, 0.043070703744888306, -0.016160354018211365, 0.007107727229595184, 0.01833510771393776, 0.020386092364788055, 0.0017194688552990556, -0.04147942364215851, -0.01763671077787876, -0.008897919207811356, -0.038721200078725815, -0.01865336298942566, 0.02694571204483509, 0.04063073918223381, 0.038190774619579315, -0.021358544006943703, -0.03177260234951973, -0.008314449340105057, -0.016743825748562813, 0.056755732744932175, -0.009105670265853405], "index": 66}, {"title": "Carol Bruneau", "text": "Carol Bruneau (born 1956) is a Canadian writer. She lives in Halifax, Nova Scotia, where she is currently a part-time faculty member of the Nova Scotia College of Art and Design University, where she teaches writing in the foundation program. She has a Master's degree from Dalhousie University.Her book Purple for Sky (2000) won the Thomas Head Raddall Award and the fiction category of the Dartmouth Book Awards in 2001.", "vector": [-0.04255025461316109, -0.04091265797615051, -0.0324244424700737, -0.019460123032331467, -0.005799826234579086, -0.002688390202820301, -0.040776193141937256, -0.03392557427287102, -0.013189488090574741, 0.052512310445308685, -0.002818033332005143, -0.03245173394680023, 0.004772915970534086, -0.021206894889473915, 0.010849087499082088, -0.027593526989221573, -0.026706494390964508, 0.03258820250630379, 0.00674485694617033, 0.020715614780783653, 0.00634910399094224, -0.029831577092409134, 0.019596589729189873, 0.013817233964800835, 0.019896816462278366, 0.059171877801418304, 0.024604910984635353, -0.009354778565466404, 0.024563970044255257, -0.026624614372849464, 0.01645786128938198, -0.0003518277080729604, 0.023349419236183167, -0.022271333262324333, -0.046098385006189346, 8.415878255618736e-06, 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-0.014741228893399239, 0.011010859161615372, 0.04943523183465004, 0.01566598378121853, -0.008424678817391396, 0.005670004524290562, 0.0008708766545169055, -0.006434103474020958, 0.006179403979331255, -0.020046817138791084, -0.00035413040313869715, 0.063698410987854, -0.04031306877732277, 0.023730164393782616, -0.038651641458272934, -0.02565804496407509, 0.04658259451389313, 0.005474081728607416, -0.017821134999394417, -0.04159832000732422, 0.037617169320583344, 0.024090662598609924, 0.004682553932070732, -0.01896532252430916, -0.029419761151075363, -0.011097065173089504, 0.009521846659481525, -0.018918301910161972, -0.01896532252430916, -0.0402190238237381, 0.0034952620044350624, 0.013079803436994553, 0.03153572604060173, -0.011465400457382202, -0.010407417081296444, -0.014600164256989956, -0.029576500877738, 0.022225478664040565, 0.05266403779387474, 0.0015115441055968404, 0.000897326273843646, -0.022664345800876617], "index": 70}, {"title": "Tablets of Bah\u00e1\u2019u\u2019ll\u00e1h Revealed After the Kit\u00e1b-i-Aqdas", "text": "The Tablets of Bah\u00e1\u2019u\u2019ll\u00e1h Revealed After the Kit\u00e1b-i-Aqdas are selected tablets written by Bah\u00e1'u'll\u00e1h, the founder of the Bah\u00e1'\u00ed Faith, and published together as of 1978.As his mission drew to a close after his writing of the Kit\u00e1b-i-Aqdas in 1873, he continued to write unnumbered tablets and letters, doing so until the last days of his life in 1892.Six of the tablets in this volume were translated into English and published in 1917.", "vector": [0.03467293083667755, -0.0244834516197443, -0.007326378487050533, 0.036854337900877, 0.01987665891647339, -0.039408884942531586, -0.016231408342719078, -0.009436030872166157, -0.023134421557188034, 0.059873949736356735, 0.0033653981518000364, -0.006041930057108402, 0.009371450170874596, -0.0044919815845787525, -0.023823287338018417, -0.0006215940811671317, 0.022215932607650757, 0.0018019949784502387, -0.030912868678569794, -0.029621245339512825, 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0.049094706773757935, -0.028564464300870895, -0.0637994036078453, -0.04642651975154877, 0.0028386584017425776, -0.01660207472741604, 0.019255442544817924, -0.01568303257226944, 0.00571437506005168, -0.011584394611418247, 0.005436438601464033, -0.02359866350889206, 0.012325558811426163, 0.004632275551557541, 0.021389994770288467, 0.034923650324344635, -0.01491963304579258, 0.003652086015790701, 0.015935027971863747, -0.03602057322859764, -0.08692372590303421, -0.003729908261448145, 0.010835818946361542, 0.018603218719363213, 0.016676191240549088], "index": 72}, {"title": "173 Hours in Captivity", "text": "173 Hours In Captivity: The Hijacking of IC 814 is a 2000 book (ISBN 81-7223-394-9) written by Neelesh Misra, a New Delhi-based correspondent of the Associated Press. The book is about the hijacking of Indian Airlines Flight 814 on its journey from Kathmandu to New Delhi on Christmas Eve, December 24, 1999.", "vector": [-0.006944699212908745, -0.001118911779485643, -0.013426940888166428, -0.042452022433280945, -0.04637115076184273, 0.02707335352897644, -0.03354775533080101, 0.03241904824972153, -0.01223552506417036, 0.020645979791879654, 0.011091139167547226, 0.004393345210701227, 0.006885912269353867, -0.030600570142269135, -0.06126384809613228, -0.04677874222397804, -0.007748120930045843, 0.0044325366616249084, -0.022480132058262825, -0.008622086606919765, 0.0149632403627038, 0.0014735930599272251, -0.013278014026582241, -0.006976052187383175, 0.04677874222397804, 0.012486349791288376, 0.0073522888123989105, 0.022401750087738037, 0.05170116946101189, -0.02486296370625496, -0.06051137298345566, -0.02390669658780098, -0.005541650578379631, -0.020128654316067696, -0.021414129063487053, -0.004115086980164051, -0.03489593788981438, 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according to Biblical regulations had a special impact on the ownership and management of land in the Land of Israel; there is some debate whether it was the 49th year (the last year of seven sabbatical cycles, referred to as the Sabbath's Sabbath), or whether it was the following (50th) year. Jubilee deals largely with land, property, and property rights.", "vector": [-0.007218821905553341, 0.000699120108038187, -0.013559678569436073, 0.007747226394712925, -0.03489097207784653, -0.006568477489054203, -0.0091129494830966, -0.010665646754205227, -0.01128347311168909, 0.0755700096487999, -0.010405508801341057, -0.06435156613588333, 0.005763676483184099, 0.03719969466328621, 0.015502582304179668, 0.005336887668818235, 0.034143075346946716, -0.011478576809167862, 0.04422341287136078, 0.012234602123498917, -0.038858070969581604, -0.005324693862348795, -0.01055996585637331, -0.00483287125825882, -0.017786916345357895, -0.012047627940773964, 0.012462222948670387, -0.01845351979136467, -0.03349273279309273, 0.02832249365746975, 0.02861514873802662, 0.007332631852477789, -0.00664164125919342, -0.014283186756074429, 0.02687547728419304, 0.0005273885908536613, -0.00814149808138609, 0.006373374257236719, -0.03963848575949669, -0.0915684774518013, 0.013177601620554924, 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All of Sonora, the Baja California Peninsula, and the islands of the Gulf of California are included.", "vector": [0.07355865836143494, 0.03149097412824631, -0.017765160650014877, -0.003800176316872239, 0.02606974169611931, -0.06207840517163277, 0.028062840923666954, -0.048791076987981796, -0.028142565861344337, 0.046080462634563446, -0.083125539124012, 0.007553847040981054, 0.0014533017529174685, 0.0022588460706174374, -0.00465388735756278, 0.041084423661231995, -0.005584000609815121, 0.016556013375520706, 0.03313860297203064, 0.05104992166161537, 0.013081376440823078, 0.01733996532857418, 0.027531348168849945, 0.005813207011669874, 0.015652474015951157, 0.06627720594406128, -0.04695742577314377, -0.016290266066789627, -0.04669167846441269, -0.024594847112894058, 0.011108207516372204, -0.03675275668501854, 0.03816121071577072, 0.061972107738256454, -0.011387242004275322, 0.027664221823215485, -0.003411521902307868, 0.009938922710716724, 0.005849746987223625, 0.03106577694416046, 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Multnomah villages were located throughout the Portland basin and on both sides of the Columbia River. The Multnomah spoke a dialect of the Upper Chinookan language in the Oregon Penutian family.", "vector": [0.006801684387028217, 0.03566597402095795, -0.02064003236591816, -0.024768037721514702, 0.001402728259563446, -0.006719124037772417, -0.05415944382548332, -0.035157911479473114, -0.06818196177482605, 0.006249166559427977, -0.04084821045398712, 0.021059183403849602, -0.02380272001028061, -0.009862760081887245, 0.012002971954643726, -0.03627564758062363, -0.0471227802336216, 0.04023853689432144, 0.040772002190351486, 0.03498008847236633, -0.0061539048328995705, -0.01083442848175764, 0.0015734054613858461, 0.005842716433107853, 0.061018284410238266, 0.00843383464962244, -0.0022624649573117495, -0.02572065405547619, 0.018366452306509018, -0.0035088052973151207, 0.007811457850039005, -0.03492928296327591, 0.026063596829771996, 0.011958517134189606, -0.004286775831133127, 0.012606295756995678, 0.02565714716911316, 0.010961444117128849, 0.0018242612713947892, 0.017007386311888695, 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It is the largest extant member of its family, with males averaging 43\u201345 kg (95\u201399 lb), and females 36\u201338.5 kg (79\u201385 lb). Like the red wolf, it is distinguished from other Canis species by its larger size and less pointed features, particularly on the ears and muzzle.", "vector": [-0.007719092071056366, -0.008680134080350399, -0.00616989191621542, 0.01832900010049343, 0.03856470808386803, 0.003325206460431218, 0.0006165086524561048, -0.030169041827321053, 0.006873374804854393, 0.02584819495677948, -0.06003054976463318, 0.0001552083413116634, 3.4147036785725504e-05, -0.03542786464095116, -0.016483798623085022, 0.05815459415316582, -0.029261818155646324, 0.011740093119442463, 0.024079877883195877, 0.021388959139585495, 0.02177337557077408, 0.004193988628685474, 0.0741770938038826, -0.01983591355383396, 0.028446853160858154, -0.0006419763085432351, -0.015714963898062706, -0.03521259129047394, -0.047237154096364975, -0.02111217752099037, 0.034812796860933304, 0.014138855040073395, 0.02944633737206459, 0.05630939453840256, -0.019067080691456795, -0.055110011249780655, 0.010679102502763271, 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Active primarily as a cable television distributor, the company also had some holdings in broadcast media and publishing.The company was founded in 1968 by chairman Geoffrey Conway, with shareholders including Jerry Grafstein, Michael Koerner and Ken Lefolii.", "vector": [0.03923020139336586, -0.0008029687451198697, -0.03432251885533333, -0.020537244156003, 0.018380364403128624, 0.006474546156823635, -0.051264964044094086, 0.023960119113326073, -0.05707915872335434, 0.012910017743706703, -0.026789069175720215, -0.026398329064249992, -0.044325437396764755, -0.01742696203291416, -0.009049516171216965, -0.01351175643503666, -0.021959533914923668, 0.02449152246117592, -0.003225550753995776, 0.05057726055383682, 0.04013671353459358, -0.02777373045682907, -0.024100784212350845, -0.01627037301659584, 0.02320989966392517, -0.00029647324117831886, -0.024319598451256752, 0.00419653719291091, 0.039105162024497986, -0.011948799714446068, 0.020756058394908905, 0.031806159764528275, 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-0.027336103841662407, -0.023647526279091835, 0.018208440393209457, 0.022381532937288284, -0.007017673458904028, 0.026882845908403397, -0.006783229764550924, -0.005161662586033344, -0.01498093456029892, -0.03607302904129028, 0.039917901158332825, 0.013621163554489613, -0.01223794650286436, -0.020771687850356102, -0.0038057982455939054, 0.002893422730267048, -0.011855022981762886, -0.028305135667324066, -0.019536951556801796, -0.014199457131326199, -0.0349789597094059, -0.021053019911050797, -0.03061831183731556, 0.006892636884003878, -0.03882383182644844, 0.010143585503101349, -0.028602097183465958, 0.03572917729616165, -0.008346186019480228, -0.029696166515350342, -0.007982798852026463, 0.030071277171373367, 0.014637084677815437, 0.01697370409965515], "index": 79}, {"title": "Hardtack (game)", "text": "Hardtack is a set of rules for American Civil War miniature wargaming by Lou Zocchi. It was published as a thirty-page pamphlet by Guidon Games in 1971, with an introduction by Gary Gygax and artwork by Don Lowry. Hardtack was the first set of American Civil War rules published in the United States and had an early following.", "vector": [-0.01987696997821331, -0.048177510499954224, -0.03492619842290878, 0.007129239849746227, -0.02134193852543831, -0.005335484631359577, 0.00368323246948421, 0.0022453151177614927, -0.0007616175571456552, 0.05267230421304703, 0.034360188990831375, 0.036324579268693924, 0.029033027589321136, 0.023705866187810898, -0.0160647202283144, -0.03136365860700607, -0.006846234202384949, 0.026719041168689728, -0.027734531089663506, -0.04225104674696922, 0.1127360463142395, 0.019960206001996994, 0.008931318297982216, 0.027068637311458588, 0.042384225875139236, 0.0035105159040540457, 0.007861724123358727, -0.019011305645108223, 0.006030512508004904, -0.0106210270896554, -0.007711898069828749, 0.019460784271359444, 0.02725175768136978, 0.004086931236088276, 0.051740050315856934, -0.012410620227456093, 0.004365774802863598, 0.04488133266568184, 0.0036020763218402863, 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They have been used for regional transport and patrol needs in French Overseas Departments and Territories since the 1970s. On 9 January 2014 it was announced that the two remaining Batrals in French service would be replaced in 2015/16 by three 1500-tonne B\u00e2timents Multimission (B2M) at a cost of ~\u20ac100m (US$136m).", "vector": [-0.047751978039741516, 0.010834340937435627, -0.013125896453857422, -0.0066219219006598, -0.026049597188830376, 0.006436575669795275, -0.013985229656100273, 0.0018176586600020528, -0.026369741186499596, 0.005151787772774696, 0.03194698318839073, 0.0035573875065892935, -0.007881435565650463, -0.007308546453714371, 0.012687805108726025, -0.024549975991249084, -0.032283976674079895, -0.0019324470777064562, 0.020169060677289963, -0.0037616898771375418, 0.015282654203474522, -0.01786065474152565, 0.007986745797097683, 0.006411300972104073, -0.02047235518693924, -0.0005544595769606531, 0.009216771461069584, -0.009924458339810371, 0.003178269835188985, -0.051795899868011475, 0.042629677802324295, 0.019343426451086998, -0.006874667014926672, -0.01559437345713377, 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Department, a sub-division of the Ministry of Education. There are currently ten parks, with four them registered as World Heritage Sites by the UNESCO.", "vector": [0.027070073410868645, 0.0030636305455118418, -0.026276154443621635, 0.007753514684736729, 0.046072907745838165, 0.043767981231212616, 0.0015878378180786967, -0.02827375754714012, -0.018695509061217308, -0.012209705077111721, -0.012600261718034744, -0.007836747914552689, -0.0037391020450741053, -0.02617371454834938, 0.029503051191568375, -0.01740219071507454, -0.04448506981134415, -0.027607889845967293, 0.03928618133068085, -0.005637464579194784, -0.022677909582853317, 0.0053077321499586105, -0.019066859036684036, -0.03144943341612816, 0.020667502656579018, 0.032653115689754486, 0.011249318718910217, -0.010244115255773067, -0.009091651998460293, 0.028529860079288483, -0.013278934173285961, 0.004376158118247986, 0.08430906385183334, -0.011799939908087254, -0.01489238254725933, 0.016224117949604988, 0.03828737884759903, -0.0028347386978566647, -0.020321764051914215, 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He was able to take several photographs, exposing wet plates at 1/100 second. These represent the earliest photos of an unidentified flying object.", "vector": [0.03938209265470505, -0.020690200850367546, -0.013534711673855782, -0.04537702351808548, -0.04417803883552551, -0.03200371563434601, -0.004519256297498941, 0.02880641631782055, 0.034647632390260696, 0.051433444023132324, -0.06960269808769226, 0.01139037124812603, -0.007412964012473822, -0.020367396995425224, -0.033387161791324615, 0.03314121440052986, -0.01301207672804594, 0.028883274644613266, -0.02583969384431839, -0.0472831055521965, 0.01958344504237175, -0.008277617394924164, -0.00106928835157305, 0.03304898366332054, 0.05020371451973915, 0.01393437385559082, 0.021489525213837624, 0.03861350938677788, -0.04762127995491028, 0.01337330974638462, 0.05469222739338875, 0.024825166910886765, 0.00033697474282234907, 0.028698815032839775, 0.02238108031451702, -0.01876874826848507, 0.004576900042593479, -0.04602263122797012, 0.018784120678901672, -0.011805404908955097, 0.007778040133416653, 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The island is the fourth largest in Polynesia, behind the two main islands of New Zealand and the Island of Hawaii.The island of Savai'i is also referred to by Samoans as Salafai, a classical Samoan term used in oratory and prose.", "vector": [0.001201200415380299, -0.008997833356261253, -0.009939546696841717, 0.0025519065093249083, 0.028760071843862534, 0.023962143808603287, -0.005416572093963623, -0.03832843154668808, -0.0399506539106369, 0.005938982591032982, -0.004626082256436348, 0.007719302084296942, -0.06769339740276337, -0.0266704298555851, 0.012778435833752155, 0.04440489038825035, 0.011025610379874706, 0.048639167100191116, 0.027316570281982422, -0.0009906896157190204, -0.0015895713586360216, 0.009286534041166306, -0.023920901119709015, 0.039263270795345306, -0.013658285140991211, 0.019824102520942688, 0.006313605699688196, -0.003629378043115139, -0.05141618847846985, -0.007643690332770348, -0.0017090040491893888, -0.012682202272117138, -0.0012433025985956192, 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Two of his sons, Augustus Charles and Francis Thomas, became renowned Australian explorers.Joshua Gregory entered the army in 1805 as an ensign in the 78th Highlanders (Ross-shire Buffs). At the age of 16 he saw active service when his regiment was sent to Sicily at the height of the Napoleonic Wars.", "vector": [0.037484049797058105, 0.012617848813533783, -0.019056489691138268, -0.029858311638236046, -0.04968523606657982, 0.047358203679323196, 0.036855123937129974, -0.0008225186611525714, -0.035848841071128845, 0.008038473315536976, -0.07194925099611282, 0.025047019124031067, 0.03226395696401596, 0.033396024256944656, 0.025597330182790756, 0.0340563990175724, -0.031210504472255707, 0.029040705412626266, 0.014646138064563274, 0.0196854155510664, 0.040377113968133926, -0.02231118641793728, 0.022358356043696404, -0.007087221369147301, 0.10320692509412766, 0.004068371839821339, 0.007767248898744583, 0.023883504793047905, -0.03716958686709404, 0.00625389302149415, 0.030078435316681862, 0.022075338289141655, 0.03638342767953873, -0.014072242192924023, -0.012531370855867863, -0.01423733588308096, -0.008121020160615444, -0.011996783316135406, 0.0055070421658456326, 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Everything known about him comes from the Anglo-Saxon Chronicle. There he is stated to have been the son of Cerdic, and also (in the regnal list in the preface) to have been the son of Cerdic's son, Creoda. During his reign it is said that the Saxons expanded into Wiltshire against strong resistance and captured Searobyrig or Old Sarum, near Salisbury, in 552.", "vector": [0.0034433980472385883, 0.06477025151252747, -0.021929355338215828, -0.0037375078536570072, 0.024573039263486862, 0.040580544620752335, -0.011288529261946678, -0.04845872148871422, -0.023819589987397194, 0.018479349091649055, -0.034526508301496506, -0.012458359822630882, -0.058108165860176086, -0.02717706747353077, 0.0484851598739624, 0.024202924221754074, -0.05305873230099678, -0.015848884359002113, -0.012127898633480072, -0.00563765550032258, 0.013826466165482998, 0.00533363176509738, 0.00780547596514225, -0.010931632481515408, 0.05905989184975624, 0.01290778536349535, -0.03291386365890503, -0.008241684176027775, -0.048379410058259964, -0.00652328971773386, 0.023753497749567032, 0.01587532088160515, -0.01547876838594675, 0.06027598679065704, 0.0008290426922030747, -0.04874952882528305, 0.019298890605568886, 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0.017713114619255066, 0.021517455577850342, 0.010455189272761345, 0.022340379655361176, -0.01863047294318676, 0.019305001944303513, -0.02822226658463478, -0.0017158315749838948, -0.013659199699759483, 0.00955132208764553, 0.004603656008839607, 0.03008396551012993, -0.0040640332736074924, 0.019588302820920944, 0.024310002103447914, -0.02122066169977188], "index": 90}, {"title": "Fuzhou", "text": "Fuzhou (Chinese: \u798f\u5dde; formerly Foochow) is the capital and one of the largest cities in Fujian province, People's Republic of China. Along with the many counties of Ningde, those of Fuzhou are considered to constitute the Mindong (lit. East of Fujian) linguistic and cultural area.Fuzhou's core counties lie on the north (left) bank of the estuary of Fujian's largest river, the Min River. All along its northern border lies Ningde, and Ningde's Gutian County lies upriver.", "vector": [0.00944509543478489, 0.09612657874822617, -0.013512429781258106, -0.010648109018802643, 0.0045900726690888405, -0.0046974848955869675, -0.0004128648724872619, -0.027382899075746536, -0.04923766106367111, -0.042993441224098206, -0.011507405899465084, 0.01715727709233761, -0.05562509223818779, 0.023129383102059364, 0.007121415343135595, 0.008012935519218445, -0.022341696545481682, 0.03892610967159271, -0.025592699646949768, -0.005023301113396883, -0.006716830190271139, 0.026595210656523705, 0.0036537982523441315, -0.013727253302931786, 0.0062298960983753204, 0.04127484932541847, -0.010841450653970242, -0.02318667061626911, -0.016340944916009903, 0.024203503504395485, 0.04943816363811493, -0.012087429873645306, 0.009974994696676731, -0.029130134731531143, -0.02211255021393299, 0.031650736927986145, 0.03929847106337547, -0.004264256451278925, 0.018847225233912468, 0.044769320636987686, 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The word patricide derives from the Latin word pater (father) and the Latin suffix -cida (cutter or killer). Patricide is a sub-form of parricide, which is defined as an act of killing a close relative.", "vector": [-0.02162994258105755, 0.009556903503835201, -0.03192991763353348, 0.04835101589560509, -0.04882187023758888, 0.04479016736149788, -0.008497477509081364, -0.047703590244054794, -0.007471159100532532, 0.03758018836379051, 0.0345490537583828, -0.03781561553478241, -0.03966961055994034, -0.041553035378456116, -0.022571654990315437, -0.0428478866815567, -0.010358829982578754, -0.0023524402640759945, 0.023380938917398453, -0.040081609040498734, -0.014699532650411129, -0.004568773787468672, -0.009630474261939526, -0.01789252460002899, 0.08952148258686066, 0.004469452425837517, -0.00014806211402174085, -0.010027759708464146, -0.0021390835754573345, -0.014066820032894611, -0.014515604823827744, -0.0006492661777883768, 0.021747658029198647, 0.034078195691108704, 0.014110962860286236, -0.04114103317260742, -0.03602047637104988, 0.0020912622567266226, 0.06274154782295227, 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It is the capital city of the Tadla-Azilal Region, with a population of 489,248 (2010 census).", "vector": [0.017672881484031677, 0.031421344727277756, 0.007017173338681459, -0.010213885456323624, 0.03908825293183327, 0.0003459856379777193, -0.06684507429599762, -0.025365782901644707, -0.026197446510195732, -0.06325852125883102, -0.01639939472079277, -0.01394338347017765, -0.046391312032938004, 0.03994590789079666, 0.021376390010118484, 0.017114106565713882, -0.02446914277970791, 0.014554137364029884, 0.02910827472805977, -0.016594314947724342, -0.012364519760012627, -0.0002984735183417797, 0.036489300429821014, 0.03552768751978874, -0.019518136978149414, -0.008946896530687809, -0.009622624143958092, -0.014943980611860752, -0.013774451799690723, -0.04368840157985687, -0.012455482967197895, 0.004246039781719446, 0.016763247549533844, -0.003437115577980876, -0.0062959641218185425, -0.0059808408841490746, -0.03521581366658211, -0.014749058522284031, -0.0070106759667396545, 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It is superior to the older high-carbon steel tools used extensively through the 1940s in that it can withstand higher temperatures without losing its temper (hardness). This property allows HSS to cut faster than high carbon steel, hence the name high-speed steel.", "vector": [0.025558795779943466, 0.039122700691223145, -0.023505879566073418, 0.015382200479507446, 0.037890952080488205, 0.013343948870897293, 0.0008614912512712181, -0.04448960721492767, 0.011298365890979767, -0.0006002944428473711, -0.00047519488725811243, 0.04290593042969704, 0.03111632913351059, 0.012852716259658337, -0.007456481456756592, 0.05619122460484505, 0.022068839520215988, 0.024224400520324707, 0.01000796165317297, -0.0478035993874073, 0.06475481390953064, -0.028696822002530098, -0.06311248242855072, -0.03284664452075958, -0.0020675789564847946, -0.02954731695353985, 0.004494417924433947, 0.0025038234889507294, -0.09150136262178421, -0.02145296521484852, -0.0018705357797443867, -0.007342838216573, -0.011364351958036423, -0.013167984783649445, 0.058390773832798004, 0.012647424824535847, -0.008446279913187027, 0.001985095674172044, -0.055311404168605804, 0.00019750144565477967, 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-0.025957128033041954, -0.0226972047239542, 0.01837780885398388, 0.034066181629896164, 0.010968278162181377, 0.028171157464385033, -0.0005068159662187099, 0.023783845826983452, 0.0011579514248296618, 0.00709032965824008, -0.014411570504307747, 0.0030629681423306465, -0.05406036972999573, 0.0013752795057371259, 0.009827305562794209, 0.03892889991402626, 0.01923353783786297, -0.00785776972770691], "index": 95}, {"title": "Clint Stennett", "text": "W. Clinton \"Clint\" Stennett (October 1, 1956 \u2013 October 14, 2010) was a Democratic politician and a minority leader of the Idaho Senate. Stennett represented District 25, which includes Blaine, Gooding, Camas and Lincoln Counties. Stennett served in the Idaho Senate from 1994 to 2010, but was unable to fulfill his duties after the 2008 session due to poor health. 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Launched into orbit on 23 April 1967 carrying cosmonaut Colonel Vladimir Komarov, Soyuz 1 was the first crewed flight of the Soyuz spacecraft. The mission plan was complex, involving a rendezvous with Soyuz 2 and an exchange of crew members before returning to Earth.", "vector": [0.027997292578220367, 0.01810913160443306, 0.0026427116245031357, -0.022966979071497917, -0.04242710769176483, -0.03782796487212181, 0.0009494718397036195, 0.03363124653697014, -0.013517173007130623, -0.013783060945570469, -0.03590207174420357, -0.039006493985652924, -0.021041085943579674, 0.0021702214144170284, 0.028299111872911453, 0.07927775382995605, -0.0028044001664966345, 0.01566583663225174, -0.02280888333916664, -0.04136355593800545, 0.05001569911837578, -0.0103983785957098, 0.023872435092926025, 0.0312166940420866, 0.04403680935502052, -0.04139230027794838, 0.021889053285121918, 0.035557135939598083, -0.029980674386024475, -0.02975071594119072, 0.017289908602833748, -0.03196405619382858, -0.016715016216039658, 0.03196405619382858, 0.06657262146472931, -0.04472668096423149, 0.019014587625861168, -0.006553781218826771, -0.029161451384425163, 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1974. 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It was founded in 2004 and is organized in 6 Faculties.", "vector": [0.01370352040976286, 0.08861248940229416, -0.023745546117424965, 0.009841619059443474, 0.026930395513772964, 0.02426552213728428, -0.06265704333782196, 0.0036425364669412374, 0.0031144365202635527, -0.0054516177624464035, -0.0017657499993219972, -0.012641903944313526, -0.01959657482802868, -0.009787455201148987, -0.0074475654400885105, 0.027970347553491592, -0.02119983360171318, 0.06798679381608963, -0.0010318263666704297, 0.03739490360021591, -0.021925631910562515, 0.019899895414710045, -0.011970268562436104, -0.028338663280010223, 0.03119852766394615, 0.024698834866285324, 0.01349769625812769, -0.03732990473508835, -0.008005456067621708, 0.028706979006528854, -0.01930408924818039, 0.011536955833435059, -0.01502512488514185, -0.023377230390906334, -0.0027258088812232018, 0.029291952028870583, -0.02024654485285282, -0.005524739157408476, -0.03654994070529938, -0.0066621857695281506, 0.04766441881656647, 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Wiss is currently working as a manager of the Finland national under-18 football team.", "vector": [0.006705993786454201, 0.04774228855967522, -0.008756163530051708, -0.04268447309732437, -0.011321617290377617, 0.04590042307972908, 0.04107649624347687, 0.009333573281764984, -0.03189640864729881, 0.019456516951322556, -0.03610638529062271, -0.002424755599349737, -0.027174806222319603, 0.004699677228927612, -0.0427137054502964, 0.014354846440255642, 0.0020465156994760036, 0.0397024042904377, -0.04142732545733452, -0.028402715921401978, 0.04861936718225479, 0.022935593500733376, -0.015538902021944523, -0.013046537525951862, 0.029469827190041542, -0.028037264943122864, 0.014822620898485184, 0.020640572533011436, -0.028899725526571274, 0.02362263947725296, 0.03692499175667763, 0.023798054084181786, 0.016606014221906662, -0.06198019161820412, 0.013718964532017708, 0.038416024297475815, 0.024426627904176712, 0.01893027126789093, -0.03534625098109245, 0.004436553921550512, 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is_live._cache = True if not is_emulator else False - credential = masterKey if is_emulator else get_credential() + credential = masterKey if is_emulator else get_credential() credential_async = masterKey if is_emulator else get_credential(is_async=True) global_host = os.getenv('GLOBAL_ACCOUNT_HOST', host) @@ -185,6 +185,29 @@ def get_vector_embedding_policy(distance_function, data_type, dimensions): } +def get_full_text_indexing_policy(path): + return { + "indexingMode": "consistent", + "includedPaths": [{"path": "/*"}], + 'excludedPaths': [{'path': '/"_etag"/?'}], + "fullTextIndexes": [ + {"path": path} + ] + } + + +def get_full_text_policy(path): + return { + "defaultLanguage": "en-US", + "fullTextPaths": [ + { + "path": path, + "language": "en-US" + } + ] + } + + class FakeResponse: def __init__(self, headers): self.headers = headers @@ -243,4 +266,3 @@ def send(self, request): def mock_send(self): raise ServiceRequestError("mock-service") - diff --git a/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search.py b/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search.py new file mode 100644 index 000000000000..ea54ec4cd06c --- /dev/null +++ b/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search.py @@ -0,0 +1,191 @@ +# The MIT License (MIT) +# Copyright (c) Microsoft Corporation. All rights reserved. + +import json +import time +import unittest +import uuid + +import pytest + +import azure.cosmos.cosmos_client as cosmos_client +import azure.cosmos.exceptions as exceptions +import test_config +import hybrid_search_data +from azure.cosmos import http_constants, DatabaseProxy +from azure.cosmos.partition_key import PartitionKey + + +class TestFullTextHybridSearchQuery(unittest.TestCase): + """Test to check full text search and hybrid search queries behavior.""" + + created_db: DatabaseProxy = None + client: cosmos_client.CosmosClient = None + config = test_config.TestConfig + host = config.host + masterKey = config.masterKey + connectionPolicy = config.connectionPolicy + TEST_DATABASE_ID = config.TEST_DATABASE_ID + TEST_CONTAINER_ID = "Full Text Container " + str(uuid.uuid4()) + + @classmethod + def setUpClass(cls): + if (cls.masterKey == '[YOUR_KEY_HERE]' or + cls.host == '[YOUR_ENDPOINT_HERE]'): + raise Exception( + "You must specify your Azure Cosmos account values for " + "'masterKey' and 'host' at the top of this class to run the " + "tests.") + + cls.client = cosmos_client.CosmosClient(cls.host, cls.masterKey) + cls.created_db = cls.client.get_database_client(cls.TEST_DATABASE_ID) + + def setUp(self): + self.test_db = self.client.create_database(str(uuid.uuid4())) + self.test_container = self.test_db.create_container( + id="FTS" + self.TEST_CONTAINER_ID, + partition_key=PartitionKey(path="/id"), + offer_throughput=test_config.TestConfig.THROUGHPUT_FOR_1_PARTITION, + indexing_policy=test_config.get_full_text_indexing_policy(path="/text"), + full_text_policy=test_config.get_full_text_policy(path="/text")) + data = hybrid_search_data.get_full_text_items() + for index, item in enumerate(data.get("items")): + item['id'] = str(index) + self.test_container.create_item(item) + # Need to give the container time to index all the recently added items - 10 minutes seems to work + time.sleep(10 * 60) + + def tearDown(self): + try: + self.test_db.delete_container(self.test_container.id) + self.client.delete_database(self.test_db.id) + except exceptions.CosmosHttpResponseError: + pass + + def test_wrong_queries(self): + try: + query = "SELECT c.index, RRF(VectorDistance(c.vector, [1,2,3]), FullTextScore(c.text, “test”) FROM c" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + list(results) + pytest.fail("Attempting to project RRF in a query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + try: + query = "SELECT TOP 10 c.index FROM c WHERE FullTextContains(c.title, 'John')" \ + " ORDER BY RANK FullTextScore(c.title, ['John']) DESC" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + list(results) + pytest.fail("Attempting to set an ordering direction in a full text score query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + try: + query = "SELECT TOP 10 c.index FROM c WHERE FullTextContains(c.title, 'John')" \ + " ORDER BY RANK RRF(FullTextScore(c.title, ['John']), VectorDistance(c.vector, [1,2,3])) DESC" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + list(results) + pytest.fail("Attempting to set an ordering direction in a hybrid search query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + def test_hybrid_search_queries(self): + query = "SELECT TOP 10 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John') OR " \ + "FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John'])" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 3 + for res in result_list: + assert res['index'] in [2, 85, 57] + + query = "SELECT TOP 10 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John'])" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 3 + for res in result_list: + assert res['index'] in [2, 85, 57] + + query = "SELECT c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John']) OFFSET 1 LIMIT 5" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 2 + for res in result_list: + assert res['index'] in [85, 57] + + query = "SELECT TOP 20 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John') OR " \ + "FullTextContains(c.text, 'John') OR FullTextContains(c.text, 'United States') " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 15 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25, 22, 2, 66, 57, 85] + + query = "SELECT TOP 10 c.index, c.title FROM c WHERE " \ + "FullTextContains(c.title, 'John') OR FullTextContains(c.text, 'John') OR " \ + "FullTextContains(c.text, 'United States') ORDER BY RANK RRF(FullTextScore(c.title, ['John'])," \ + " FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25] + + query = "SELECT c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') OR FullTextContains(c.text, 'United States') ORDER BY " \ + "RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) OFFSET 5 LIMIT 10" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [24, 77, 76, 80, 25, 22, 2, 66, 57, 85] + + query = "SELECT TOP 10 c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25] + + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) " \ + "OFFSET 0 LIMIT 13" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 13 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25, 22, 2, 66] + + item_vector = self.test_container.read_item('50', '50')['vector'] + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.text, ['United States']), VectorDistance(c.vector, {})) " \ + "OFFSET 0 LIMIT 10".format(item_vector) + results = self.test_container.query_items(query, enable_cross_partition_query=True) + result_list = list(results) + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [51, 54, 28, 70, 24, 61, 56, 26, 58, 77] + + def test_hybrid_search_query_pagination(self): + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) " \ + "OFFSET 0 LIMIT 13" + query_iterable = self.test_container.query_items(query, enable_cross_partition_query=True, max_item_count=5) + all_fetched_res = [] + count = 0 + item_pages = query_iterable.by_page() + for items in item_pages: + count += 1 + all_fetched_res.extend(list(items)) + assert count == 3 + assert len(all_fetched_res) == 13 + + +if __name__ == "__main__": + unittest.main() diff --git a/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search_async.py b/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search_async.py new file mode 100644 index 000000000000..537f89050e42 --- /dev/null +++ b/sdk/cosmos/azure-cosmos/test/test_query_hybrid_search_async.py @@ -0,0 +1,193 @@ +# The MIT License (MIT) +# Copyright (c) Microsoft Corporation. All rights reserved. + +import json +import time +import unittest +import uuid + +import pytest + +from azure.cosmos.aio import CosmosClient +import azure.cosmos.exceptions as exceptions +import test_config +import hybrid_search_data +from azure.cosmos import http_constants, DatabaseProxy +from azure.cosmos.partition_key import PartitionKey + + +class TestFullTextHybridSearchQueryAsync(unittest.IsolatedAsyncioTestCase): + """Test to check full text search and hybrid search queries behavior.""" + + created_db: DatabaseProxy = None + client: CosmosClient = None + config = test_config.TestConfig + host = config.host + masterKey = config.masterKey + connectionPolicy = config.connectionPolicy + TEST_DATABASE_ID = config.TEST_DATABASE_ID + TEST_CONTAINER_ID = "Full Text Container " + str(uuid.uuid4()) + + @classmethod + def setUpClass(cls): + if (cls.masterKey == '[YOUR_KEY_HERE]' or + cls.host == '[YOUR_ENDPOINT_HERE]'): + raise Exception( + "You must specify your Azure Cosmos account values for " + "'masterKey' and 'host' at the top of this class to run the " + "tests.") + + cls.client = CosmosClient(cls.host, cls.masterKey) + cls.created_db = cls.client.get_database_client(cls.TEST_DATABASE_ID) + + async def asyncSetUp(self): + self.test_db = await self.client.create_database(str(uuid.uuid4())) + self.test_container = await self.test_db.create_container( + id="FTS" + self.TEST_CONTAINER_ID, + partition_key=PartitionKey(path="/id"), + offer_throughput=test_config.TestConfig.THROUGHPUT_FOR_1_PARTITION, + indexing_policy=test_config.get_full_text_indexing_policy(path="/text"), + full_text_policy=test_config.get_full_text_policy(path="/text")) + data = hybrid_search_data.get_full_text_items() + for index, item in enumerate(data.get("items")): + item['id'] = str(index) + await self.test_container.create_item(item) + # Need to give the container time to index all the recently added items - 10 minutes seems to work + time.sleep(10 * 60) + + async def tearDown(self): + try: + await self.test_db.delete_container(self.test_container.id) + await self.client.delete_database(self.test_db.id) + except exceptions.CosmosHttpResponseError: + pass + await self.client.close() + + async def test_wrong_queries_async(self): + try: + query = "SELECT c.index, RRF(VectorDistance(c.vector, [1,2,3]), FullTextScore(c.text, “test”) FROM c" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + [item async for item in results] + pytest.fail("Attempting to project RRF in a query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + try: + query = "SELECT TOP 10 c.index FROM c WHERE FullTextContains(c.title, 'John')" \ + " ORDER BY RANK FullTextScore(c.title, ['John']) DESC" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + [item async for item in results] + pytest.fail("Attempting to set an ordering direction in a full text score query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + try: + query = "SELECT TOP 10 c.index FROM c WHERE FullTextContains(c.title, 'John')" \ + " ORDER BY RANK RRF(FullTextScore(c.title, ['John']), VectorDistance(c.vector, [1,2,3])) DESC" + results = self.test_container.query_items(query, enable_cross_partition_query=True) + [item async for item in results] + pytest.fail("Attempting to set an ordering direction in a hybrid search query should fail.") + except exceptions.CosmosHttpResponseError as e: + assert e.status_code == http_constants.StatusCodes.BAD_REQUEST + assert "One of the inputs is invalid" in e.message + + async def test_hybrid_search_queries_async(self): + query = "SELECT TOP 10 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John') OR " \ + "FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John'])" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 3 + for res in result_list: + assert res['index'] in [2, 85, 57] + + query = "SELECT TOP 10 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John'])" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 3 + for res in result_list: + assert res['index'] in [2, 85, 57] + + query = "SELECT c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') ORDER BY RANK FullTextScore(c.title, ['John']) OFFSET 1 LIMIT 5" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 2 + for res in result_list: + assert res['index'] in [85, 57] + + query = "SELECT TOP 20 c.index, c.title FROM c WHERE FullTextContains(c.title, 'John') OR " \ + "FullTextContains(c.text, 'John') OR FullTextContains(c.text, 'United States') " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 15 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25, 22, 2, 66, 57, 85] + + query = "SELECT TOP 10 c.index, c.title FROM c WHERE " \ + "FullTextContains(c.title, 'John') OR FullTextContains(c.text, 'John') OR " \ + "FullTextContains(c.text, 'United States') ORDER BY RANK RRF(FullTextScore(c.title, ['John'])," \ + " FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25] + + query = "SELECT c.index, c.title FROM c WHERE FullTextContains(c.title, 'John')" \ + " OR FullTextContains(c.text, 'John') OR FullTextContains(c.text, 'United States') ORDER BY " \ + "RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) OFFSET 5 LIMIT 10" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [24, 77, 76, 80, 25, 22, 2, 66, 57, 85] + + query = "SELECT TOP 10 c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States']))" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25] + + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) " \ + "OFFSET 0 LIMIT 13" + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 13 + for res in result_list: + assert res['index'] in [61, 51, 49, 54, 75, 24, 77, 76, 80, 25, 22, 2, 66] + + read_item = await self.test_container.read_item('50', '50') + item_vector = read_item['vector'] + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.text, ['United States']), VectorDistance(c.vector, {})) " \ + "OFFSET 0 LIMIT 10".format(item_vector) + results = self.test_container.query_items(query) + result_list = [item async for item in results] + assert len(result_list) == 10 + for res in result_list: + assert res['index'] in [51, 54, 28, 70, 24, 61, 56, 26, 58, 77] + + async def test_hybrid_search_query_pagination_async(self): + query = "SELECT c.index, c.title FROM c " \ + "ORDER BY RANK RRF(FullTextScore(c.title, ['John']), FullTextScore(c.text, ['United States'])) " \ + "OFFSET 0 LIMIT 13" + query_iterable = self.test_container.query_items(query, max_item_count=5) + all_fetched_res = [] + count = 0 + item_pages = query_iterable.by_page() + async for items in item_pages: + count += 1 + all_fetched_res.extend([item async for item in items]) + assert count == 3 + assert len(all_fetched_res) == 13 + + +if __name__ == "__main__": + unittest.main()