neo4j 向量索引

neo4j向量索引 neo4j向量索引,cypher原生命令创建 阅读详情
AI摘要

本文介绍如何在Neo4j中使用向量索引进行高效的数据查询。通过具体示例展示了如何创建向量索引及查询相似节点的方法。

以下资源提供了在 Neo4j 中使用 LLM 和向量索引的实践教程:

Neo4j 向量索引由Apache Lucene索引和搜索库提供支持。 [ 1 ]

示例图

本页上的示例使用Neo4j 电影推荐数据集,重点关注节点的plot和属性。属性由和属性组合而成的 1536 维向量嵌入组成。embeddingMovieembeddingplottitle

该图包含 28863 个节点和 332522 个关系。

要重新创建图表,请下载此转储文件并将其导入空的 Neo4j 数据库(运行 5.13 或更高版本)。可以为Aura和本地实例导入转储文件。

用于加载数据集的转储文件包含使用模型由OpenAItext-embedding-ada-002生成的嵌入。

Neo4j 中的向量和嵌入

向量索引允许您从大型数据集中查询向量嵌入。嵌入是数据对象(例如文本、图像或文档)的数值表示。文本中的每个单词或标记通常表示为高维向量,其中每个维度代表单词含义的某个方面。

特定数据对象的嵌入可以由专有(例如Vertex AI或OpenAI)和开源(例如sentence-transformers)嵌入生成器创建,它们可以生成维度为 256、768、1536 和 3072 的向量嵌入。在 Neo4j 中,向量嵌入存储为LIST<INTEGER | FLOAT>节点或关系上的属性。

有关如何生成嵌入并将其存储为属性的信息,请参阅:

例如电影《教父》有以下内容plot:"The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant son." 这是它的 1536 维embedding属性,其中每个元素LIST代表情节含义的某个特定方面:

[0.005967312026768923,-0.03817005082964897,0.0014667075593024492,-0.03868866711854935,-0.006505374796688557,0.02090017683 8040352, -0.0027551413513720036, -0.0024731445591896772, -0.03734026849269867, -0.02228747308254242, 0.028783122077584267, 0.017905177548527718、0.011396560817956924、0.014235977083444595、0.023143187165260315、-0.014184115454554558、0.0298462826 75862312, -0.011928141117095947, 0.018838683143258095, -0.0019172541797161102, 0.0033483069855719805, 0.009497134014964104, -0.03516208380460739、0.0021441481076180935、0.002657901030033827、0.0030760341323912144、0.004255882930010557、-0.020809419 453144073, 0.02358401007950306, -0.013808120042085648, 0.01064456906169653, -0.006975369527935982, 0.007318951655179262, -0.013872946612536907, 0.005905726458877325, -0.010689947754144669, 0.0020225979387760162, -0.016245609149336815, -0.000388150 77277831733, -0.007163367234170437, 0.027668101713061333, 0.007215228863060474, -0.009380445815622807, -0.02956104464828968, -0.000863007502630353、0.012142069637775421、0.0012957267463207245、-0.027953339740633965、-0.016414159908890724、0.008453421 294689178, -0.0010777463903650641, 0.03311355784535408, -0.013639570213854313, -0.052457891404628754, 0.0010242642601951957, 0.0034390646032989025、-0.01049546804279089、0.006456754636019468、0.003970644902437925、-0.011629937216639519、0.0052801473 06621075, -0.023402493447065353, -0.014689764939248562, -0.007623638026416302, -0.002453696448355913, 0.02290981076657772, 0.0017989451298490167, 0.0013427261728793383, -0.001776255783624947, -0.002414800226688385, 0.04833490028977394, 0.031142819 672822952, -0.0033013075590133667, 0.017879245802760124, 0.0070077828131616116, -0.016154851764440536, -0.005772831384092569, 0.019875913858413696、-0.018008900806307793、0.012764407321810722、0.0055232481099665165、-0.027901478111743927、-0.003490925 9993582964, 0.0307279285043478, 0.006472961511462927, 0.008861830458045006, -0.01802186481654644, 0.018281172960996628, -0.014223011210560799、-0.00018313586770091206、0.0026352116838097572、0.0006754148053005338、0.014975002966821194、0.024361 930787563324、-0.017166150733828545、0.0028880364261567593、0.011824417859315872、0.01710132323205471、 -0.0005003822734579444, -0.018890544772148132, -0.002192768268287182, -0.0018264965619891882, 0.011033530347049236, -0.00909520 7788050175, -0.022689398378133774, -0.004281813744455576, 0.007092057727277279, -0.015247276052832603, 0.024115590378642082, 0.002996621420606971, -0.02834230102598667, 0.030546413734555244, 0.02350621670484543, -0.020511215552687645, 0.010190781205 892563, -0.016582708805799484, 0.028238577768206596, -0.011967036873102188, 0.011623455211520195, -0.02797926962375641, 0.0026254875119775534、0.018307102844119072、0.0038701631128787994、-0.03850715234875679、0.006246067117899656、-0.000631251 4888122678, 0.010352848097682, -0.02358401007950306, -0.026708664372563362, -0.002863726345822215, 0.035862214863300323, 0.009860164485871792,-0.01726987399160862,0。004275330808013678, -0.02663087099790573, 0.009140586480498314, -0.013872946612536907, 0.019136887043714523, -0.0208353511989 11667、-0.0250879917293787、0.03044269047677517、0.026280807331204414、-0.013406192883849144、0.006683648563921452、 -0.01216800045222044、0.007824601605534554、0.031505849212408066、0.023726629093289375、0.0294832531362772、-0.0136784659698 60554, 0.033891480416059494, 0.009211895987391472, 0.017088359221816063, -0.02183368429541588, 0.01847565360367298, 0.004644844215363264, -0.009834233671426773, -0.011344699189066887, -0.0006725785788148642, 0.00012691882147919387, 0.0153380 33437728882, 0.025736261159181595, -0.003967403434216976, -0.007312469184398651, -0.01312743779271841, 0.02350621670484543, -0.0006843284936621785, -0.011785522103309631, 0.006570201832801104, -0.004187814891338348, -0.0070013003423810005, 0.01651788 31666708, -0.004537879955023527, 0.022715330123901367, -0.0025120405480265617, 0.025580676272511482, 0.005053253378719091, -0.0020063910633325577、-0.039285074919462204、-0.001816772622987628、0.0007224142318591475、0.0161029901355505、0.0408668480 8135033, 0.03536953032016754, 0.009626788087189198, -0.023571044206619263, -0.009607339277863503, 0.011085391975939274, 0.020835351198911667, -0.0009027139167301357, -0.007584741804748774, 0.016958704218268394, 0.011130770668387413, -0.016829051 077365875, -0.6712950468063354, -0.006511857267469168, -0.024854615330696106, -0.02663087099790573, -0.00008933950448408723, 0.0061779990792274475、0.004605947993695736、0.013231161050498486、-0.020187081769108772、0.00798666849732399、-0.0018475652 90518105, 0.04086684808135033, 0.007519915234297514, 0.0040808506309986115, -0.034021131694316864, -0.01997963711619377, -0.004972219467163086, -0.023220978677272797, 0.012129104696214199, 0.0018329792656004429, -0.011649386025965214, 0.028446022 421121597, -0.0010356089333072305, -0.006223377771675587, 0.021211346611380577, 0.004006299655884504, 0.021937407553195953, -0.02927580662071705, -0.01129283756017685, -0.009296170435845852, -0.01864420250058174, 0.02717541716992855, -0.00035553477937 35564, 0.0021700789220631123, 0.048360832035541534, -0.002277043182402849, -0.009049829095602036, 0.033969271928071976, 0.004557327833026648、0.018916476517915726、-0.000779542897362262、-0.00638544512912631、0.022183749824762344、-0.01275792438 5368824, -0.027149485424160957, -0.012278205715119839, 0.0238303504884243, -0.02963883802294731, 0.005218561738729477, -0.004434156697243452、0.013665501028299332、-0.0024520757142454386、0.002124700229614973、-0.007273572962731123、-0.003565476 9744724035, -0.0028621056117117405, 0.020640870556235313, 0.01091684214770794, -0.0006867594784125686, -0.011694764718413353, 0.011215046048164368、0.016504917293787003、0.00827838946133852、-0.00444712​​21044659615、0.010676982812583447、0.0277718249 70841408, -0.0133802630007267, 0.029820352792739868, 0.008349698968231678, -0.014573076739907265, -0.009017415344715118, 0.011655868031084538,-0.0061066895723342896,-0.013082059100270271、0.004353123251348734、0.00672254478558898、0.01773662678897381、0.012433790601789951、0.023843316361 308098, 0.015221345238387585, -0.0046221548691391945, -0.00026214358513243496, -0.016582708805799484, 0.016504917293787003, 0.028005201369524002、0.005516765173524618、-0.04309689253568649、0.013743292540311813、-0.0064308238215744495、-0.0071763326 41392946, 0.01911095716059208, 0.00446332897990942, -0.012971853837370872, -0.016919808462262154, 0.010048162192106247, 0.0032769974786788225、-0.021548446267843246、0.001816772622987628、0.01856641098856926、-0.04804966226220131、0.00728653836 9953632, -0.007299503777176142, -0.014080392196774483, 0.008952588774263859, 0.023908143863081932, 0.012932957150042057, -0.008433973416686058、0.012783855199813843、0.0430709607899189、-0.01015836838632822、0.03534360229969025、-0.00758474180474 8774, -0.016453055664896965, -0.005720969755202532, -0.014871280640363693, -0.026540113613009453, 0.005228285677731037, 0.0004019264888484031、0.005931657273322344、-0.02533433400094509、-0.018825719133019447、0.0023353875149041414、0.001405932 3584660888, -0.02020004764199257, 0.022481953725218773, 0.034980569034814835, -0.02709762565791607, -0.022974636405706406, -0.025023166090250015、0.00641785841435194、-0.00019822835747618228、-0.004845807328820229、0.0003723492263816297、-0.01013243 757188​​3202, 0.01498796883970499, 0.001948046963661909, -0.0020161152351647615, -0.008842382580041885, 0.0223652645945549, -0.013574742712080479、-0.002369421534240246、0.003275376744568348、0.005879795644432306、0.005789037793874741、0.0063595143 14681292, -0.03549918532371521, 0.003118171589449048, -0.026993902400135994, -0.01614188589155674, 0.011578075587749481, 0.0008524731383658946、-0.013367297127842903、0.004194297362118959、0.019331367686390877、0.006152068264782429、-0.015208380 296826363, -0.0018005658639594913, -0.015714028850197792, -0.01681608520448208, -0.028990568593144417, 0.010676982812583447, 0.024595309048891068, -0.045560311526060104, -0.0009262136882171035, 0.014845349825918674, -0.020887212827801704, 0.015739960 595965385, 0.011727177537977695, 0.0012560202740132809, -0.023052429780364037, 0.0014245701022446156, -0.013062611222267151, -0.011299320496618748、0.022274507209658623、0.011338216252624989、-0.007908876053988934、0.010339883156120777、-0.0061326203 86779308, 0.01247916929423809, -0.007947771809995174, -0.0025347298942506313, -0.011416008695960045, 0.011027047410607338, 0.004521673079580069、0.04880165681242943、0.0012543996563181281、0.02115948498249054、0.0165178831666708、-0.0253732297569 51332, 0.026125222444534302, -0.0031262750271707773, 0.007669016718864441, 0.003821542952209711, -0.021561412140727043, 0.008187631145119667、0.02358401007950306、0.02249491773545742、0.015247276052832603、-0.004560569301247597、0.030753860250 115395, 0.031090958043932915, -0.021457688882946968, 0.027694031596183777, -0.004823117982596159, 0.0049171168357133865, -0.018346000462770462,-0。0030355174094438553, -0.011176149360835552, 0.024102624505758286, 0.006923507899045944, 0.010009266436100006, -0.00510187353 938818, 0.0007916979375295341, -0.004722636193037033, 0.019914809614419937, 0.026190048083662987, -0.013289504684507847, 0.006346548907458782、-0.015415825881063938、-0.026734594255685806、0.003623821074143052、0.005325525999069214、-0.0039220247 41768837, -0.00640813447535038, -0.014624938368797302, -0.0065021333284676075, 0.007435640320181847, -0.002808623481541872, 0.010138919577002525、-0.033813685178756714、-0.0032008260022848845、0.01614188589155674、-0.018994268029928207、0.0081357704 47552204, -0.008596041239798069, -0.015662167221307755, 0.004310985561460257, -0.014663834124803543, 0.014962038025259972, -0.03479905426502228、0.013114472851157188​​、0.01341915875673294、0.05092797800898552、-0.011908693239092827、0.0053320089355 11112, -0.013367297127842903, 0.02501020021736622, -0.00029678543796762824, -0.02454344742000103, 0.003152205841615796, -0.015454721637070179、0.010028714314103127、-0.02102983184158802、-0.0032624113373458385、0.03583628311753273、-0.01502686459 5711231, 0.00672254478558898, 0.000010907877367571928, 0.019875913858413696, 0.020161151885986328, 0.014054462313652039, -0.005675591062754393, -0.009224860928952694, 0.014793488197028637, 0.03687351569533348, -0.005442214198410511, 0.00563345337 2865915, -0.0030436208471655846, -0.012615305371582508, -0.009075759910047054, 0.017192082479596138, -0.002220319816842675, 0.005798762198537588, -0.0007568534929305315, 0.010378778912127018, 0.005908967927098274, -0.0158825796097517, 0.00888127926 73707, 0.007766257040202618, -0.0030209312681108713, -0.013561777770519257, -0.035395462065935135, 0.022391194477677345, -0.0027049004565924406, 0.004748567007482052, -0.020433424040675163, -0.00028706141165457666, -0.005092149134725332, -0.0183719 30345892906, 0.006009449250996113, -0.00645027169957757, 0.015286171808838844, -0.012343033216893673, -0.008628454059362411, -0.010605673305690289、0.009192448109388351、0.007500466890633106、-0.013535846956074238、0.003831267124041915、-0.0295610446 4828968, 0.0009724028059281409, 0.0034585127141326666, -0.00004074468961334787, -0.025139853358268738, 0.012278205715119839, 0.023519182577729225、-0.012913509272038937、-0.006301170215010643、0.0037178201600909233、0.004716153722256422、-0.017905177 548527718, 0.009769407100975513, -0.019746258854866028, -0.011675315909087658, 0.007409709505736828, -0.022676432505249977, -0.013406192883849144、0.003922024741768837、0.03925914317369461、-0.011325251311063766、-0.014611972495913506、-0.02240416035 0561142, -0.03311355784535408, 0.0024634203873574734, 0.1057974249124527, 0.014145219698548317, 0.025956671684980392, 0.006878129206597805, -0.019914809614419937, -0.019162818789482117, -0.009231343865394592, -0.04423784464597702, 0.01201889850 1992226, -0.00921837892383337, 0.02408965863287449, -0.026501217857003212, 0.020225977525115013, 0.005014357157051563, 0.02053714729845524,0。014521215111017227, -0.002670866437256336, -0.020433424040675163, -0.0015372068155556917, -0.031168751418590546, 0.00512132141 73913, 0.006865163799375296, 0.010048162192106247, 0.003795612370595336, -0.009749959222972393, -0.024063728749752045, 0.026449356228113174, 0.00967864878475666, -0.009049829095602036, -0.012284688651561737, -0.02475089207291603, 0.003484443295 7470417, -0.00928320549428463, 0.011772556230425835, -0.01811262220144272, -0.01918874867260456, 0.009043346159160137, 0.023843316361308098、0.02580108679831028、0.005980277433991432、0.029327668249607086、-0.008103356696665287、0.00808390881 8662167, -0.005490834359079599, 0.021146519109606743, -0.0023499734234064817, -0.03298390284180641, 0.005283388774842024, -0.00043352958164177835, -0.024271173402667046, 0.03181701898574829, -0.000028944177756784484, -0.004479535389691591, -0.002066 355897113681, 0.017995934933423996, -0.012783855199813843, 0.013859981670975685, -0.006615580525249243, -0.0008403180981986225、0.025489918887615204、-0.01789221167564392、-0.03189481049776077、0.00028949242550879717、-0.032517150 04444122, 0.03588814660906792, -0.03500650078058243, -0.007869980297982693, -0.024361930787563324, 0.00451519014313817, -0.018177449703216553、0.020627904683351517、0.003249445930123329、0.010962220840156078、-0.005299595184624195、0.0480237342 41724014, -0.0033094107639044523, 0.012971853837370872, -0.02290981076657772, 0.017918141558766365, -0.016245609149336815, -0.013179299421608448, -0.020589008927345276, 0.0037469922099262476, -0.029327668249607086, -0.007383778691291809, 0.013017232 529819012, 0.006327101029455662, -0.02689017914235592, -0.004385536536574364, 0.005789037793874741, -0.005597798619419336, -0.004152160137891769, 0.012719028629362583, -0.008220044896006584, -0.01702353172004223, -0.011506766080856323, 0.00429802061 98990345, 0.0018702547531574965, -0.0032964455895125866, 0.007267090491950512, -0.009581409394741058, -0.0058182100765407085, -0.005429248791188002, -0.008829417638480663, -0.0030403793789446354, -0.01194110605865717, -0.002591453492641449, 0.0057566245 08649111, -0.01618078351020813, -0.009821268729865551, -0.00021210535487625748, -0.01768476516008377, -0.0005562954465858638, -0.017451388761401176、-0.015545479021966457、0.02332470193505287、0.015960371121764183、0.02208002656698227、0.013691431842 74435, -0.014495284296572208, -0.007701430004090071, -0.0005567006301134825, 0.027590308338403702, 0.05188741534948349, -0.023609939962625504、-0.017957039177417755、0.015999266877770424、-0.020900176838040352、0.003038758644834161、0.0210427958 51826668, -0.009814785793423653, 0.0014083633432164788, 0.010897394269704819, -0.0167253278195858, -0.020135220140218735, -0.005273664370179176, -0.009788854978978634, -0.002986897248774767, -0.008764590136706829, -0.006729027256369591, -0.0184497218 57905388, -0.009166517294943333, -0.002651418326422572, 0.008245975710451603, 0.0034358231350779533, -0.028757192194461823, 0.01511762198060751,-0.008544179610908031,0.005344973877072334, 0.013924808241426945, -0.003299686824902892, -0.04143732413649559, -0.0008403180981986225, 0.0109492558 98594856, -0.013600673526525497, -0.03448788449168205, -0.007863497361540794, -0.01809965819120407, -0.00444063963368535, 0.004920358303934336、0.0330357663333416、-0.008816451765596867、0.006683648563921452、0.00823301076889038、-0.0159474052488 80386, 0.02608632668852806, 0.0037243026308715343, -0.007623638026416302, -0.028031131252646446, 0.027123555541038513, 0.01843675784766674、0.016712361946702003、0.040374163538217545、-0.0021538722794502974、0.01885164901614189、-0.01174014341 0861492, 0.017490284517407417, -0.0004517621418926865, -0.00034439266892150044, -0.026190048083662987, -0.021729961037635803, 0.0020209772046655416, -0.014521215111017227, -0.01467679999768734, 0.002505557844415307, -0.01061863824725151, 0.01562327146 5301514, -0.010087057948112488, -0.0031748951878398657, 0.01631043665111065, 0.016375262290239334, -0.013257091864943504, 0.010741809383034706、-0.012932957150042057、-0.002484489232301712、0.0027324517723172903、0.00897203665226698、-0.0047939456 99930191, 0.0043466403149068356, -0.0020047705620527267, 0.0021538722794502974, 0.021263208240270615, -0.0269679706543684, -0.024115590378642082、-0.0025833500549197197、0.030598275363445282、0.002772968728095293、0.01584368385374546、0.0069818519 98716593, -0.0037113374564796686, -0.01273199450224638, -0.026280807331204414, -0.02182071842253208, -0.049527715891599655, 0.02195037342607975, -0.008628454059362411, -0.004353123251348734, 0.01064456906169653, -0.009698097594082355, -0.040944639593 36281, 0.0238303504884243, 0.0034649954177439213, 0.032802388072013855, 0.0002048123424174264, 0.022507883608341217, 0.03770329803228378、-0.010346366092562675、0.0028588641434907913、0.026410460472106934、0.019085025414824486、0.0088488655 16483784, 0.015830717980861664, -0.004469811450690031, 0.013808120042085648, -0.012031864374876022, -0.02099093608558178, -0.006054827943444252、-0.045638103038072586、-0.024050762876868248、0.014417491853237152、0.01218744833022356、0.00324134272 52322435, -0.013302470557391644, -0.0003156257444061339, 0.006942956242710352, 0.00542600778862834, -0.0034358231350779533, 0.022067060694098473, -0.013847015798091888, -0.026942040771245956, -0.0334506556391716, -0.01835896447300911, -0.0021036313846 707344, -0.001962633104994893, 0.012615305371582508, -0.0186053067445755, 0.01572699472308159, -0.02542509138584137, 0.019422125071287155, -0.013950739055871964, -0.002110114088281989, 0.02052418142557144, -0.0014197081327438354, 0.0010485743 405297399, -0.004372571129351854, 0.0069299908354878426, -0.005105114541947842, -0.003756716148927808, -0.015960371121764183, 0.025554746389389038、0.003516856813803315、0.005951105151325464、0.009736993350088596、0.043459922075271606、-0.0089525887 74263859, 0.021315069869160652, -0.011318768374621868, -0.016375262290239334, -0.004560569301247597, -0.026656802743673325, 0.004842565860599279,0.0004894427256658673, -0.023635871708393097, 0.007448605261743069, -0.008965553715825081, 0.0026092808693647385, -0.0199926011 2643242, -0.007811635732650757, 0.012142069637775421, -0.01375625841319561, -0.02102983184158802, -0.006806819699704647, 0.015869613736867905, -0.0074032265692949295, -0.001892944099381566, -0.0037016132846474648, -0.005322284530848265, 0.03293204 307556152, -0.014430457726120949, 0.0418262854218483, -0.012641236186027527, 0.018216345459222794, -0.028290439397096634, 0.02576219104230404、0.008433973416686058、0.013963703997433186、0.030598275363445282、-0.01225227490067482、0.012051312252 879143, 0.0014553628861904144, -0.008822934702038765, 0.01100111659616232, 0.009860164485871792, -0.004388778004795313, -0.01685498282313347、0.01091035921126604、-0.00033223762875422835、-0.007850532419979572、-0.0006320617976598442、0.002114976 057782769, -0.007532880175858736, 0.01710132323205471, 0.015610306523740292, -0.009036863222718239, 0.008200597018003464, 0.012174483388662338、0.00447305291891098、0.0186053067445755、-0.019253576174378395、0.010638087056577206、-0.0208612810820 3411, 0.022404160350561142, 0.010437123477458954, 0.0006920266896486282, -0.02128913812339306, -0.009296170435845852, -0.004106780979782343、0.044808320701122284、-0.013782189227640629、-0.003750233445316553、-0.01181145291775465、0.02764216996 729374, 0.011960554867982864, -0.005043528974056244, 0.006155309733003378, -0.015584375709295273, 0.012433790601789951, -0.021600307896733284、-0.04314875230193138、-0.01214855257421732、-0.024776823818683624、0.039077628403902054、0.016271540895 104408, 0.000348039175150916, -0.01511762198060751, 0.0014926382573321462, -0.04068533331155777, -0.0020290804095566273, -0.006904060021042824、0.02099093608558178、0.017049461603164673、-0.006981851998716593、0.007364330347627401、0.00741619197 6517439, 0.00766253424808383, 0.02153548039495945, -0.002995000686496496, 0.02157437615096569, -0.011312286369502544, -0.009685131721198559, 0.00414891866967082, -0.009672166779637337, -0.01308854203671217, -0.003380720503628254, -0.003168412484 228611, 0.013769223354756832, -0.012615305371582508, 0.007973702624440193, 0.001315985107794404, -0.006139102857559919, -0.028212646022439003、0.0004906582762487233、0.0006340876570902765、0.013289504684507847、-0.010359331034123898、-0.02956104 464828968, 0.0263456329703331, 0.02621597982943058, 0.005357939284294844, -0.022754225879907608, -0.009393410757184029, 0.007053161505609751, -0.018086692318320274, -0.0012552099069580436, 0.003977127373218536, -0.010839049704372883, -0.015843683 85374546, 0.007753291632980108, 0.005951105151325464, 0.02478978969156742, -0.00858955830335617, 0.007280055433511734, 0.013257091864943504, -0.0000065713156800484285, 0.007234676741063595, -0.00413919473066926, -0.01467679999768734, -0.01833303 4589886665, -0.017658835276961327, -0.01681608520448208, 0.005108356010168791, -0.007630120497196913, 0.008479352109134197, -0.02771996334195137,0.004567051772028208,-0。018579376861453056, -0.003983610309660435, -0.0023110774345695972, 0.023065393790602684, 0.04281165450811386, -0.015273206867 277622, -0.006696613971143961, 0.002272181212902069, -0.008356180973351002, -0.0.014508250169456005, -0.0066090975888073444, 0.00827838946133852, -0.016906842589378357, 0.003750233445316553, -0.008524730801582336, -0.0022802846506237984, -0.0051569761 70837879, -0.009633270092308521, -0.035940006375312805, -0.004323950968682766, 0.027771824970841408, 0.19261354207992554, -0.014547145925462246, -0.006657717749476433, 0.013808120042085648, -0.021340999752283096, 0.011869796551764011, 0.0241155903 78642082, 0.014080392196774483, 0.0023856281768530607, 0.0005133476224727929, -0.016206713393330574, 0.01723097823560238, 0.008012599311769009、0.0019723570439964533、0.006560477428138256、-0.040996503084897995、-0.010657534934580326、0.000370323 39605502784, -0.027875546365976334, -0.011727177537977695, -0.00768198212608695, -0.007299503777176142, -0.011202080175280571, -0.01939619518816471、0.039622172713279724、-0.011668833903968334、-0.015830717980861664、0.016919808462262154、0.03207632899 284363, 0.015960371121764183, -0.01093629002571106, -0.016842016950249672, -0.008336733095347881, -0.013244125992059708, -0.011999450623989105, -0.020122256129980087, -0.007422674912959337, -0.02501020021736622, -0.008505282923579216, -0.00552648911 2526178, -0.0011830900330096483, 0.01773662678897381, 0.010709396563470364, -0.007267090491950512, 0.015999266877770424, 0.02604742906987667, -0.013315435498952866, 0.01621967926621437, -0.02082238532602787, -0.01689387857913971, -0.04390074685215 95、-0.03358031064271927、0.000994281843304634、0.03726247698068619、-0.02208002656698227、0.000011990435268671717、 0.006949438713490963、0.020433424040675163、0.00515373470261693、-0.031298406422138214、0.0031116888858377934、0.0157010648 39959145, -0.02813485451042652, -0.007377295754849911, 0.007461570668965578, 0.03985555097460747, -0.010975186713039875, -0.025697365403175354、0.0397258959710598、-0.026319703087210655、-0.0030403793789446354、-0.010067610070109367、-0.00248610973 3581543, -0.0088812792673707, 0.0017438423819839954, -0.001923736883327365, 0.017827384173870087, 0.006220136769115925, 0.010255607776343822、0.001199296792037785、-0.01772366091609001、0.035136155784130096、-0.0061066895723342896、-0.0107353273 77915382, -0.010651051998138428, -0.026151152327656746, 0.006981851998716593, 0.006622062996029854, -0.010048162192106247, -0.0009124379721470177、-0.00419105589389801、-0.019668467342853546、0.00012296844215597957、0.004894427489489317、0.00685219 8392152786, 0.010437123477458954, 0.005908967927098274, 0.0038247844204306602, -0.008103356696665287, -0.006456754636019468, -0.028653468936681747、0.018216345459222794、0.032205980271101、0.00022101905778981745、-0.029664767906069756、-0.00815521832 5555325、0.03871459513902664、0.03394334018230438、0.005860347766429186、-0.013600673526525497、-0.016958704218268394、 0.006372479721903801,0.0012543996563181281, -0.01911095716059208, -0.010437123477458954, 0.008356180973351002, -0.012855164706707, -0.008472870104014 874, 0.019370263442397118, -0.029457321390509605, 0.0034487885423004627, -0.015415825881063938, -0.00047364120837301016, 0.008887761272490025、-0.0020015290938317776、0.010501950047910213、-0.007500466890633106、-0.0017470837337896228、0.01717911 660671234, -0.024063728749752045, 0.026734594255685806, -0.024556411430239677, 0.0013573121977970004, -0.00010007645323639736, -0.00450546620413661, 0.007513432297855616, 0.027201347053050995, 0.003426099196076393, -0.022183749824762344, 0.00281348545 1042652, 0.008064460940659046, 0.002243009163066745, 0.009899060241878033, 0.010988151654601097, -0.004790704697370529, -0.004638361278921366, 0.006025656126439571, -0.010605673305690289, -0.01625857502222061, -0.020342666655778885, -0.01609002426 2666702, -0.026410460472106934, 0.0121226217597723, -0.009406376630067825, 0.0023759042378515005, -0.0273828636854887, -0.015260240994393826, -0.004832841921597719, -0.0007702240254729986, 0.01856641098856926, -0.031039098277688026, 0.0073967440 985143185, 0.018721995875239372, -0.023026498034596443, -0.008200597018003464, -0.023480286821722984, -0.16450461745262146, 0.025710329413414, 0.01681608520448208, -0.009023898281157017, 0.023428425192832947, -0.022754225879907608, 0.02761624008417 1295, 0.015234310179948807, -0.009224860928952694, 0.005166700109839439, 0.0008131718495860696, 0.0038507150020450354, -0.03153178095817566, -0.0026757284067571163, 0.003335341578349471, 0.00672254478558898, -0.030546413734555244, 0.03627710789 4420624, 0.017256908118724823, 0.0010526260593906045, 0.0053125605918467045, -0.02091314271092415, -0.0016555157490074635, -0.0012454859679564834、0.023467320948839188、0.009497134014964104、0.0046351198107004166、0.005380628630518913、-0.02169106 5281629562, -0.013062611222267151, -0.048023734241724014, -0.0008427490829490125, 0.017321735620498657, 0.021340999752283096, 0.011740143410861492、0.012219862081110477、-0.012984818778932095、0.007020748220384121、-0.015130587853491306、-0.0161937475 20446777, 0.0071439193561673164, 0.03236156702041626, 0.024997234344482422, 0.01185683161020279, 0.010735327377915382, 0.04636416584253311、0.014599007554352283、-0.009004450403153896、0.019383229315280914、-0.009607339277863503、-0.00414891866 967082, -0.008336733095347881, -0.019888877868652344, -0.0005830365116707981, 0.02771996334195137, 0.005620488431304693, -0.00701426574960351、0.013730327598750591、0.014145219698548317、0.011331734247505665、-0.021807754412293434、0.02285794913 7687683, 0.01593444123864174, -0.0031343784648925066, 0.001282761339098215, -0.028627539053559303, 0.013354332186281681, 0.0034098925534635782, -0.014689764939248562, -0.004784221760928631, -0.015208380296826363, -0.00796722061932087, -0.0086932806 29813671, -0.02311725541949272, 0.011629937216639519, -0.012323584407567978, -0.03243935853242874, 0.007643085904419422, 0.00766253424808383,0.0028702090494334698, -0.017412493005394936, 0.026267841458320618, 0.010884428396821022, -0.03448788449168205, 0.004327192436 903715, 0.018838683143258095, -0.02228747308254242, -0.014702730812132359, -0.01020374707877636, -0.027694031596183777, 0.006122896447777748、-0.004252641461789608、-0.012686614878475666、-0.008829417638480663、0.03319134935736656、0.01789221167 564392, 0.021250242367386818, -0.006683648563921452, 0.009412859566509724, -0.02294870652258396, 0.0009659201023168862, -0.008336733095347881, -0.019603639841079712, -0.012116138823330402, 0.009775889106094837, 0.03993334248661995, 0.00989257823 6758709, 0.017153184860944748, 0.015545479021966457, -0.01288109552115202, -0.020433424040675163, 0.013652535155415535, 0.022170783951878548、0.024102624505758286、-0.003623821074143052、0.03230970352888107、0.01852751523256302、-0.031324334442 61551、-0.017218012362718582、0.011279872618615627、0.052250444889068604、0.005604281555861235、0.010722361505031586、 0.006155309733003378, -0.016362298280000687, 0.0038020950742065907, -0.1179330125451088, 0.0006563718779943883, 0.0069235078 99045944, 0.010300987400114536, 0.010313952341675758, 0.016128921881318092, 0.010683465749025345, 0.032050397247076035, -0.0040808506309986115, 0.011318768374621868, -0.021016865968704224, -0.05787741392850876, -0.018786821514368057, -0.0315577127 0394325, 0.010994634591042995, -0.00672254478558898, 0.010605673305690289, -0.029042430222034454, -0.018294138833880424, 0.01147435326129198、-0.0367957204580307、0.016906842589378357、0.010385261848568916、-0.006301170215010643、-0.0145471459254 62246, -0.004356364719569683, -0.03181701898574829, -0.0031505851075053215, 0.004936564713716507, 0.012952405028045177, 0.010398227721452713, -0.018164483830332756, 0.01794407330453396, -0.020977970212697983, -0.0003221084189135581, 0.0076171550 89974403, 0.0036173383705317974, -0.01026209071278572, 0.037651438266038895, -0.015662167221307755, 0.011156701482832432, -0.014599007554352283、-0.00417160801589489、-0.03412485495209694、0.010022231377661228、0.004084091633558273、-0.005659384187 310934, -0.0012973473640158772, 0.02266346849501133, -0.015195414423942566, -0.021211346611380577, -0.01056029461324215, -0.008284871466457844、-0.001761669758707285、0.005711245816200972、0.009205413050949574、0.008997967466711998、-0.0214706547 55830765, -0.02379145473241806, 0.013872946612536907, -0.004845807328820229, -0.016193747520446777, -0.003912300802767277, 0.00304200011305511, -0.002687073079869151, -0.007617155089974403, 0.003983610309660435, -0.028575677424669266, 0.01293944008 6483955, -0.004434156697243452, -0.020381562411785126, 0.0030338966753333807, -0.022131888195872307, 0.0012187449028715491, -0.020251909270882607、0.003640027716755867、-0.018449721857905388、0.008557144552469254、0.029042430222034454、-0.0080709429 4577837, -0.025502884760499, -0.025852948427200317, 0.03057234361767769, -0.032205980271101, 0.011779039166867733, 0.007481019012629986,-0.010112988762557507,0。017114289104938507, 0.011623455211520195, -0.01751621626317501, -0.009341550059616566, -0.005238009616732597, -0.0135617777705 19257, -0.005001391749829054, -0.014702730812132359, 0.008609006181359291, -0.009568443521857262, 0.00857011042535305, 0.0027049004565924406、0.009101689793169498、-0.018294138833880424、-0.0010202126577496529、-0.07286538183689117、0.012148552 57421732, -0.011403043754398823, 0.0032656528055667877, 0.0046221548691391945, -0.017568077892065048, 0.019136887043714523, -0.022546779364347458, -0.0037826469633728266, -0.004913875367492437, -0.01572699472308159, 0.034306369721889496, 0.0135099161 41629219, -0.014158184640109539, -0.011014082469046116, -0.010787188075482845, 0.005027322564274073, 0.002033942611888051, 0.017218012362718582、0.02478978969156742、-0.010430640541017056、0.0027437966782599688、0.00802556425333023、-0.01406742725 521326, 0.0038442325312644243, 0.0035038914065808058, -0.003345065750181675, 0.02386924810707569, -0.00384747376665473, -0.012550478801131248、0.0008500420954078436、-0.012025381438434124、0.015662167221307755、0.019914809614419937、0.029846282 675862312, -0.026656802743673325, -0.006203929893672466, -0.011033530347049236, 0.04947585612535477, 0.03575849160552025, -0.007960737682878971, -0.024984268471598625, 0.013548812828958035, -0.02484164945781231, -0.01406742725521326, 0.011681798845 529556、-0.022806087508797646、0.0018378413515165448、0.030961304903030396、0.007928323931992054、0.03251715004444122、 0.010884428396821022, 0.002808623481541872, -0.008466387167572975, 0.02379145473241806, -0.019162818789482117, 0.05357291176 915169, -0.0044049848802387714, -0.0040581608191132545, -0.013471020385622978, 0.020718662068247795, 0.00829783733934164, -0.01685498282313347, -0.004100298509001732, -0.000024132808903232217, -0.014482319355010986, -0.03404706344008446, 0.007876462 303102016, 0.0011855211341753602, -0.0405556783080101, -0.01225227490067482, -0.006268756929785013, 0.015312102623283863, 0.015299137681722641、0.013548812828958035、0.014560110867023468、0.01471569575369358、-0.002121458761394024、-0.01100111659 616232, 0.00015933225222397596, 0.01965550146996975, -0.003769681556150317, -0.02826450765132904, 0.01413225382566452, 0.029198015108704567、0.048568278551101685、-0.005461662542074919、0.014274872839450836、0.0036529931239783764、0.005160217 639058828, 0.0010145402047783136, 0.017243942245841026, -0.006793854292482138, 0.0005344163510017097, 0.01341915875673294, 0.019538814201951027, -0.003721061395481229, -0.01056029461324215, 0.005033805035054684, 0.03562884032726288, -0.004832841921 597719, 0.012997783720493317, -0.006443789228796959, -0.015817752107977867, -0.015947405248880386, 0.023208012804389, -0.019590675830841064, -0.0267605260014534, -0.008045012131333351, 0.0018005658639594913, 0.022935740649700165, -0.00632385956 1234713, -0.0033677550964057446, 0.02027783915400505, -0.020433424040675163, 0.01689387857913971, -0.027019832283258438, -0.040166717022657394, -0.0001858707400970161,0.009393410757184029, 0.0010169713059440255, 0.00733839999884367, 0.00923782680183649, -0.011007599532604218, 0.02233933284 8787308, 0.01406742725521326, 0.01659567467868328, -0.021794788539409637, -0.019085025414824486, -0.008245975710451603, 0.016323402523994446, -0.0023759042378515005, -0.0077208783477544785, -0.001962633104994893, 0.0036108556669205427, -0.0008832 658641040325, -0.0267605260014534, 0.02873126231133938, -0.022935740649700165, 0.02412855438888073, -0.005513523705303669, 0.00507918419316411、0.005951105151325464、0.005173183046281338、0.005001391749829054、-0.0177625585347414、0.0151305878534 91306, -0.01999260112643242, -0.0192406103014946, 0.02140582725405693, -0.007377295754849911, 0.02927580662071705, -0.015104657039046288、-0.01216800045222044、0.0034552712459117174、-0.003481202060356736、0.013561777770519257、0.0022592158 056795597, -0.01183090079575777, 0.013665501028299332, 0.017075393348932266, 0.008511765860021114, -0.007409709505736828, -0.0014261907199397683、-0.003058206755667925、0.0031424816697835922、0.0021846650633960962、-0.000989419873803854、-0.0221448 54068756104, 0.0036270625423640013, -0.006233102176338434, -0.016504917293787003, 0.003999816719442606, 0.017931107431650162, -0.025956671684980392、0.021626237779855728、0.002192768268287182、-0.001260882243514061、0.018721995875239372、-0.0234932508 31961632, 0.030598275363445282, -0.011616972275078297, -0.019331367686390877, 0.01505279541015625, 0.01505279541015625, 0.004524914547801018, 0.0019042887724936008, -0.014962038025259972]01505279541015625, 0.004524914547801018, 0.0019042887724936008, -0.014962038025259972]01505279541015625, 0.004524914547801018, 0.0019042887724936008, -0.014962038025259972]

语义上相似的单词通常由在这个向量空间中彼此接近的向量表示。这使得加法和减法等数学运算能够传达语义。例如,“国王”减去“男人”加上“女人”的向量表示应该接近“女王”的向量表示。换句话说,向量嵌入是特定数据对象的数值表示。

向量索引允许您根据节点或关系的嵌入属性与查询中指定的属性之间的相似性来检索节点或关系的邻域。

创建向量索引

向量索引是节点的单标签、单属性索引或关系的单关系类型、单属性索引。它可用于通过LIST<INTEGER | FLOAT>对索引的维度和向量相似度函数有效的属性来索引节点或关系。请注意,可用的向量索引提供程序(vector-2.0(默认)和vector-1.0)支持不同的索引架构、属性值类型和向量维度。有关更多信息,请参阅兼容性的向量索引提供程序。

使用CREATE VECTOR INDEX命令创建向量索引,建议在创建索引时指定名称,如果创建时未指定名称,则会分配一个随机名称。从 Neo4j 5.16 开始,索引名称也可以作为参数指定:CREATE VECTOR INDEX $name …​。

索引名称在索引和约束中必须是唯一的。
新创建的索引不会立即可用,而是在后台创建。
创建索引需要 权限CREATE INDEX。
为属性Movie上的节点创建向量索引embedding在 5.15 中引入
CREATE VECTOR INDEX moviePlots IF NOT EXISTS
FOR (m:Movie)
ON m.embedding
OPTIONS {indexConfig: {
 `vector.dimensions`: 1536,
 `vector.similarity_function`: 'cosine'
}}
该CREATE VECTOR INDEX命令是可选的幂等命令。这意味着,如果尝试两次创建相同的索引,则其默认行为是抛出错误。使用IF NOT EXISTS,如果已存在具有相同名称、架构或两者的索引,则不会抛出任何错误,也不会发生任何事情。如果存在具有相同名称的约束,它仍可能会抛出错误。从 Neo4j 5.17 开始,当什么都没有发生时会返回信息通知,显示阻止创建的现有索引。
该OPTIONS映射是必需的,因为如果不设置向量维度和相似度函数,就无法创建向量索引。在此示例中,向量维度设置为1536,向量相似度函数为cosine,这通常是文本嵌入的首选相似度函数。要了解有关可用相似度函数的更多信息,请参阅余弦和欧几里得相似度函数。
在 Neo4j 5.15 之前,节点向量索引是使用该db.index.vector.createNodeIndex过程创建的。

您还可以使用以下语法为给定属性上具有特定类型的关系创建向量索引:

为单个属性上的关系类型创建向量索引在 5.18 中引入
CREATE VECTOR INDEX name IF NOT EXISTS
FOR ()-[r:REL_TYPE]-() ON (r.embedding)
OPTIONS {indexConfig: {
 `vector.dimensions`: $dimension,
 `vector.similarity_function`: $similarityFunction
}}

查询向量索引

要查询节点向量索引,请使用该db.index.vector.queryNodes过程。

签名db.index.vector.queryNodes
db.index.vector.queryNodes(indexName :: STRING, numberOfNearestNeighbours :: INTEGER, query :: ANY) :: (node :: NODE, score :: FLOAT)
  • 指indexName的是要查询的向量索引的唯一名称。

  • 指numberOfNearestNeighbours的是要返回的最近邻居的数量。

  • 该query向量指的是在LIST<INTEGER | FLOAT>其中搜索邻域。

该过程返回节点的邻域及其各自的相似性得分,并按得分排序。得分介于0和之间1,得分越接近1,索引向量与查询向量越相似。

找出与《教父》情节最相似的 5 部电影
MATCH (m:Movie {title: 'Godfather, The'})
CALL db.index.vector.queryNodes('moviePlots', 5, m.embedding)
YIELD node AS movie, score
RETURN movie.title AS title, movie.plot AS plot, score
结果
<span style="color:#5e636a"><span style="background-color:#ffffff"><span style="color:#1a1b1d"><code class="language-none">+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| title                      | plot                                                                                                                                                                                                                     | score              |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "Godfather, The"           | "The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant son."                                                                                                    | 1.0                |
| "Godfather: Part III, The" | "In the midst of trying to legitimize his business dealings in New York and Italy in 1979, aging Mafia don Michael Corleone seeks to avow for his sins while taking a young protégé under his wing."                     | 0.9648237228393555 |
| "Godfather: Part II, The"  | "The early life and career of Vito Corleone in 1920s New York is portrayed while his son, Michael, expands and tightens his grip on his crime syndicate stretching from Lake Tahoe, Nevada to pre-revolution 1958 Cuba." | 0.9547788500785828 |
| "Scarface"                 | "An ambitious and near insanely violent gangster climbs the ladder of success in the mob, but his weaknesses prove to be his downfall."                                                                                  | 0.9367183446884155 |
| "Jane Austen's Mafia!"     | "Takeoff on the Godfather with the son of a mafia king taking over for his dying father"                                                                                                                                 | 0.9366795420646667 |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+</code></span></span></span>

请注意,返回的所有电影都围绕犯罪家族组织展开情节。结果按降序score排列,其中最匹配的结果条目放在第一位(在本例中,相似度得分为,这是可以预料的,因为索引是使用此特定属性查询的)。如果不需要查询向量本身,则添加谓词会删除相同的向量。The Godfather1.0WHERE score < 1

要查询关系向量索引,请使用该db.index.vector.queryRelationships过程。

签名db.index.vector.queryRelationships 在 5.18 中引入
db.index.vector.queryRelationships(indexName :: STRING, numberOfNearestNeighbours :: INTEGER, query :: ANY) :: (relationship :: RELATIONSHIP, score :: FLOAT)

db.index.vector.queryRelationships具有与 相同的参数描述db.index.vector.queryNodes。

使用向量函数计算两个特定向量对之间的相似度得分,而无需使用向量索引。

性能建议

向量索引可以利用孵化的 Java 20 Vector API 来显著提高速度。如果您使用的是兼容版本的 Java,则可以将以下设置添加到配置设置中:

配置设置
server.jvm.additional=--add-modules jdk.incubator.vector

显示向量索引

要列出数据库中的所有向量索引,请使用该SHOW VECTOR INDEXES命令。此SHOW命令与其他索引的命令相同,但索引类型筛选为VECTOR。

列出索引需要 权限SHOW INDEX。
例 1. 显示所有向量索引
使用默认返回列显示向量索引
SHOW VECTOR INDEXES
结果
<span style="color:#5e636a"><span style="background-color:#ffffff"><span style="color:#1a1b1d"><code class="language-none">+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| id | name         | state    | populationPercent | type     | entityType | labelsOrTypes | properties        | indexProvider | owningConstraint | lastRead                 | readCount |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| 2  | "moviePlots" | "ONLINE" | 100.0             | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"]     | "vector-2.0"  | NULL             | 2024-05-07T09:19:09.225Z | 47        |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+</code></span></span></span>

有关所有返回列的完整描述,请参阅搜索结果索引 → 列表索引的结果列。

示例 2.显示具有完整或筛选详细信息的向量索引

要返回完整的向量索引详细信息,请使用YIELD *。

显示所有向量索引及所有返回列
SHOW VECTOR INDEXES YIELD *
结果
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| id | name         | state    | populationPercent | type     | entityType | labelsOrTypes | properties        | indexProvider | owningConstraint | lastRead                 | readCount | trackedSince             | options                                                                                                         | failureMessage | createStatement                                                                                                                                                                                  |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| 2  | "moviePlots" | "ONLINE" | 100.0             | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"]     | "vector-2.0"  | NULL             | 2024-05-07T09:19:09.225Z | 47        | 2024-05-07T08:26:19.072Z | {indexConfig: {`vector.dimensions`: 1536, `vector.similarity_function`: "COSINE"}, indexProvider: "vector-2.0"} | ""             | "CREATE VECTOR INDEX `moviePlots` FOR (n:`Movie`) ON (n.`embedding`) OPTIONS {indexConfig: {`vector.dimensions`: 1536,`vector.similarity_function`: 'COSINE'}, indexProvider: 'vector-2.0'}"     |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

要仅返回特定的详细信息,请在子句后指定所需的列名YIELD。

显示所有带有过滤返回列的向量索引
SHOW VECTOR INDEXES YIELD name, type, entityType, labelsOrTypes, properties
结果
+----------------------------------------------------------------------+
| name         | type     | entityType | labelsOrTypes | properties    |
+----------------------------------------------------------------------+
| "moviePlots" | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"] |
+----------------------------------------------------------------------+

删除向量索引

使用与其他索引相同的命令删除向量索引。DROP INDEX从 Neo4j 5.16 开始,删除索引时也可以将索引名称作为参数给出: DROP INDEX $name。

删除索引需要 权限DROP INDEX。
删除向量索引
DROP INDEX moviePlots

用于兼容性的向量索引提供程序

从 Neo4j 5.18 开始,默认和首选的向量索引提供程序是vector-2.0。以前创建的vector-1.0索引将继续起作用。vector-1.0如果在映射中指定了提供程序,仍然可以使用该提供程序创建新索引OPTIONS。

余弦和欧几里得相似函数

相似度函数的选择会影响哪些索引向量被视为相似,哪些是有效的。向量的语义含义本身可能决定选择哪个相似度函数。请参阅您正在使用的特定向量嵌入模型的文档,因为它可能会建议对某些相似度函数的偏好。否则,能够区分各种相似度函数可以帮助做出更明智的决定。

表 1. 相似度函数
姓名不区分大小写的参数关键相似特征

余弦

"cosine"

角度

欧几里得

"euclidean"

距离

-标准化向量(单位向量),余弦和欧几里得相似函数产生相同的相似性顺序。

向量索引程序

用法程序描述

创建节点向量索引。

使用给定的相似度函数为具有给定向量维度的指定标签和属性创建向量索引。由命令替换CREATE VECTOR INDEX。

使用节点向量索引。

查询给定的节点向量索引。返回请求的近似最近邻节点数量及其相似度得分,按得分排序。

使用关系向量索引。

查询给定的关系向量索引。返回请求的近似最近邻关系数量及其相似性得分,按得分排序。在 5.18 中引入

设置节点矢量属性。

使用给定的向量以比直接使用更节省空间的方式更新给定的节点属性SET。替换db.create.setVectorProperty。测试版 在 5.13 中引入

设置节点矢量属性。

取而代之db.create.setNodeVectorProperty。已弃用 测试版

设置关系向量属性。

使用给定的向量以比直接使用更节省空间的方式更新给定的关系属性SET。测试版 在 5.18 中引入

限制和已知问题

从 Neo4j 5.13 开始,向量索引不再是测试版功能。但是,它仍然存在一些限制和已知问题。

探索Neo4j向量索引:提升图数据库的搜索能力 Neo4j的向量索引为开发者提供了一种强大的工具,可以在复杂的数据关系中进行高效的搜索和查询。未来的更新版本中可能还会引入更多的特性和优化。 阅读详情

相关推荐

深入探索Neo4j Vector Index:实现高效向量相似性搜索

Neo4j提供的向量索引支持多种相似性度量,包括常见的余弦相似性和欧几里得相似性。这种集成支持使得开发者可以方便地在大型文本语料中进行高效的相似性搜索。本文介绍了如何使用Neo4j的向量索引实现文本相似性搜索,内容涵盖了从环境准备、数据加载到搜索执行的全过程。Neo4j 官方文档OpenAI API 文档博客文章:Neo4j 中的混合搜索。

aehrutktrjk的博客 900

neo4j使用详解(十六、索引之语义索引<向量索引>——最全参考)

节点矢量搜索索引在Neo4j 5.11中作为公测版本发布,在Neo4j 5.13中作为通用版本发布。向量索引允许用户从大型数据集查询向量嵌入。嵌入是数据对象(如文本、图像、音频或文档)的数字表示。例如,文本中的每个单词或标记通常表示为高维向量,其中每个维表示单词含义的某个方面。语义上相似或相关的词通常用向量空间中彼此更接近的向量来表示。这允许像加法和减法这样的数学运算带有语义意义。例如,“国王”减去“男人”加上“女人”的向量表示可能接近于“女王”的向量表示。

Timmer的博客 6024

探索Neo4j和LangChain的强大组合:用向量索引优化文本检索

本文介绍了如何结合使用Neo4j和LangChain,以利用向量索引实现高效的文本数据检索。OpenAI API。

nseejrukjhad的博客 559

人工智能之利用LangChain和Neo4j向量索引,构建一个RAG应用程序

这种集成有助于将数据有效地摄取到 Neo4j Vector Index 中,简化了 RAG 应用程序中的数据摄取和查询,并能够构建有效的 RAG 应用程序,通过利用结构化和非结构化数据提供实时、准确且与上下文相关的答案。例如,如果我们使用向量相似性搜索来检索前三个结果,则摘要将重复三次。例如,如果我们想要创建一个问答系统,根据提供的上下文生成答案,同时还提供它用作上下文的文档,我们可以使用以下代码。正如我们所看到的,LLM 根据提供的维基百科文章构建了准确的答案,但也返回了它使用的源文档。

人工智能讲师分享前沿技术 1480

海康线扫相机平场矫正实战:从原理到精准成像

本文深入解析了海康线扫相机平场矫正的原理与实战操作。通过拆解暗场与明场矫正的物理意义,揭示了其消除系统噪声、补偿像素响应不均的核心机制。文章详细指导了在海康相机上进行平场矫正的标准化流程、关键参数设置(如行高、灰度值控制)及常见误区,并提供了针对高行频匹配、环境稳定性维护等进阶调优技巧与问题排查指南,旨在帮助用户实现从原理理解到精准成像的跨越。

tomato的博客 790

安卓7.0+抓包难题:雷电模拟器9.0+Charles系统证书安装全攻略

HTTPS协议通过SSL/TLS加密保障网络通信安全,其核心机制依赖于证书信任链。在Android系统中,自7.0版本起,谷歌收紧了证书信任策略,默认仅信任系统预置的CA证书,这直接导致了传统抓包方法失效。理解这一原理对于移动开发、测试及安全研究至关重要,它揭示了应用层安全策略与系统底层机制的关联。通过将用户证书安装至系统信任区,可以突破此限制,实现HTTPS流量的解密与分析。这一技术在App调试、接口测试、安全审计等场景中具有广泛的应用价值。本文以雷电模拟器9.0和Charles抓包工具为例,详细演示了如

weixin_42521843的博客 279

Dify+Neo4j向量检索优化指南,5个你必须掌握的索引技巧

掌握Dify-Neo4j向量检索的索引优化,提升查询效率与系统性能。适用于知识图谱、智能推荐等场景,涵盖复合索引设计、向量维度压缩、查询缓存策略等5大核心技巧。显著降低响应延迟,增强高并发处理能力,值得收藏。

CodePulse的博客 690

STM32F407通过SMBus协议精准读取BQ40Z50电池电量

本文详细介绍了STM32F407通过SMBus协议精准读取BQ40Z50电池电量的实现方法。从硬件连接到软件驱动开发,再到通信异常排查,提供了完整的解决方案。重点解析了SMBus协议的特殊时序要求、GPIO模拟驱动的关键代码,以及实际调试中的常见问题与对策,帮助开发者高效完成电池管理系统开发。

weixin_29189003的博客 253

【neo4j】win/linux安装和使用+cypher+langchian+向量索引

进入http://localhost:7474后输入用户密码,用户名是neo4j,密码是刚刚设置的数据库密码。设置下环境变量,把解压后的neo4j-community-5.21.2/bin放到环境变量的path里。上述做法是在conf配置里取消一行内容的注释,但是我这版的conf根本没有这行内容。设置下数据库名和密码,我这里设置的数据库是test,密码是rootroot。照上面参考的使用就可以了,windows和linux两版的连接都没有问题。bolt://localhost:7687是bolt协议。

zt0612xd的博客 1685

【chips】个人笔记系列-SystemVerilog

个人整理的Systemverilog笔记。

Hide_in_Code 2058

暗月项目七详解

本文围绕“暗月靶场项目七”展开,记录了一次从外网 Web 入口逐步深入内网并最终获取域控目标的完整实训过程。

Re_K123的博客 417

Neo4j向量索引实战:从原理到应用的全链路解析

本文全面解析Neo4j向量索引的原理与应用,从HNSW算法底层实现到实战构建论文检索系统。通过余弦相似度和欧式距离计算,实现高效的语义搜索,并分享性能优化技巧和混合查询等高级应用场景,帮助开发者掌握向量索引在Neo4j中的全链路实践。

weixin_30263277的博客 419

游戏开发实战:5种AOI算法对比(九宫格 vs 灯塔 vs 十字链表)

本文深入对比了游戏开发中五种主流AOI算法(九宫格、灯塔、十字链表等)的性能与适用场景,帮助开发者根据项目规模选择最优解决方案。通过详细的技术分析和实战数据,揭示不同算法在万人同屏等极端场景下的表现差异,为MMORPG等大型多人在线游戏提供关键性能优化指南。

weixin_29268385的博客 474

Neo4j向量索引调优全解析,在Dify中实现1秒内响应语义查询

掌握Dify与Neo4j的向量检索集成,实现语义查询1秒内响应。适用于智能问答、知识图谱等场景,通过Neo4j向量索引调优提升查询效率。涵盖索引配置、相似度算法优化等核心方法,显著增强语义匹配精度,值得收藏

LearnPlex的博客 960

【unity实战】Unity游戏开发:如何用ScriptableObject与序列化多态实现可复用的模块化效果系统?

本文介绍了两种实现卡牌游戏效果系统的模块化设计方案。方案一使用ScriptableObject创建独立的效果资产,通过组合实现不同效果,优点是数据可复用、可视化编辑,缺点是同类不同参数效果需创建大量SO文件。方案二利用SerializeReference特性直接嵌套效果实例,避免SO文件过多,但需要插件支持编辑器多态显示。两种方案都将效果与卡牌解耦,提高了代码复用性和扩展性,解决了硬编码带来的重复、维护困难和扩展不便等问题。开发者可根据项目需求选择合适方案,或结合两者优势构建更灵活的系统。

向宇的博客,专注php/web全栈 unity游戏开发,欢迎大家评论纠错 436

Dify 第 2 篇 Dify 插件离线安装

Dify是一个支持插件扩展的AI平台,其插件市场提供5种类型插件(模型、工具、Agent策略、扩展、插件包)。由于默认pip安装速度慢,可通过dify-plugin-repackaging工具将插件转换为离线包(使用阿里云镜像加速)。该工具提供两种方式:1)自备Python环境执行脚本;2)使用Docker环境(推荐)。脚本支持从Dify市场或GitHub下载插件,并重新打包为含依赖的离线包,便于通过"本地插件"方式快速安装。

甘蓝的专栏 1264

Neo4j向量索引优化实战(从入门到高阶的3个关键步骤)

掌握Dify-Neo4j向量检索的索引优化,提升图数据库查询效率。本文详解从基础配置到高阶调优的3个关键步骤,覆盖相似性搜索、向量索引构建与性能对比,适用于AI推荐、知识图谱等场景,显著降低响应延迟,值得收藏。

QuickProceed的博客 1111

迈瑞BS系列全自动生化分析仪LIS协议接口手册(内含HL7和ASTM)

迈瑞BS系列全自动生化分析仪LIS协议接口手册,内含HL7和ASTM)

Neo4j向量检索性能翻倍的秘密:Dify场景下的索引重建策略

提升Dify-Neo4j向量检索性能的实用方法,揭秘索引重建策略如何实现查询速度翻倍。针对高并发场景,通过动态索引优化与向量化存储结构改进,显著降低响应延迟。掌握这一Dify-Neo4j向量检索的索引优化方案,值得收藏。

BytePerch的博客 900

汉书HE8,好用的汇编代码编写工具

汉书HE8,好用的汇编代码编写工具早期编写汇编代码所用功能强大

LinePhone3.2.7(android端最新版本) sip客户端

SIP客户端For android:LinePhone3.2.7(最新版本),官网地址:http://www.linphone.org/

【专家亲授】Dify-Neo4j向量检索索引设计:避开90%开发者踩过的坑

掌握Dify-Neo4j向量检索的索引优化秘诀,解决查询慢、性能低难题。适用于知识图谱、智能推荐等场景,通过复合索引与向量化策略提升检索效率3倍以上。避开常见设计误区,实现毫秒级响应,值得收藏。

VarChat的博客 869

SAP B1中文培訓教材_SDK

公司内部培训资料,对开发工具 ,DIAPI, UIAPI,Add-ON有详细解说

【Dify-Neo4j向量检索性能突破】:揭秘索引优化的5大核心策略

提升Dify-Neo4j向量检索性能,揭秘索引优化的5大核心策略。涵盖查询加速、存储结构优化与高并发场景适配,显著降低响应延迟。深入解析适用场景与关键技术实现,助力系统高效稳定运行,值得收藏。

LearnFlow的博客 686

Dify中Neo4j向量检索为何卡顿?3步定位并优化索引瓶颈

解决Dify-Neo4j向量检索卡顿难题,3步精准定位索引瓶颈。涵盖高频查询场景,通过智能索引策略与执行计划优化,显著提升检索效率。掌握Dify-Neo4j向量检索的索引优化关键技巧,性能飞跃值得收藏。

ProceChat的博客 876

还在为向量检索延迟发愁?揭秘Dify-Neo4j索引优化的4大黄金法则

解决向量检索延迟难题,揭秘Dify-Neo4j向量检索的索引优化4大黄金法则。适用于AI知识图谱、智能问答等场景,通过索引结构调优、查询路径精简、向量嵌入预处理与缓存策略提升性能,显著降低响应延迟。方法实用高效,值得收藏。

CompiLume的博客 925

(独家披露)Dify-Neo4j向量检索索引优化秘籍:仅限高级工程师掌握的2种方法

掌握Dify-Neo4j向量检索的索引优化,显著提升图数据库查询效率。针对高维向量场景,揭秘基于HNSW与复合属性索引的2种高级优化方法,降低响应延迟达60%。适用于AI推荐、语义搜索等实时应用,性能飞跃,值得收藏。

AlgoPerch的博客 674

向量检索太慢?Dify+Neo4j索引调优全解析,性能提升90%不是梦

向量检索太慢?掌握Dify-Neo4j向量检索的索引优化方法,提升查询效率。适用于AI知识库、语义搜索等场景,通过索引策略调优实现性能飞跃,响应速度提升90%值得收藏

FastProceed的博客 1095

利用 LangChain 和 Neo4j 向量索引,构建一个RAG应用程序

向量索引是 Neo4j 的一个重要补充,使其成为处理 RAG 应用程序的结构化和非结构化数据的出色解决方案。希望 LangChain 集成能够简化将向量索引集成到现有或新的 RAG 应用程序中的过程,这样我们就不必担心细节。请记住,LangChain 已经支持生成 Cypher 语句并使用它们来检索上下文,因此我们现在可以使用它来检索结构化和非结构化信息。参考文献。

2201_75499313的博客 3423

Neo4j 5.x 向量索引实战:对比3种相似度函数与混合查询性能

本文深入评测Neo4j 5.x向量索引功能,对比余弦、欧式和点积三种相似度函数在性能与准确率上的差异,并详解图过滤与向量搜索的混合查询技巧。通过实战案例展示如何优化索引配置和查询性能,为智能推荐、知识图谱等场景提供高效解决方案。

weixin_33883104的博客 311
上一篇: neo4j UNION
下一篇: GraphRAG 介绍
hellochenlian
博客等级 码龄17年 629粉丝 295原创
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

个

红包个数最小为10个

元

红包金额最低5元

当前余额3.43元 前往充值 >
需支付:10.00元
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包

打赏作者

hellochenlian

你的鼓励将是我创作的最大动力

¥1 ¥2 ¥4 ¥6 ¥10 ¥20
扫码支付:¥1
获取中
扫码支付

您的余额不足,请更换扫码支付或充值

打赏作者

实付元
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值