The results of WeightedRanker are inconsistent with the manually calculated results

[secsilm]

To illustrate the issue, I:

1. Created a sample database with the following configuration:

2. Randomly generated some data and inserted it. Here is the generated data:
   test.sample.100 (2).csv

3. Performed a hybrid search on attu:
   
   You can see that the score for id -107704053 is 0.54694002866745.

4. Calculated manually:

from pymilvus import (
    AnnSearchRequest,
    Collection,
    MilvusClient,
    WeightedRanker,
    connections,
    utility,
)

dim = 384
collection_name = "test"
metric_type = "COSINE"

connections.connect(
    host="localhost",
    port="19530",
    user="root",
    password="password",
    db_name="default",
)
print(utility.get_server_version())
collection = Collection(collection_name)
client = MilvusClient(
    host="localhost",
    port="19530",
    user="root",
    password="password",
    db_name="default",
)

# Create ANN search request 1 for title_embed
query_title_embed = [[0.983523428440094,-0.8391790390014648,-0.8032287359237671,-0.5166313052177429,0.05071425437927246,0.5441797375679016,-0.5547304749488831,-0.603778064250946,-0.15840409696102142,-0.6537017226219177,0.361355185508728,0.622897744178772,-0.07799355685710907,-0.6141539812088013,0.7908791303634644,0.6941851377487183,-0.657155454158783,0.11362609267234802,0.4948195815086365,0.40579649806022644,-0.25325828790664673,0.9457282423973083,0.3905382454395294,0.9559028744697571,-0.8652129173278809,0.13507923483848572,0.2217797040939331,0.2167176753282547,-0.9417803287506104,-0.3469189405441284,0.2515069842338562,0.758793294429779,-0.665325403213501,-0.9630787372589111,0.8929239511489868,0.2826336920261383,-0.49395236372947693,-0.7083621025085449,-0.9299284219741821,-0.03956103324890137,-0.3250620365142822,-0.2949804365634918,0.5097399353981018,0.38044241070747375,-0.0008414802141487598,-0.0022818073630332947,0.6071318984031677,-0.46523478627204895,0.6339311599731445,0.1754024475812912,-0.9917840361595154,0.5002033710479736,0.5469969511032104,0.5317974090576172,-0.30454713106155396,-0.5858418345451355,-0.21189971268177032,-0.5175448656082153,0.2752014994621277,-0.42725297808647156,0.21428680419921875,-0.15107949078083038,0.32962697744369507,0.660426676273346,0.2844550609588623,0.16602714359760284,0.45362579822540283,-0.9070158004760742,-0.9045433402061462,0.412014901638031,-0.4642958343029022,0.15941861271858215,0.1847061663866043,-0.6178812384605408,0.3987264335155487,-0.25759050250053406,-0.7203645706176758,-0.14423000812530518,-0.8244701623916626,-0.6012415289878845,-0.018422549590468407,0.10039536654949188,0.38867416977882385,0.20169752836227417,-0.6089040637016296,0.18944890797138214,0.9589499235153198,0.5513626933097839,-0.635711669921875,0.42406103014945984,0.3656099736690521,-0.5914181470870972,0.3328245282173157,0.6406367421150208,0.4164564609527588,-0.6369005441665649,0.12179381400346756,-0.4336058795452118,-0.5966317057609558,-0.1514657586812973,0.667130708694458,0.636605978012085,0.9374914765357971,0.45470181107521057,-0.8407467007637024,-0.7280417680740356,0.9122164249420166,0.7940447926521301,-0.0031563513912260532,-0.4834553301334381,-0.5762156844139099,0.31938910484313965,-0.9107409715652466,-0.5853129029273987,-0.27609771490097046,0.3070986270904541,0.2542582154273987,-0.4088221490383148,0.2679722309112549,0.964634120464325,-0.8164207339286804,-0.5218080878257751,-0.6660234332084656,-0.9749698638916016,0.49477124214172363,0.14501555263996124,0.20497426390647888,0.9193476438522339,-0.11754743754863739,-0.8056240677833557,-0.8412579894065857,0.678379476070404,-0.07394459843635559,0.7672460675239563,-0.2842973470687866,0.7742812037467957,-0.8175541758537292,0.11186152696609497,-0.8373710513114929,0.7032427191734314,0.43958449363708496,0.02220936492085457,-0.9598187208175659,0.35095223784446716,-0.41268476843833923,0.5067937970161438,0.11656925827264786,-0.49431177973747253,0.17901720106601715,0.22209888696670532,0.6511514186859131,0.4211234450340271,0.9119741916656494,-0.5405924320220947,0.28618356585502625,-0.1471686214208603,-0.5067185163497925,-0.23226387798786163,0.661508321762085,0.7766247987747192,-0.36431586742401123,0.9015870094299316,-0.8802100419998169,-0.4566798210144043,0.7025085687637329,-0.7252403497695923,-0.9945029020309448,0.6247142553329468,0.043173324316740036,0.7189810872077942,0.3202139735221863,0.5947784781455994,-0.7841039299964905,0.653359591960907,-0.6404665112495422,0.739761471748352,0.23870137333869934,0.3836825489997864,0.07765422761440277,0.2279834747314453,0.9069516062736511,-0.19500677287578583,-0.4222830533981323,-0.13243640959262848,0.036507971584796906,-0.47556695342063904,-0.03019038215279579,0.9565433859825134,0.9613786935806274,0.42837363481521606,0.7795919179916382,0.9036203026771545,-0.39238837361335754,-0.8358848094940186,-0.9260507822036743,-0.9301326274871826,0.27498099207878113,-0.9233197569847107,0.21880531311035156,-0.19454772770404816,0.8739873766899109,0.4265751242637634,-0.22775717079639435,0.5014805197715759,0.6441541910171509,0.2317916303873062,0.618430495262146,-0.09997288137674332,0.21521319448947906,0.033637501299381256,-0.8412822484970093,0.9775489568710327,-0.5854083895683289,0.5756803750991821,-0.06309319287538528,-0.48027992248535156,0.36863160133361816,0.2351023554801941,-0.7617709040641785,-0.5252478718757629,-0.04759879782795906,0.1429697424173355,0.08635170757770538,-0.7161168456077576,0.27086755633354187,0.8123964667320251,-0.3769381642341614,-0.485711932182312,-0.8078860640525818,-0.3041667938232422,0.8764626383781433,0.9802131056785583,0.958717405796051,-0.2525680661201477,0.3777036964893341,-0.2676170766353607,-0.9939644932746887,0.17978426814079285,0.08505496382713318,0.7991445660591125,0.7662686705589294,-0.911207377910614,-0.6770098805427551,-0.13624440133571625,0.11619643867015839,0.5686232447624207,-0.6227269768714905,-0.30311888456344604,-0.5352568030357361,-0.43176504969596863,0.12724579870700836,-0.0007862784550525248,0.515409588813781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search_param_1 = {
    "data": query_title_embed,  # Query vector
    "anns_field": "title_embed",  # Vector field name
    "param": {
        "metric_type": "COSINE",  # This parameter value must be identical to the one used in the collection schema
    },
    "limit": 10,  # Number of search results to return in this AnnSearchRequest
}
request_1 = AnnSearchRequest(**search_param_1)

# Create ANN search request 2 for content_embed
query_content_embed = [[0.2861897945404053,-0.39101845026016235,0.6880837082862854,0.40235093235969543,-0.7203652262687683,0.9046116471290588,-0.046035945415496826,0.11374322324991226,0.1775716096162796,-0.7715834379196167,-0.17576931416988373,-0.9976612329483032,-0.7166515588760376,-0.7502949237823486,0.18102014064788818,0.04448854550719261,0.7685198783874512,-0.825968861579895,-0.8630498051643372,0.40380728244781494,-0.6665027141571045,-0.9203201532363892,-0.966298520565033,0.09880384802818298,0.5326834917068481,0.24795332551002502,0.46522974967956543,-0.9139230847358704,0.7969437837600708,0.8246533274650574,-0.5157542824745178,-0.18412333726882935,0.8964553475379944,0.32205286622047424,0.22472162544727325,-0.7737959623336792,-0.7086634039878845,0.8937684893608093,0.13746535778045654,0.7360185384750366,0.9025880694389343,-0.818394124507904,-0.4057571589946747,0.7623814344406128,-0.9072341918945312,-0.2942046821117401,-0.09541966021060944,-0.38862550258636475,0.041180070489645004,0.01517803966999054,0.6290923953056335,-0.15891779959201813,0.7977094054222107,-0.633341372013092,0.7554120421409607,-0.5681434273719788,-0.06281767040491104,-0.2984144687652588,0.9709879755973816,0.09502615034580231,-0.42507779598236084,-0.06629613041877747,0.9858709573745728,-0.8731403350830078,-0.7622696757316589,-0.9013647437095642,0.6308067440986633,0.2710781395435333,-0.2479594498872757,0.9279452562332153,0.87628173828125,0.2030203938484192,0.47604721784591675,-0.09691354632377625,-0.5607119202613831,-0.8055468201637268,-0.7259688377380371,0.23823150992393494,-0.16087253391742706,0.5741780400276184,0.205247163772583,-0.8487960696220398,0.8875460028648376,-0.3921508193016052,0.17340032756328583,0.8023339509963989,0.5828752517700195,0.1045493334531784,-0.24915750324726105,-0.8453338742256165,0.26331934332847595,-0.6573676466941833,-0.2577413022518158,0.31612545251846313,0.09309455752372742,-0.024703217670321465,0.6374219059944153,0.6393706798553467,0.6970018744468689,0.429146945476532,0.8132683634757996,-0.911218523979187,-0.4460456967353821,0.7832351326942444,-0.600439190864563,0.354434609413147,-0.24099966883659363,-0.28733307123184204,0.12446238100528717,0.5002736449241638,-0.5583096146583557,-0.4863644540309906,-0.11749423295259476,-0.4655034840106964,-0.013392954133450985,0.1862112581729889,0.15291927754878998,0.010878651402890682,0.9475089907646179,-0.5331373810768127,-0.446144700050354,-0.1131148412823677,-0.5636909008026123,0.6677161455154419,0.8891878128051758,0.7913194894790649,0.10785465687513351,-0.8987740874290466,0.8554578423500061,0.6591880321502686,-0.8802266716957092,-0.36406970024108887,-0.6805170178413391,0.7360439300537109,-0.6692677140235901,-0.030526496469974518,0.4683218002319336,0.5943816900253296,0.580885112285614,-0.21366633474826813,-0.7026301026344299,0.7043229341506958,-0.5809754729270935,-0.39050349593162537,0.48389333486557007,-0.9053614735603333,-0.6575913429260254,-0.3204646110534668,-0.623723566532135,-0.1247013732790947,0.5542570948600769,-0.19130946695804596,0.4849671721458435,-0.9033098220825195,0.09032738208770752,-0.2822946012020111,-0.3206619322299957,0.09276343882083893,0.8585870862007141,0.35389459133148193,-0.5027367472648621,0.9339624047279358,-0.3456558585166931,0.9621780514717102,-0.3029465675354004,-0.8451476097106934,0.45678481459617615,0.46149057149887085,-0.7866204977035522,-0.050517160445451736,0.18486547470092773,-0.8580964207649231,0.05636948347091675,0.3524029850959778,-0.9386275410652161,0.7184330224990845,-0.6879270672798157,0.6649265289306641,-0.6566826701164246,-0.2697645127773285,-0.5542512536048889,-0.8888866305351257,-0.12402517348527908,-0.5548505783081055,0.6583195328712463,0.3916422128677368,0.03040916845202446,0.5074292421340942,0.6988760828971863,0.3054898977279663,0.3988095223903656,0.17731960117816925,0.9392130970954895,0.9815362691879272,-0.0249361302703619,0.9754906892776489,0.5181635618209839,0.8987080454826355,-0.7648979425430298,-0.3481248617172241,0.930277943611145,0.6918122172355652,-0.8486305475234985,0.8349274396896362,-0.06586162745952606,-0.3519398272037506,-0.7556070685386658,-0.24719245731830597,-0.5402887463569641,0.6176698207855225,-0.7027993202209473,-0.14969384670257568,0.7222162485122681,0.7736344337463379,-0.8525734543800354,-0.009086236357688904,0.7535814642906189,-0.5838337540626526,0.8909141421318054,-0.6109655499458313,0.7436161637306213,0.007104672025889158,-0.3509502410888672,0.9158087968826294,-0.5518125295639038,0.3089018762111664,-0.4850153625011444,-0.25113505125045776,0.29541927576065063,-0.9309138059616089,0.025313083082437515,0.9005815386772156,-0.2867039442062378,0.5167450904846191,-0.47345712780952454,0.9213545918464661,0.05016353726387024,0.5042085647583008,-0.9961196780204773,0.16185052692890167,0.02881941944360733,0.9542166590690613,-0.8603371977806091,-0.892711877822876,-0.12569327652454376,-0.46957820653915405,-0.3539789021015167,-0.14250066876411438,0.9255494475364685,0.4533630907535553,0.5483347177505493,0.6578931212425232,-0.876625537872314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search_param_2 = {
    "data": query_content_embed,  # Query vector
    "anns_field": "content_embed",  # Vector field name
    "param": {
        "metric_type": "COSINE",  # This parameter value must be identical to the one used in the collection schema
    },
    "limit": 10,  # Number of search results to return in this AnnSe archRequest
}
request_2 = AnnSearchRequest(**search_param_2)

# Store these two requests as a list in `reqs`
reqs = [request_1, request_2]

rerank = WeightedRanker(0.8, 0.2)

# Compute distance using hybrid_search
res = collection.hybrid_search(
    reqs,  # List of AnnSearchRequests created in step 1
    rerank,  # Reranking strategy specified in step 2
    limit=10,  # Number of final search results to return
    consistency_level="Bounded",
)
hybrid_distance = None
for item in res[0]:
    if not hybrid_distance and item.id == -107704053:
        hybrid_distance = item.distance
    print(item.id, item.distance, sep="\t")

# Compute distance manually
pids = [item.id for item in res[0]]
search_params = {
    "data": query_title_embed,
    "anns_field": "title_embed",
    "search_params": {
        "metric_type": "COSINE",
    },
    "limit": 10,
    "consistency_level": "Bounded",
    "filter": f"pid in {pids}",
}
title_res = client.search(collection_name, **search_params)
manual_title_distance = None
for item in title_res[0]:
    if item["id"] == -107704053:
        manual_title_distance = item["distance"]
        break
print(title_res[0])

search_params = {
    "data": query_content_embed,
    "anns_field": "content_embed",
    "search_params": {
        "metric_type": "COSINE",
    },
    "limit": 10,
    "consistency_level": "Bounded",
    "filter": f"pid in {pids}",
}
content_res = client.search(collection_name, **search_params)
manual_content_distance = None
for item in title_res[0]:
    if item["id"] == -107704053:
        manual_content_distance = item["distance"]
        break
print(content_res[0])

hybrid_distance_manunal = (1 + manual_title_distance) * 0.5 * 0.8 + (1 + manual_content_distance) * 0.5 * 0.2

# Output result
print(f"\nHybrid distance computed by hybrid_search: {hybrid_distance}")
print(f"Hybrid distance computed manually        : {hybrid_distance_manunal}")

5. You will see the following output:

Hybrid distance computed by hybrid_search: 0.44489821791648865
Hybrid distance computed manually        : 0.5561228096485138

The manually computed result differs from the result of hybrid_search but is almost identical to the result on attu.

Thanks.

[yhmo]

The reason is: the search scope is different.

1. You call hybrid_search() to search the entire collection, all the 100 vectors are computed. The limit is 10. The id "-107704053" is not in the top10 of request_2.
2. You call search() with "filter"=f"pid in {pids}", the id "-107704053" is always in the "content_res".

[yhmo]

This script will return the expected result:

collection = Collection(collection_name)
client = MilvusClient(
    host="localhost",
    port="19530",
    user="root",
    password="password",
    db_name="default",
)

print("===============================================================")
# Create ANN search request 1 for title_embed
query_title_embed = [[0.983523428440094,-0.8391790390014648,-0.8032287359237671,-0.5166313052177429,0.05071425437927246,0.5441797375679016,-0.5547304749488831,-0.603778064250946,-0.15840409696102142,-0.6537017226219177,0.361355185508728,0.622897744178772,-0.07799355685710907,-0.6141539812088013,0.7908791303634644,0.6941851377487183,-0.657155454158783,0.11362609267234802,0.4948195815086365,0.40579649806022644,-0.25325828790664673,0.9457282423973083,0.3905382454395294,0.9559028744697571,-0.8652129173278809,0.13507923483848572,0.2217797040939331,0.2167176753282547,-0.9417803287506104,-0.3469189405441284,0.2515069842338562,0.758793294429779,-0.665325403213501,-0.9630787372589111,0.8929239511489868,0.2826336920261383,-0.49395236372947693,-0.7083621025085449,-0.9299284219741821,-0.03956103324890137,-0.3250620365142822,-0.2949804365634918,0.5097399353981018,0.38044241070747375,-0.0008414802141487598,-0.0022818073630332947,0.6071318984031677,-0.46523478627204895,0.6339311599731445,0.1754024475812912,-0.9917840361595154,0.5002033710479736,0.5469969511032104,0.5317974090576172,-0.30454713106155396,-0.5858418345451355,-0.21189971268177032,-0.5175448656082153,0.2752014994621277,-0.42725297808647156,0.21428680419921875,-0.15107949078083038,0.32962697744369507,0.660426676273346,0.2844550609588623,0.16602714359760284,0.45362579822540283,-0.9070158004760742,-0.9045433402061462,0.412014901638031,-0.4642958343029022,0.15941861271858215,0.1847061663866043,-0.6178812384605408,0.3987264335155487,-0.25759050250053406,-0.7203645706176758,-0.14423000812530518,-0.8244701623916626,-0.6012415289878845,-0.018422549590468407,0.10039536654949188,0.38867416977882385,0.20169752836227417,-0.6089040637016296,0.18944890797138214,0.9589499235153198,0.5513626933097839,-0.635711669921875,0.42406103014945984,0.3656099736690521,-0.5914181470870972,0.3328245282173157,0.6406367421150208,0.4164564609527588,-0.6369005441665649,0.12179381400346756,-0.4336058795452118,-0.5966317057609558,-0.1514657586812973,0.667130708694458,0.636605978012085,0.9374914765357971,0.45470181107521057,-0.8407467007637024,-0.7280417680740356,0.9122164249420166,0.7940447926521301,-0.0031563513912260532,-0.4834553301334381,-0.5762156844139099,0.31938910484313965,-0.9107409715652466,-0.5853129029273987,-0.27609771490097046,0.3070986270904541,0.2542582154273987,-0.4088221490383148,0.2679722309112549,0.964634120464325,-0.8164207339286804,-0.5218080878257751,-0.6660234332084656,-0.9749698638916016,0.49477124214172363,0.14501555263996124,0.20497426390647888,0.9193476438522339,-0.11754743754863739,-0.8056240677833557,-0.8412579894065857,0.678379476070404,-0.07394459843635559,0.7672460675239563,-0.2842973470687866,0.7742812037467957,-0.8175541758537292,0.11186152696609497,-0.8373710513114929,0.7032427191734314,0.43958449363708496,0.02220936492085457,-0.9598187208175659,0.35095223784446716,-0.41268476843833923,0.5067937970161438,0.11656925827264786,-0.49431177973747253,0.17901720106601715,0.22209888696670532,0.6511514186859131,0.4211234450340271,0.9119741916656494,-0.5405924320220947,0.28618356585502625,-0.1471686214208603,-0.5067185163497925,-0.23226387798786163,0.661508321762085,0.7766247987747192,-0.36431586742401123,0.9015870094299316,-0.8802100419998169,-0.4566798210144043,0.7025085687637329,-0.7252403497695923,-0.9945029020309448,0.6247142553329468,0.043173324316740036,0.7189810872077942,0.3202139735221863,0.5947784781455994,-0.7841039299964905,0.653359591960907,-0.6404665112495422,0.739761471748352,0.23870137333869934,0.3836825489997864,0.07765422761440277,0.2279834747314453,0.9069516062736511,-0.19500677287578583,-0.4222830533981323,-0.13243640959262848,0.036507971584796906,-0.47556695342063904,-0.03019038215279579,0.9565433859825134,0.9613786935806274,0.42837363481521606,0.7795919179916382,0.9036203026771545,-0.39238837361335754,-0.8358848094940186,-0.9260507822036743,-0.9301326274871826,0.27498099207878113,-0.9233197569847107,0.21880531311035156,-0.19454772770404816,0.8739873766899109,0.4265751242637634,-0.22775717079639435,0.5014805197715759,0.6441541910171509,0.2317916303873062,0.618430495262146,-0.09997288137674332,0.21521319448947906,0.033637501299381256,-0.8412822484970093,0.9775489568710327,-0.5854083895683289,0.5756803750991821,-0.06309319287538528,-0.48027992248535156,0.36863160133361816,0.2351023554801941,-0.7617709040641785,-0.5252478718757629,-0.04759879782795906,0.1429697424173355,0.08635170757770538,-0.7161168456077576,0.27086755633354187,0.8123964667320251,-0.3769381642341614,-0.485711932182312,-0.8078860640525818,-0.3041667938232422,0.8764626383781433,0.9802131056785583,0.958717405796051,-0.2525680661201477,0.3777036964893341,-0.2676170766353607,-0.9939644932746887,0.17978426814079285,0.08505496382713318,0.7991445660591125,0.7662686705589294,-0.911207377910614,-0.6770098805427551,-0.13624440133571625,0.11619643867015839,0.5686232447624207,-0.6227269768714905,-0.30311888456344604,-0.5352568030357361,-0.43176504969596863,0.12724579870700836,-0.0007862784550525248,0.515409588813781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search_param_1 = {
    "data": query_title_embed,  # Query vector
    "anns_field": "title_embed",  # Vector field name
    "param": {
        "metric_type": "COSINE",  # This parameter value must be identical to the one used in the collection schema
    },
    "limit": 10,  # Number of search results to return in this AnnSearchRequest
}
request_1 = AnnSearchRequest(**search_param_1)

# Create ANN search request 2 for content_embed
query_content_embed = [[0.2861897945404053,-0.39101845026016235,0.6880837082862854,0.40235093235969543,-0.7203652262687683,0.9046116471290588,-0.046035945415496826,0.11374322324991226,0.1775716096162796,-0.7715834379196167,-0.17576931416988373,-0.9976612329483032,-0.7166515588760376,-0.7502949237823486,0.18102014064788818,0.04448854550719261,0.7685198783874512,-0.825968861579895,-0.8630498051643372,0.40380728244781494,-0.6665027141571045,-0.9203201532363892,-0.966298520565033,0.09880384802818298,0.5326834917068481,0.24795332551002502,0.46522974967956543,-0.9139230847358704,0.7969437837600708,0.8246533274650574,-0.5157542824745178,-0.18412333726882935,0.8964553475379944,0.32205286622047424,0.22472162544727325,-0.7737959623336792,-0.7086634039878845,0.8937684893608093,0.13746535778045654,0.7360185384750366,0.9025880694389343,-0.818394124507904,-0.4057571589946747,0.7623814344406128,-0.9072341918945312,-0.2942046821117401,-0.09541966021060944,-0.38862550258636475,0.041180070489645004,0.01517803966999054,0.6290923953056335,-0.15891779959201813,0.7977094054222107,-0.633341372013092,0.7554120421409607,-0.5681434273719788,-0.06281767040491104,-0.2984144687652588,0.9709879755973816,0.09502615034580231,-0.42507779598236084,-0.06629613041877747,0.9858709573745728,-0.8731403350830078,-0.7622696757316589,-0.9013647437095642,0.6308067440986633,0.2710781395435333,-0.2479594498872757,0.9279452562332153,0.87628173828125,0.2030203938484192,0.47604721784591675,-0.09691354632377625,-0.5607119202613831,-0.8055468201637268,-0.7259688377380371,0.23823150992393494,-0.16087253391742706,0.5741780400276184,0.205247163772583,-0.8487960696220398,0.8875460028648376,-0.3921508193016052,0.17340032756328583,0.8023339509963989,0.5828752517700195,0.1045493334531784,-0.24915750324726105,-0.8453338742256165,0.26331934332847595,-0.6573676466941833,-0.2577413022518158,0.31612545251846313,0.09309455752372742,-0.024703217670321465,0.6374219059944153,0.6393706798553467,0.6970018744468689,0.429146945476532,0.8132683634757996,-0.911218523979187,-0.4460456967353821,0.7832351326942444,-0.600439190864563,0.354434609413147,-0.24099966883659363,-0.28733307123184204,0.12446238100528717,0.5002736449241638,-0.5583096146583557,-0.4863644540309906,-0.11749423295259476,-0.4655034840106964,-0.013392954133450985,0.1862112581729889,0.15291927754878998,0.010878651402890682,0.9475089907646179,-0.5331373810768127,-0.446144700050354,-0.1131148412823677,-0.5636909008026123,0.6677161455154419,0.8891878128051758,0.7913194894790649,0.10785465687513351,-0.8987740874290466,0.8554578423500061,0.6591880321502686,-0.8802266716957092,-0.36406970024108887,-0.6805170178413391,0.7360439300537109,-0.6692677140235901,-0.030526496469974518,0.4683218002319336,0.5943816900253296,0.580885112285614,-0.21366633474826813,-0.7026301026344299,0.7043229341506958,-0.5809754729270935,-0.39050349593162537,0.48389333486557007,-0.9053614735603333,-0.6575913429260254,-0.3204646110534668,-0.623723566532135,-0.1247013732790947,0.5542570948600769,-0.19130946695804596,0.4849671721458435,-0.9033098220825195,0.09032738208770752,-0.2822946012020111,-0.3206619322299957,0.09276343882083893,0.8585870862007141,0.35389459133148193,-0.5027367472648621,0.9339624047279358,-0.3456558585166931,0.9621780514717102,-0.3029465675354004,-0.8451476097106934,0.45678481459617615,0.46149057149887085,-0.7866204977035522,-0.050517160445451736,0.18486547470092773,-0.8580964207649231,0.05636948347091675,0.3524029850959778,-0.9386275410652161,0.7184330224990845,-0.6879270672798157,0.6649265289306641,-0.6566826701164246,-0.2697645127773285,-0.5542512536048889,-0.8888866305351257,-0.12402517348527908,-0.5548505783081055,0.6583195328712463,0.3916422128677368,0.03040916845202446,0.5074292421340942,0.6988760828971863,0.3054898977279663,0.3988095223903656,0.17731960117816925,0.9392130970954895,0.9815362691879272,-0.0249361302703619,0.9754906892776489,0.5181635618209839,0.8987080454826355,-0.7648979425430298,-0.3481248617172241,0.930277943611145,0.6918122172355652,-0.8486305475234985,0.8349274396896362,-0.06586162745952606,-0.3519398272037506,-0.7556070685386658,-0.24719245731830597,-0.5402887463569641,0.6176698207855225,-0.7027993202209473,-0.14969384670257568,0.7222162485122681,0.7736344337463379,-0.8525734543800354,-0.009086236357688904,0.7535814642906189,-0.5838337540626526,0.8909141421318054,-0.6109655499458313,0.7436161637306213,0.007104672025889158,-0.3509502410888672,0.9158087968826294,-0.5518125295639038,0.3089018762111664,-0.4850153625011444,-0.25113505125045776,0.29541927576065063,-0.9309138059616089,0.025313083082437515,0.9005815386772156,-0.2867039442062378,0.5167450904846191,-0.47345712780952454,0.9213545918464661,0.05016353726387024,0.5042085647583008,-0.9961196780204773,0.16185052692890167,0.02881941944360733,0.9542166590690613,-0.8603371977806091,-0.892711877822876,-0.12569327652454376,-0.46957820653915405,-0.3539789021015167,-0.14250066876411438,0.9255494475364685,0.4533630907535553,0.5483347177505493,0.6578931212425232,-0.876625537872314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search_param_2 = {
    "data": query_content_embed,  # Query vector
    "anns_field": "content_embed",  # Vector field name
    "param": {
        "metric_type": "COSINE",  # This parameter value must be identical to the one used in the collection schema
    },
    "limit": 10,  # Number of search results to return in this AnnSe archRequest
}
request_2 = AnnSearchRequest(**search_param_2)

# Store these two requests as a list in `reqs`
reqs = [request_1, request_2]

rerank = WeightedRanker(0.8, 0.2)

# Compute distance using hybrid_search
res = collection.hybrid_search(
    reqs,  # List of AnnSearchRequests created in step 1
    rerank,  # Reranking strategy specified in step 2
    limit=10,  # Number of final search results to return
    consistency_level="Bounded",
)
hybrid_distance = None
for item in res[0]:
    if not hybrid_distance and item.id == -107704053:
        hybrid_distance = item.distance
    print(item.id, item.distance, sep="\t")

print("===============================================================")
# Compute distance manually
pids = [item.id for item in res[0]]
search_params = {
    "data": query_title_embed,
    "anns_field": "title_embed",
    "search_params": {
        "metric_type": "COSINE",
    },
    "limit": 10,
    "consistency_level": "Bounded",
    # "filter": f"pid in {pids}",
}
title_res = client.search(collection_name, **search_params)
manual_title_distance = None
for item in title_res[0]:
    if item["id"] == -107704053:
        manual_title_distance = item["distance"]
        break
print(title_res[0])

search_params = {
    "data": query_content_embed,
    "anns_field": "content_embed",
    "search_params": {
        "metric_type": "COSINE",
    },
    "limit": 10,
    "consistency_level": "Bounded",
    # "filter": f"pid in {pids}",
}
content_res = client.search(collection_name, **search_params)
manual_content_distance = None
for item in content_res[0]:
    if item["id"] == -107704053:
        manual_content_distance = item["distance"]
        break
print(content_res[0])

print(manual_title_distance)
print(manual_content_distance)
hybrid_distance_manunal = 0.0
if manual_title_distance is not None:
    hybrid_distance_manunal = hybrid_distance_manunal + (1 + manual_title_distance) * 0.5 * 0.8
if manual_content_distance is not None:
    hybrid_distance_manunal = hybrid_distance_manunal + (1 + manual_content_distance) * 0.5 * 0.2

# Output result
print(f"\nHybrid distance computed by hybrid_search: {hybrid_distance}")
print(f"Hybrid distance computed manually        : {hybrid_distance_manunal}")

[secsilm]

As I understand, the working process of hybrid search in Milvus is roughly as follows:

For example, if an ID cannot be found in title_top10, then that item does not count towards the score, right?

[yhmo]

Right.