[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-github-qdrant-search-quality-diagnosis":3,"mdc-4ca1sx-key":47,"related-org-github-qdrant-search-quality-diagnosis":330,"related-repo-github-qdrant-search-quality-diagnosis":495},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":28,"repoUrl":29,"updatedAt":30,"license":31,"forks":32,"topics":33,"repo":42,"sourceUrl":45,"mdContent":46},"qdrant-search-quality-diagnosis","diagnose Qdrant search quality issues","Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', or 'quality dropped after quantization'. Also use when search quality degrades without obvious changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"github","GitHub","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgithub.png",[12,16,19,22,25],{"name":13,"slug":14,"type":15},"Data Quality","data-quality","tag",{"name":17,"slug":18,"type":15},"Qdrant","qdrant",{"name":20,"slug":21,"type":15},"Search","search",{"name":23,"slug":24,"type":15},"Analytics","analytics",{"name":26,"slug":27,"type":15},"Debugging","debugging",36978,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","2026-04-18T04:46:17.579894",null,4632,[34,35,36,37,38,39,40,41],"agent-skills","agents","ai","awesome","custom-agents","github-copilot","hacktoberfest","prompt-engineering",{"repoUrl":29,"stars":28,"forks":32,"topics":43,"description":44},[34,35,36,37,38,39,40,41],"Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Ftree\u002FHEAD\u002Fskills\u002Fqdrant-search-quality\u002Fdiagnosis","---\nname: qdrant-search-quality-diagnosis\ndescription: \"Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', or 'quality dropped after quantization'. Also use when search quality degrades without obvious changes.\"\n---\n\n# How to Diagnose Bad Search Quality\n\nBefore tuning, establish baselines. Use exact KNN as ground truth, compare against approximate HNSW. Target >95% recall@K for production.\n\n## Don't Know What's Wrong Yet\n\nUse when: results are irrelevant or missing expected matches and you need to isolate the cause.\n\n- Test with `exact=true` to bypass HNSW approximation [Search API](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Ftutorials-search-engineering\u002Fretrieval-quality\u002F?s=standard-mode-vs-exact-search)\n- Exact search bad = model or search pipeline problem. Exact good, approximate bad = tune HNSW.\n- Check if quantization degrades quality (compare with and without)\n- Check if filters are too restrictive (then you might need to use ACORN)\n- If duplicate results from chunked documents, use Grouping API to deduplicate [Grouping](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fsearch\u002Fsearch\u002F?s=grouping-api)\n\nPayload filtering and sparse vector search are different things. Metadata (dates, categories, tags) goes in payload for filtering. Text content goes in sparse vectors for search.\n\n## Approximate Search Worse Than Exact\n\nUse when: exact search returns good results but HNSW approximation misses them.\n\n- Increase `hnsw_ef` at query time [Search params](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimize\u002F?s=fine-tuning-search-parameters)\n- Increase `ef_construct` (200+ for high quality) [HNSW config](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Findexing\u002F?s=vector-index)\n- Increase `m` (16 default, 32 for high recall) [HNSW config](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Findexing\u002F?s=vector-index)\n- Enable oversampling + rescore with quantization [Search with quantization](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F?s=searching-with-quantization)\n- ACORN for filtered queries (v1.16+) [ACORN](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fsearch\u002Fsearch\u002F?s=acorn-search-algorithm)\n\nBinary quantization requires rescore. Without it, quality loss is severe. Use oversampling (3-5x minimum for binary) to recover recall. Always test quantization impact on your data before production. [Quantization](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F)\n\n## Wrong Embedding Model\n\nUse when: exact search also returns bad results.\n\nTest top 3 MTEB models on 100-1000 sample queries, measure recall@10. Domain-specific models often outperform general models. [Hosted inference](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Finference\u002F)\n\n## Unoptimized Search Pipeline\n\nUse when: exact search also returns bad results and model choice is confirmed by user.\n\nOptimize search according to advanced search-strategies skill.\n\n## What NOT to Do\n\n- Tune Qdrant before verifying the model is right for the task (most quality issues are model issues)\n- Use binary quantization without rescore (severe quality loss)\n- Set `hnsw_ef` lower than results requested (guaranteed bad recall)\n- Skip payload indexes on filtered fields then blame quality (HNSW can't traverse filtered-out nodes, and filterable HNSW is built only if payload indexes were set up prior)\n- Deploy without baseline recall or other search relevance metrics (no way to measure regressions)\n- Confuse payload filtering with sparse vector search (different things, different config)\n",{"data":48,"body":49},{"name":4,"description":6},{"type":50,"children":51},"root",[52,61,67,74,79,134,139,145,150,233,245,251,256,268,274,279,284,290],{"type":53,"tag":54,"props":55,"children":57},"element","h1",{"id":56},"how-to-diagnose-bad-search-quality",[58],{"type":59,"value":60},"text","How to Diagnose Bad Search Quality",{"type":53,"tag":62,"props":63,"children":64},"p",{},[65],{"type":59,"value":66},"Before tuning, establish baselines. Use exact KNN as ground truth, compare against approximate HNSW. Target >95% recall@K for production.",{"type":53,"tag":68,"props":69,"children":71},"h2",{"id":70},"dont-know-whats-wrong-yet",[72],{"type":59,"value":73},"Don't Know What's Wrong Yet",{"type":53,"tag":62,"props":75,"children":76},{},[77],{"type":59,"value":78},"Use when: results are irrelevant or missing expected matches and you need to isolate the cause.",{"type":53,"tag":80,"props":81,"children":82},"ul",{},[83,107,112,117,122],{"type":53,"tag":84,"props":85,"children":86},"li",{},[87,89,96,98],{"type":59,"value":88},"Test with ",{"type":53,"tag":90,"props":91,"children":93},"code",{"className":92},[],[94],{"type":59,"value":95},"exact=true",{"type":59,"value":97}," to bypass HNSW approximation ",{"type":53,"tag":99,"props":100,"children":104},"a",{"href":101,"rel":102},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Ftutorials-search-engineering\u002Fretrieval-quality\u002F?s=standard-mode-vs-exact-search",[103],"nofollow",[105],{"type":59,"value":106},"Search API",{"type":53,"tag":84,"props":108,"children":109},{},[110],{"type":59,"value":111},"Exact search bad = model or search pipeline problem. Exact good, approximate bad = tune HNSW.",{"type":53,"tag":84,"props":113,"children":114},{},[115],{"type":59,"value":116},"Check if quantization degrades quality (compare with and without)",{"type":53,"tag":84,"props":118,"children":119},{},[120],{"type":59,"value":121},"Check if filters are too restrictive (then you might need to use ACORN)",{"type":53,"tag":84,"props":123,"children":124},{},[125,127],{"type":59,"value":126},"If duplicate results from chunked documents, use Grouping API to deduplicate ",{"type":53,"tag":99,"props":128,"children":131},{"href":129,"rel":130},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fsearch\u002Fsearch\u002F?s=grouping-api",[103],[132],{"type":59,"value":133},"Grouping",{"type":53,"tag":62,"props":135,"children":136},{},[137],{"type":59,"value":138},"Payload filtering and sparse vector search are different things. Metadata (dates, categories, tags) goes in payload for filtering. Text content goes in sparse vectors for search.",{"type":53,"tag":68,"props":140,"children":142},{"id":141},"approximate-search-worse-than-exact",[143],{"type":59,"value":144},"Approximate Search Worse Than Exact",{"type":53,"tag":62,"props":146,"children":147},{},[148],{"type":59,"value":149},"Use when: exact search returns good results but HNSW approximation misses them.",{"type":53,"tag":80,"props":151,"children":152},{},[153,173,192,209,221],{"type":53,"tag":84,"props":154,"children":155},{},[156,158,164,166],{"type":59,"value":157},"Increase ",{"type":53,"tag":90,"props":159,"children":161},{"className":160},[],[162],{"type":59,"value":163},"hnsw_ef",{"type":59,"value":165}," at query time ",{"type":53,"tag":99,"props":167,"children":170},{"href":168,"rel":169},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimize\u002F?s=fine-tuning-search-parameters",[103],[171],{"type":59,"value":172},"Search params",{"type":53,"tag":84,"props":174,"children":175},{},[176,177,183,185],{"type":59,"value":157},{"type":53,"tag":90,"props":178,"children":180},{"className":179},[],[181],{"type":59,"value":182},"ef_construct",{"type":59,"value":184}," (200+ for high quality) ",{"type":53,"tag":99,"props":186,"children":189},{"href":187,"rel":188},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Findexing\u002F?s=vector-index",[103],[190],{"type":59,"value":191},"HNSW config",{"type":53,"tag":84,"props":193,"children":194},{},[195,196,202,204],{"type":59,"value":157},{"type":53,"tag":90,"props":197,"children":199},{"className":198},[],[200],{"type":59,"value":201},"m",{"type":59,"value":203}," (16 default, 32 for high recall) ",{"type":53,"tag":99,"props":205,"children":207},{"href":187,"rel":206},[103],[208],{"type":59,"value":191},{"type":53,"tag":84,"props":210,"children":211},{},[212,214],{"type":59,"value":213},"Enable oversampling + rescore with quantization ",{"type":53,"tag":99,"props":215,"children":218},{"href":216,"rel":217},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F?s=searching-with-quantization",[103],[219],{"type":59,"value":220},"Search with quantization",{"type":53,"tag":84,"props":222,"children":223},{},[224,226],{"type":59,"value":225},"ACORN for filtered queries (v1.16+) ",{"type":53,"tag":99,"props":227,"children":230},{"href":228,"rel":229},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fsearch\u002Fsearch\u002F?s=acorn-search-algorithm",[103],[231],{"type":59,"value":232},"ACORN",{"type":53,"tag":62,"props":234,"children":235},{},[236,238],{"type":59,"value":237},"Binary quantization requires rescore. Without it, quality loss is severe. Use oversampling (3-5x minimum for binary) to recover recall. Always test quantization impact on your data before production. ",{"type":53,"tag":99,"props":239,"children":242},{"href":240,"rel":241},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F",[103],[243],{"type":59,"value":244},"Quantization",{"type":53,"tag":68,"props":246,"children":248},{"id":247},"wrong-embedding-model",[249],{"type":59,"value":250},"Wrong Embedding Model",{"type":53,"tag":62,"props":252,"children":253},{},[254],{"type":59,"value":255},"Use when: exact search also returns bad results.",{"type":53,"tag":62,"props":257,"children":258},{},[259,261],{"type":59,"value":260},"Test top 3 MTEB models on 100-1000 sample queries, measure recall@10. Domain-specific models often outperform general models. ",{"type":53,"tag":99,"props":262,"children":265},{"href":263,"rel":264},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Finference\u002F",[103],[266],{"type":59,"value":267},"Hosted inference",{"type":53,"tag":68,"props":269,"children":271},{"id":270},"unoptimized-search-pipeline",[272],{"type":59,"value":273},"Unoptimized Search Pipeline",{"type":53,"tag":62,"props":275,"children":276},{},[277],{"type":59,"value":278},"Use when: exact search also returns bad results and model choice is confirmed by user.",{"type":53,"tag":62,"props":280,"children":281},{},[282],{"type":59,"value":283},"Optimize search according to advanced search-strategies skill.",{"type":53,"tag":68,"props":285,"children":287},{"id":286},"what-not-to-do",[288],{"type":59,"value":289},"What NOT to Do",{"type":53,"tag":80,"props":291,"children":292},{},[293,298,303,315,320,325],{"type":53,"tag":84,"props":294,"children":295},{},[296],{"type":59,"value":297},"Tune Qdrant before verifying the model is right for the task (most quality issues are model issues)",{"type":53,"tag":84,"props":299,"children":300},{},[301],{"type":59,"value":302},"Use binary quantization without rescore (severe quality loss)",{"type":53,"tag":84,"props":304,"children":305},{},[306,308,313],{"type":59,"value":307},"Set ",{"type":53,"tag":90,"props":309,"children":311},{"className":310},[],[312],{"type":59,"value":163},{"type":59,"value":314}," lower than results requested (guaranteed bad recall)",{"type":53,"tag":84,"props":316,"children":317},{},[318],{"type":59,"value":319},"Skip payload indexes on filtered fields then blame quality (HNSW can't traverse filtered-out nodes, and filterable HNSW is built only if payload indexes were set up prior)",{"type":53,"tag":84,"props":321,"children":322},{},[323],{"type":59,"value":324},"Deploy without baseline recall or other search relevance metrics (no way to measure regressions)",{"type":53,"tag":84,"props":326,"children":327},{},[328],{"type":59,"value":329},"Confuse payload filtering with sparse vector search (different things, different config)",{"items":331,"total":494},[332,352,370,386,398,412,426,438,450,462,470,482],{"slug":333,"name":333,"fn":334,"description":335,"org":336,"tags":337,"stars":28,"repoUrl":29,"updatedAt":351},"qdrant-horizontal-scaling","guide Qdrant horizontal scaling decisions","Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[338,341,344,347,350],{"name":339,"slug":340,"type":15},"AI Infrastructure","ai-infrastructure",{"name":342,"slug":343,"type":15},"Architecture","architecture",{"name":345,"slug":346,"type":15},"Capacity Planning","capacity-planning",{"name":348,"slug":349,"type":15},"Database","database",{"name":17,"slug":18,"type":15},"2026-04-18T04:46:16.349561",{"slug":353,"name":353,"fn":354,"description":355,"org":356,"tags":357,"stars":28,"repoUrl":29,"updatedAt":369},"qdrant-indexing-performance-optimization","optimize Qdrant indexing performance","Diagnoses and fixes slow Qdrant indexing and data ingestion. Use when someone reports 'uploads are slow', 'indexing takes forever', 'optimizer is stuck', 'HNSW build time too long', or 'data uploaded but search is bad'. Also use when optimizer status shows errors, segments won't merge, or indexing threshold questions arise.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[358,361,362,365,368],{"name":359,"slug":360,"type":15},"Data Engineering","data-engineering",{"name":348,"slug":349,"type":15},{"name":363,"slug":364,"type":15},"ETL","etl",{"name":366,"slug":367,"type":15},"Performance","performance",{"name":17,"slug":18,"type":15},"2026-04-18T04:46:02.766357",{"slug":371,"name":371,"fn":372,"description":373,"org":374,"tags":375,"stars":28,"repoUrl":29,"updatedAt":385},"qdrant-memory-usage-optimization","optimize Qdrant memory usage","Diagnoses and reduces Qdrant memory usage. Use when someone reports 'memory too high', 'RAM keeps growing', 'node crashed', 'out of memory', 'memory leak', or asks 'why is memory usage so high?', 'how to reduce RAM?'. Also use when memory doesn't match calculations, quantization didn't help, or nodes crash during recovery.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[376,379,380,383,384],{"name":377,"slug":378,"type":15},"Cost Optimization","cost-optimization",{"name":348,"slug":349,"type":15},{"name":381,"slug":382,"type":15},"Observability","observability",{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:01.525023",{"slug":387,"name":387,"fn":388,"description":389,"org":390,"tags":391,"stars":28,"repoUrl":29,"updatedAt":397},"qdrant-minimize-latency","minimize Qdrant query latency","Guides Qdrant query latency optimization. Use when someone asks 'search is slow', 'how to reduce latency', 'p99 is too high', 'tail latency', 'single query too slow', 'how to make search faster', or 'latency spikes'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[392,393,394,395,396],{"name":342,"slug":343,"type":15},{"name":348,"slug":349,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-04-18T04:46:10.126667",{"slug":399,"name":399,"fn":400,"description":401,"org":402,"tags":403,"stars":28,"repoUrl":29,"updatedAt":411},"qdrant-monitoring-debugging","debug Qdrant production issues with metrics","Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[404,405,408,409,410],{"name":26,"slug":27,"type":15},{"name":406,"slug":407,"type":15},"Monitoring","monitoring",{"name":381,"slug":382,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:06.450784",{"slug":413,"name":413,"fn":414,"description":415,"org":416,"tags":417,"stars":28,"repoUrl":29,"updatedAt":425},"qdrant-monitoring-setup","set up Qdrant monitoring and alerting","Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up monitoring', 'Prometheus config', 'Grafana dashboard', 'health check endpoints', 'how to scrape Hybrid Cloud', 'what alerts to set', 'how to centralize logs', or 'audit logging'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[418,419,420,421,422],{"name":339,"slug":340,"type":15},{"name":406,"slug":407,"type":15},{"name":381,"slug":382,"type":15},{"name":17,"slug":18,"type":15},{"name":423,"slug":424,"type":15},"SRE","sre","2026-04-18T04:46:05.217192",{"slug":427,"name":427,"fn":428,"description":429,"org":430,"tags":431,"stars":28,"repoUrl":29,"updatedAt":437},"qdrant-scaling-data-volume","scale Qdrant data volume","Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[432,433,434,435,436],{"name":339,"slug":340,"type":15},{"name":342,"slug":343,"type":15},{"name":345,"slug":346,"type":15},{"name":348,"slug":349,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:07.684464",{"slug":439,"name":439,"fn":440,"description":441,"org":442,"tags":443,"stars":28,"repoUrl":29,"updatedAt":449},"qdrant-scaling-qps","scale Qdrant query throughput","Guides Qdrant query throughput (QPS) scaling. Use when someone asks 'how to increase QPS', 'need more throughput', 'queries per second too low', 'batch search', 'read replicas', or 'how to handle more concurrent queries'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[444,445,446,447,448],{"name":339,"slug":340,"type":15},{"name":342,"slug":343,"type":15},{"name":348,"slug":349,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:08.905219",{"slug":451,"name":451,"fn":452,"description":453,"org":454,"tags":455,"stars":28,"repoUrl":29,"updatedAt":461},"qdrant-scaling-query-volume","scale Qdrant query volume and pagination","Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[456,457,458,459,460],{"name":342,"slug":343,"type":15},{"name":348,"slug":349,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-04-18T04:46:11.371326",{"slug":4,"name":4,"fn":5,"description":6,"org":463,"tags":464,"stars":28,"repoUrl":29,"updatedAt":30},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[465,466,467,468,469],{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":26,"slug":27,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":471,"name":471,"fn":472,"description":473,"org":474,"tags":475,"stars":28,"repoUrl":29,"updatedAt":481},"qdrant-search-speed-optimization","optimize Qdrant search speed","Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[476,477,478,479,480],{"name":23,"slug":24,"type":15},{"name":348,"slug":349,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-04-18T04:46:03.987332",{"slug":483,"name":483,"fn":484,"description":485,"org":486,"tags":487,"stars":28,"repoUrl":29,"updatedAt":493},"qdrant-search-strategies","select optimal Qdrant search strategies","Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'BM25 or sparse vectors?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback', 'recommendation API', 'discovery API', 'ColBERT reranking', or 'missing keyword matches'",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[488,489,490,491,492],{"name":339,"slug":340,"type":15},{"name":23,"slug":24,"type":15},{"name":342,"slug":343,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-04-18T04:46:18.812306",45,{"items":496,"total":553},[497,505,513,521,529,537,545],{"slug":333,"name":333,"fn":334,"description":335,"org":498,"tags":499,"stars":28,"repoUrl":29,"updatedAt":351},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[500,501,502,503,504],{"name":339,"slug":340,"type":15},{"name":342,"slug":343,"type":15},{"name":345,"slug":346,"type":15},{"name":348,"slug":349,"type":15},{"name":17,"slug":18,"type":15},{"slug":353,"name":353,"fn":354,"description":355,"org":506,"tags":507,"stars":28,"repoUrl":29,"updatedAt":369},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[508,509,510,511,512],{"name":359,"slug":360,"type":15},{"name":348,"slug":349,"type":15},{"name":363,"slug":364,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"slug":371,"name":371,"fn":372,"description":373,"org":514,"tags":515,"stars":28,"repoUrl":29,"updatedAt":385},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[516,517,518,519,520],{"name":377,"slug":378,"type":15},{"name":348,"slug":349,"type":15},{"name":381,"slug":382,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"slug":387,"name":387,"fn":388,"description":389,"org":522,"tags":523,"stars":28,"repoUrl":29,"updatedAt":397},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[524,525,526,527,528],{"name":342,"slug":343,"type":15},{"name":348,"slug":349,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":399,"name":399,"fn":400,"description":401,"org":530,"tags":531,"stars":28,"repoUrl":29,"updatedAt":411},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[532,533,534,535,536],{"name":26,"slug":27,"type":15},{"name":406,"slug":407,"type":15},{"name":381,"slug":382,"type":15},{"name":366,"slug":367,"type":15},{"name":17,"slug":18,"type":15},{"slug":413,"name":413,"fn":414,"description":415,"org":538,"tags":539,"stars":28,"repoUrl":29,"updatedAt":425},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[540,541,542,543,544],{"name":339,"slug":340,"type":15},{"name":406,"slug":407,"type":15},{"name":381,"slug":382,"type":15},{"name":17,"slug":18,"type":15},{"name":423,"slug":424,"type":15},{"slug":427,"name":427,"fn":428,"description":429,"org":546,"tags":547,"stars":28,"repoUrl":29,"updatedAt":437},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[548,549,550,551,552],{"name":339,"slug":340,"type":15},{"name":342,"slug":343,"type":15},{"name":345,"slug":346,"type":15},{"name":348,"slug":349,"type":15},{"name":17,"slug":18,"type":15},15]