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2025)","https:\u002F\u002Fqwenlm.github.io\u002Fblog\u002Fqwen3-embedding\u002F",{"title":360,"url":361},"CoIR: a benchmark for code information retrieval (arXiv 2407.02883)","https:\u002F\u002Farxiv.org\u002Fabs\u002F2407.02883",{"title":363,"url":364},"CocoIndex blog: indexing a codebase","https:\u002F\u002Fcocoindex.io\u002Fblogs\u002Findex-codebase-v1","\u002Fimages\u002Fblog\u002Fcode-rag-repository-indexing\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fcode-rag-repository-indexing\u002Fog.jpg",[82,83,84],"RAG über Code: AST-Chunking, Repo-Maps und Code-Embeddings für Agenten","Wie Coding-Agenten Code finden: AST-Chunking mit tree-sitter, Repo-Maps, Merkle-Tree-Sync, Code-Embedding-Modelle 2026 und wann grep einen Index schlägt.","RAG über Code: Ein verzweigter Codebaum speist eine Reihe von 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Wo sie angenehm ist und wo die Suche an der Cloud-Grenze endet.","Chroma: Ein Schubladenschrank mit sortierten Murmeln, obenauf ein Kiesel mit Riss.",{"slug":495,"published":496,"minutes":497,"category":8,"tags":498,"tagPages":500,"keywords":501,"about":510,"sources":516,"cover":541,"og":542,"expertise":80,"locales":543,"lang":83,"title":544,"description":545,"coverAlt":546},"pinecone","2026-07-09",11,[13,10,11,499,441],"Namespaces",[17,16,8,444],[502,503,504,505,506,507,508,509],"pinecone vektordatenbank","pinecone preise","pinecone read units kosten","pinecone namespaces erklärt","pinecone vs qdrant vergleich","pinecone vs pgvector vergleich","pinecone documents api nutzen","serverless vektordatenbank kosten",[511,514,515],{"name":512,"url":513},"Vector database","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FVector_database",{"name":278,"url":279},{"name":114,"url":115},[517,520,523,526,529,532,535,538],{"title":518,"url":519},"Pinecone docs: Index data overview, indexes, namespaces and metadata","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Findex-data\u002Findexing-overview",{"title":521,"url":522},"Pinecone docs: Adopt the Documents API, API version 2026-07","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Findex-data\u002Fadopt-the-documents-api",{"title":524,"url":525},"Pinecone docs: Create an index, schemas, regions and metrics","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Findex-data\u002Fcreate-an-index",{"title":527,"url":528},"Pinecone docs: Understanding Pinecone cost, read units, write units and egress","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Forganizations\u002Fmanage-cost\u002Funderstanding-cost",{"title":530,"url":531},"Pinecone pricing: plans, limits and rates","https:\u002F\u002Fwww.pinecone.io\u002Fpricing\u002F",{"title":533,"url":534},"Pinecone docs: Semantic search","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Fsearch\u002Fsemantic-search",{"title":536,"url":537},"Pinecone docs: Local development with Pinecone Local","https:\u002F\u002Fdocs.pinecone.io\u002Fguides\u002Foperations\u002Flocal-development",{"title":539,"url":540},"Pinecone docs: 2026 release notes","https:\u002F\u002Fdocs.pinecone.io\u002Frelease-notes\u002F2026","\u002Fimages\u002Fblog\u002Fpinecone\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fpinecone\u002Fog.jpg",[82,83,84],"Pinecone: ein Test der verwalteten Vektordatenbank","Pinecone im Test: Read Units wachsen mit der Namespace-Größe, ein Schema ist nachträglich nicht änderbar, und wo eine eigene Vektordatenbank besser passt.","Pinecone: Ein Kiefernzapfen auf einer Wolke hält Murmeln zwischen den Schuppen, darunter ein Schlüssel.",1793451237700]