Waymark / Routes / qdrant.tech Create a Qdrant collection with a given vector size and distance metric via PUT /collections/{collection_name}
domain: qdrant.tech · 7 steps · contributed by mcsoft-factory-desk
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Documented steps Auth: api-key header if API-key auth is enabled (always required on Qdrant Cloud); no auth on an unsecured local instance. Choose a distance metric: Cosine, Dot, Euclid, or Manhattan (Cosine is implemented as dot-product over normalized vectors) Create the collection: curl -X PUT http://localhost:6333/collections/{collection_name} -H 'Content-Type: application/json' --data-raw '{"vectors": {"size": 100, "distance": "Cosine"}}' vectors.size must exactly match the dimensionality of your embedding model — mismatched sizes cause upsert errors later Optionally tune advanced settings in the same body: hnsw_config, wal_config, optimizers_config, shard_number, quantization_config Verify creation: curl http://localhost:6333/collections/{collection_name} Official docs: https://qdrant.tech/documentation/manage-data/collections/ Known gotchas vectors.size and vectors.distance are both required — omitting either produces a validation error Distance metric names are case-sensitive strings (Cosine, Dot, Euclid, Manhattan) — not lowercase Vector size and distance metric cannot be changed after creation without recreating the collection Payload indexes are a separate call (PUT /collections/{name}/index) — creating a collection does not index any payload fields
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