diff --git a/qdrant-landing/content/documentation/configuration.md b/qdrant-landing/content/documentation/configuration.md index 3ee13a233..674b6d660 100644 --- a/qdrant-landing/content/documentation/configuration.md +++ b/qdrant-landing/content/documentation/configuration.md @@ -20,14 +20,13 @@ docker run -p 6333:6333 \ Example of the configuration file: ```yaml -debug: false -log_level: INFO - - storage: # Where to store all the data storage_path: ./storage + # Where to store snapshots + snapshots_path: ./snapshots + # If true - point's payload will not be stored in memory. # It will be read from the disk every time it is requested. # This setting saves RAM by (slightly) increasing the response time. @@ -71,12 +70,14 @@ storage: # If indexation speed have more priority for your - make this parameter lower. # If search speed is more important - make this parameter higher. # Note: 1Kb = 1 vector of size 256 - max_segment_size_kb: 200000 + # If not set, will be automatically selected considering the number of available CPUs. + max_segment_size_kb: null # Maximum size (in KiloBytes) of vectors to store in-memory per segment. # Segments larger than this threshold will be stored as read-only memmaped file. # To enable memmap storage, lower the threshold # Note: 1Kb = 1 vector of size 256 + # If not set, mmap will not be used. memmap_threshold_kb: null # Maximum size (in KiloBytes) of vectors allowed for plain index. @@ -85,12 +86,15 @@ storage: indexing_threshold_kb: 20000 # Interval between forced flushes. - flush_interval_sec: 1 + flush_interval_sec: 5 - # Max number of threads, which can be used for optimization. If 0 - `NUM_CPU - 1` will be used - max_optimization_threads: 0 + # Max number of threads, which can be used for optimization per collection. + # Note: Each optimization thread will also use `max_indexing_threads` for index building. + # So total number of threads used for optimization will be `max_optimization_threads * max_indexing_threads` + # If `max_optimization_threads = 0`, optimization will be disabled. + max_optimization_threads: 1 - # Default parameters of HNSW Index. Could be override for each collection individually + # Default parameters of HNSW Index. Could be overridden for each collection individually hnsw_index: # Number of edges per node in the index graph. Larger the value - more accurate the search, more space required. m: 16 @@ -101,6 +105,8 @@ storage: # in this case full-scan search should be preferred by query planner and additional indexing is not required. # Note: 1Kb = 1 vector of size 256 full_scan_threshold_kb: 10000 + # Number of parallel threads used for background index building. If 0 - auto selection. + max_indexing_threads: 0 service: @@ -119,7 +125,7 @@ service: # gRPC port to bind the service on. # If `null` - gRPC is disabled. Default: null - grpc_port: null + grpc_port: 6334 # Uncomment to enable gRPC: # grpc_port: 6334 @@ -131,7 +137,7 @@ service: cluster: # Use `enabled: true` to run Qdrant in distributed deployment mode - enabled: true + enabled: false # Configuration of the inter-cluster communication p2p: @@ -146,4 +152,6 @@ cluster: # tick period may create significant network and CPU overhead. # We encourage you NOT to change this parameter unless you know what you are doing. tick_period_ms: 100 + + ``` diff --git a/qdrant-landing/content/documentation/quick_start.md b/qdrant-landing/content/documentation/quick_start.md index b588c59bf..4a9834410 100644 --- a/qdrant-landing/content/documentation/quick_start.md +++ b/qdrant-landing/content/documentation/quick_start.md @@ -81,6 +81,7 @@ curl -X PUT 'http://localhost:6333/collections/test_collection' \ ```python from qdrant_client import QdrantClient +from qdrant_client.http.models import Distance, VectorParams client = QdrantClient(host="localhost", port=6333) client.recreate_collection( diff --git a/qdrant-landing/content/documentation/search.md b/qdrant-landing/content/documentation/search.md index 1fd137285..aac422d2b 100644 --- a/qdrant-landing/content/documentation/search.md +++ b/qdrant-landing/content/documentation/search.md @@ -179,7 +179,7 @@ It will exclude all results with a score worse than the given. ### Payload and vector in the result By default, retrieval methods do not return any stored information. -Additional parameters `with_vector` and `with_payload` could alter this behavior. +Additional parameters `with_vectors` and `with_payload` could alter this behavior. Example: @@ -188,7 +188,7 @@ POST /collections/{collection_name}/points/search { "vector": [0.2, 0.1, 0.9, 0.7], - "with_vector": true, + "with_vectors": true, "with_payload": true } ``` @@ -197,7 +197,7 @@ POST /collections/{collection_name}/points/search client.search( collection_name="{collection_name}", query_vector=[0.2, 0.1, 0.9, 0.7], - with_vector=True, + with_vectors=True, with_payload=True, ) ``` @@ -560,7 +560,7 @@ POST /collections/{collection_name}/points/search { "vector": [0.2, 0.1, 0.9, 0.7], - "with_vector": true, + "with_vectors": true, "with_payload": true, "limit": 10, "offset": 100 @@ -575,7 +575,7 @@ client = QdrantClient(host="localhost", port=6333) client.search( collection_name="{collection_name}", query_vector=[0.2, 0.1, 0.9, 0.7], - with_vector=True, + with_vectors=True, with_payload=True, limit=10, offset=100