docs auto-sync

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
+
+
 ```

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(

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