Shortcode for rendering code snippets from separate markdown files (#1548)

* shortcode for rendering code snippets from separate markdown files

* formatted code

* fix and readme

* semi-automatically extracts snippets from markdown

* extract snippets from points.md

* extract snippets from vectors.md

* extract snippets from payload.md

* extract snippets from search.md + fixes

* extract snippets from explore.md

* extract snippets from hybrid-queries.md + mode query by id into search

* extract snippets from filtering.md

* extract snippets from storage.md + update outdated info

* extract snippets from indexing.md

* extract snippets from snapshots.md

* extract snippets from guides/optimize.md

* extract snippets from guides/multiple-partitions.md + fix aside note

* extract snippets from guides/quantization.md

* use auto-generated descriptions

* order json snippets first

---------

Co-authored-by: generall <andrey@vasnetsov.com>

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/_description.md

@@ -0,0 +1 @@
+You can create a collection for high-speed search with low memory usage by configuring it to store original vectors on disk and quantized vectors in RAM. The quantization technique compresses vectors to `int8` using the scalar method, optimizing memory usage and minimizing disk reads for efficient search operations.

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/csharp.md

@@ -0,0 +1,15 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+var client = new QdrantClient("localhost", 6334);
+
+await client.CreateCollectionAsync(
+	collectionName: "{collection_name}",
+	vectorsConfig: new VectorParams { Size = 768, Distance = Distance.Cosine, OnDisk = true },
+	quantizationConfig: new QuantizationConfig
+	{
+		Scalar = new ScalarQuantization { Type = QuantizationType.Int8, AlwaysRam = true }
+	}
+);
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/go.md

@@ -0,0 +1,25 @@
+```go
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+client, err := qdrant.NewClient(&qdrant.Config{
+	Host: "localhost",
+	Port: 6334,
+})
+
+client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+	CollectionName: "{collection_name}",
+	VectorsConfig: qdrant.NewVectorsConfig(&qdrant.VectorParams{
+		Size:     768,
+		Distance: qdrant.Distance_Cosine,
+		OnDisk:   qdrant.PtrOf(true),
+	}),
+	QuantizationConfig: qdrant.NewQuantizationScalar(&qdrant.ScalarQuantization{
+		Type:      qdrant.QuantizationType_Int8,
+		AlwaysRam: qdrant.PtrOf(true),
+	}),
+})
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/http.md

@@ -0,0 +1,16 @@
+```http
+PUT /collections/{collection_name}
+{
+    "vectors": {
+        "size": 768,
+        "distance": "Cosine",
+        "on_disk": true
+    },
+    "quantization_config": {
+        "scalar": {
+            "type": "int8",
+            "always_ram": true
+        }
+    }
+}
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/java.md

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+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.CreateCollection;
+import io.qdrant.client.grpc.Collections.Distance;
+import io.qdrant.client.grpc.Collections.OptimizersConfigDiff;
+import io.qdrant.client.grpc.Collections.QuantizationConfig;
+import io.qdrant.client.grpc.Collections.QuantizationType;
+import io.qdrant.client.grpc.Collections.ScalarQuantization;
+import io.qdrant.client.grpc.Collections.VectorParams;
+import io.qdrant.client.grpc.Collections.VectorsConfig;
+
+QdrantClient client =
+    new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build());
+
+client
+    .createCollectionAsync(
+        CreateCollection.newBuilder()
+            .setCollectionName("{collection_name}")
+            .setVectorsConfig(
+                VectorsConfig.newBuilder()
+                    .setParams(
+                        VectorParams.newBuilder()
+                            .setSize(768)
+                            .setDistance(Distance.Cosine)
+                            .setOnDisk(true)
+                            .build())
+                    .build())
+            .setQuantizationConfig(
+                QuantizationConfig.newBuilder()
+                    .setScalar(
+                        ScalarQuantization.newBuilder()
+                            .setType(QuantizationType.Int8)
+                            .setAlwaysRam(true)
+                            .build())
+                    .build())
+            .build())
+    .get();
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/python.md

@@ -0,0 +1,16 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(url="http://localhost:6333")
+
+client.create_collection(
+    collection_name="{collection_name}",
+    vectors_config=models.VectorParams(size=768, distance=models.Distance.COSINE, on_disk=True),
+    quantization_config=models.ScalarQuantization(
+        scalar=models.ScalarQuantizationConfig(
+            type=models.ScalarType.INT8,
+            always_ram=True,
+        ),
+    ),
+)
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/rust.md

@@ -0,0 +1,21 @@
+```rust
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Distance, QuantizationType, ScalarQuantizationBuilder,
+    VectorParamsBuilder,
+};
+use qdrant_client::Qdrant;
+
+let client = Qdrant::from_url("http://localhost:6334").build()?;
+
+client
+    .create_collection(
+        CreateCollectionBuilder::new("{collection_name}")
+            .vectors_config(VectorParamsBuilder::new(768, Distance::Cosine))
+            .quantization_config(
+                ScalarQuantizationBuilder::default()
+                    .r#type(QuantizationType::Int8.into())
+                    .always_ram(true),
+            ),
+    )
+    .await?;
+```

qdrant-landing/content/documentation/headless/snippets/create-collection/scalar-quantization-in-ram/typescript.md

@@ -0,0 +1,19 @@
+```typescript
+import { QdrantClient } from "@qdrant/js-client-rest";
+
+const client = new QdrantClient({ host: "localhost", port: 6333 });
+
+client.createCollection("{collection_name}", {
+  vectors: {
+    size: 768,
+    distance: "Cosine",
+    on_disk: true,
+  },
+  quantization_config: {
+    scalar: {
+      type: "int8",
+      always_ram: true,
+    },
+  },
+});
+```