Automated snippet conversion by scripts

These changes are purely mechanical to differentiate them from manual
fixes/adjustments made in the next commit.
This results in broken code as some snippets contain errors.

Made in four steps:
1. Run ./migrate-snippet.py that converts `.md` files to code files
   and perhaps adds missing lines under `// @hide` comments.
2. Sort Java imports.
3. Remove old `.md` files.
4. Run ./generate.md to produce `*/generated/*.md` files.

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/csharp.md

@@ -0,0 +1,24 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+var client = new QdrantClient(
+host: "xyz-example.qdrant.io", port: 6334, https: true, apiKey: "<your-api-key>");
+
+await client.UpsertAsync(
+    collectionName: "{collection_name}",
+    points: new List<PointStruct>
+    {
+        new()
+        {
+            Id = 1,
+            Vectors = new Document()
+            {
+                Model = "openai/text-embedding-3-large",
+                Text = "Recipe for baking chocolate chip cookies",
+                Options = { ["openai-api-key"] = "<YOUR_OPENAI_API_KEY>", ["dimensions"] = 512 },
+            },
+        },
+    }
+);
+```

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/go.md

@@ -0,0 +1,32 @@
+```go
+import (
+	"context"
+	"time"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+client, err := qdrant.NewClient(&qdrant.Config{
+	Host:   "xyz-example.qdrant.io",
+	Port:   6334,
+	APIKey: "<paste-your-api-key-here>",
+	UseTLS: true,
+})
+
+client.Upsert(ctx, &qdrant.UpsertPoints{
+	CollectionName: "{collection_name}",
+	Points: []*qdrant.PointStruct{
+		{
+			Id: qdrant.NewIDNum(uint64(1)),
+			Vectors: qdrant.NewVectorsDocument(&qdrant.Document{
+				Model: "openai/text-embedding-3-large",
+				Text:  "Recipe for baking chocolate chip cookies",
+				Options: qdrant.NewValueMap(map[string]any{
+					"openai-api-key": "<YOUR_OPENAI_API_KEY>",
+					"dimensions":     512,
+				}),
+			}),
+		},
+	},
+})
+```

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/java.md

@@ -0,0 +1,39 @@
+```java
+import static io.qdrant.client.PointIdFactory.id;
+import static io.qdrant.client.ValueFactory.value;
+import static io.qdrant.client.VectorsFactory.vectors;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Points.Document;
+import io.qdrant.client.grpc.Points.PointStruct;
+import java.util.List;
+import java.util.Map;
+
+QdrantClient client =
+    new QdrantClient(
+        QdrantGrpcClient.newBuilder("xyz-example.qdrant.io", 6334, true)
+            .withApiKey("<your-api-key")
+            .build());
+
+client
+    .upsertAsync(
+        "{collection_name}",
+        List.of(
+            PointStruct.newBuilder()
+                .setId(id(1))
+                .setVectors(
+                    vectors(
+                        Document.newBuilder()
+                            .setModel("openai/text-embedding-3-large")
+                            .setText("Recipe for baking chocolate chip cookies")
+                            .putAllOptions(
+                                Map.of(
+                                    "openai-api-key",
+                                    value("<YOUR_OPENAI_API_KEY>"),
+                                    "dimensions",
+                                    value(512)))
+                            .build()))
+                .build()))
+    .get();
+```

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/python.md

@@ -0,0 +1,26 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333", 
+    api_key="<your-api-key>", 
+    cloud_inference=True
+)
+
+client.upsert(
+    collection_name="{collection_name}",
+    points=[
+        models.PointStruct(
+            id=1,
+            vector=models.Document(
+                text="Recipe for baking chocolate chip cookies",
+                model="openai/text-embedding-3-large",
+                options={
+                    "openai-api-key": "<your_openai_api_key>",
+                    "dimensions": 512
+                }
+            )
+        )
+    ]
+)
+```

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/rust.md

@@ -0,0 +1,25 @@
+```rust
+use qdrant_client::{
+    Payload, Qdrant, QdrantError,
+    qdrant::{Document, PointStruct, UpsertPointsBuilder},
+};
+use std::collections::HashMap;
+
+let client = Qdrant::from_url("<your-qdrant-url>").build()?;
+let mut options = HashMap::new();
+options.insert("openai-api-key".to_string(), "<YOUR_OPENAI_API_KEY>".into());
+options.insert("dimensions".to_string(), 512.into());
+
+client
+    .upsert_points(UpsertPointsBuilder::new("{collection_name}",
+        vec![
+            PointStruct::new(1,
+                Document {
+                  text: "Recipe for baking chocolate chip cookies".into(),
+                  model: "openai/text-embedding-3-large".into(),
+                  options,
+                  },
+                Payload::default())
+            ]).wait(true))
+        .await?;
+```

qdrant-landing/content/documentation/headless/snippets/inference/openai-upsert/generated/typescript.md

@@ -0,0 +1,21 @@
+```typescript
+import { QdrantClient } from "@qdrant/js-client-rest";
+
+const client = new QdrantClient({ host: "localhost", port: 6333 });
+
+client.upsert("{collection_name}", {
+    points: [
+        {
+            id: 1,
+            vector: {
+                text: 'Recipe for baking chocolate chip cookies',
+                model: 'openai/text-embedding-3-large',
+                options: {
+                    'openai-api-key': '<your_openai_api_key>',
+                    dimensions: 512,
+                },
+            },
+        },
+    ],
+});
+```