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-query/generated/csharp.md

@@ -0,0 +1,21 @@
+```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.QueryAsync(
+    collectionName: "{collection_name}",
+    query: new Document()
+    {
+        Model = "openai/text-embedding-3-large",
+        Text = "How to bake cookies?",
+        Options = { ["openai-api-key"] = "<YOUR_OPENAI_API_KEY>", ["dimensions"] = 512 },
+    }
+);
+```

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

@@ -0,0 +1,29 @@
+```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.Query(ctx, &qdrant.QueryPoints{
+	CollectionName: "{collection_name}",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{
+			Model: "openai/text-embedding-3-large",
+			Text:  "How to bake cookies?",
+			Options: qdrant.NewValueMap(map[string]any{
+				"openai-api-key": "<YOUR_OPENAI_API_KEY>",
+				"dimensions":     512,
+			}),
+		}),
+	),
+})
+```

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

@@ -0,0 +1,33 @@
+```java
+import static io.qdrant.client.QueryFactory.nearest;
+import static io.qdrant.client.ValueFactory.value;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Points.Document;
+import java.util.Map;
+
+QdrantClient client =
+    new QdrantClient(
+        QdrantGrpcClient.newBuilder("xyz-example.qdrant.io", 6334, true)
+            .withApiKey("<your-api-key")
+            .build());
+client
+    .queryAsync(
+        Points.QueryPoints.newBuilder()
+            .setCollectionName("{collection_name}")
+            .setQuery(
+                nearest(
+                    Document.newBuilder()
+                        .setModel("openai/text-embedding-3-large")
+                        .setText("How to bake 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-query/generated/python.md

@@ -0,0 +1,21 @@
+```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.query_points(
+    collection_name="{collection_name}",
+    query=models.Document(
+        text="How to bake 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-query/generated/rust.md

@@ -0,0 +1,25 @@
+```rust
+use qdrant_client::{
+    Qdrant, QdrantError,
+    qdrant::{Document, Query, QueryPointsBuilder, Value},
+};
+use std::collections::HashMap;
+
+let client = Qdrant::from_url("<your-qdrant-url>").build().unwrap();
+
+let mut options = HashMap::<String, Value>::new();
+options.insert("openai-api-key".to_string(), "<YOUR_OPENAI_API_KEY>".into());
+options.insert("dimensions".to_string(), 512.into());
+
+client
+    .query(
+        QueryPointsBuilder::new("{collection_name}")
+            .query(Query::new_nearest(Document {
+                text: "How to bake cookies?".into(),
+                model: "openai/text-embedding-3-large".into(),
+                options,
+            }))
+            .build(),
+    )
+    .await?;
+```

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

@@ -0,0 +1,16 @@
+```typescript
+import { QdrantClient } from "@qdrant/js-client-rest";
+
+const client = new QdrantClient({ host: "localhost", port: 6333 });
+
+client.query("{collection_name}", {
+    query: {
+        text: 'How to bake cookies?',
+        model: 'openai/text-embedding-3-large',
+        options: {
+            'openai-api-key': '<your_openai_api_key>',
+            dimensions: 512,
+        },
+    },
+});
+```