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.
This commit is contained in:
xzfc
2025-11-28 22:00:47 +00:00
parent cdfbd6538a
commit 00896acb28
2300 changed files with 22902 additions and 378 deletions
@@ -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 = "cohere/embed-v4.0",
Text = "a green square",
Options = { ["cohere-api-key"] = "<YOUR_COHERE_API_KEY>", ["output_dimension"] = 512 },
}
);
```
@@ -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{
Text: "a green square",
Model: "cohere/embed-v4.0",
Options: qdrant.NewValueMap(map[string]any{
"cohere-api-key": "<YOUR_COHERE_API_KEY>",
"output_dimension": 512,
}),
}),
),
})
```
@@ -0,0 +1,34 @@
```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("cohere/embed-v4.0")
.setText("a green square")
.putAllOptions(
Map.of(
"cohere-api-key",
value("<YOUR_COHERE_API_KEY>"),
"output_dimension",
value(512)))
.build()))
.build())
.get();
```
@@ -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="a green square",
model="cohere/embed-v4.0",
options={
"cohere-api-key": "<your_cohere_api_key>",
"output_dimension": 512
}
)
)
```
@@ -0,0 +1,25 @@
```rust
use qdrant_client::{
Qdrant, QdrantError,
qdrant::{Document, Query, QueryPointsBuilder, Value},
};
use std::collections::HashMap;
let client = Qdrant::from_url("http://localhost:6333").build().unwrap();
let mut options = HashMap::<String, Value>::new();
options.insert("cohere-api-key".to_string(), "<YOUR_COHERE_API_KEY>".into());
options.insert("output_dimension".to_string(), 512.into());
client
.query(
QueryPointsBuilder::new("{collection_name}")
.query(Query::new_nearest(Document {
text: "a green square".into(),
model: "cohere/embed-v4.0".into(),
options,
}))
.build(),
)
.await?;
```
@@ -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: 'a green square',
model: 'cohere/embed-v4.0',
options: {
'cohere-api-key': '<your_cohere_api_key>',
output_dimension: 512,
},
},
});
```