feat: add hybrid search example in Rust (#2579)

Hello!

I'm new to lancedb and interested in the Rust SDK.
I couldn't find a good hybrid search example in Rust, so I created one.

## Usage

```bash
$ cargo run --quiet --example hybrid_search --features=sentence-transformers
Result: Python is a popular programming language.
Result: Mount Everest is the highest mountain in the world.
Result: The first computer programmer was Ada Lovelace.
Result: Coffee is one of the most popular beverages in the world.
Result: Basketball is a sport played with a ball and a hoop.
```

rust/lancedb/Cargo.toml

@@ -65,7 +65,11 @@ http = { version = "1", optional = true } # Matching what is in reqwest
 uuid = { version = "1.7.0", features = ["v4"], optional = true }
 polars-arrow = { version = ">=0.37,<0.40.0", optional = true }
 polars = { version = ">=0.37,<0.40.0", optional = true }
-hf-hub = { version = "0.4.1", optional = true, default-features = false, features = ["rustls-tls", "tokio", "ureq"]}
+hf-hub = { version = "0.4.1", optional = true, default-features = false, features = [
+    "rustls-tls",
+    "tokio",
+    "ureq",
+] }
 candle-core = { version = "0.9.1", optional = true }
 candle-transformers = { version = "0.9.1", optional = true }
 candle-nn = { version = "0.9.1", optional = true }
@@ -119,3 +123,7 @@ required-features = ["sentence-transformers"]
 [[example]]
 name = "bedrock"
 required-features = ["bedrock"]
+
+[[example]]
+name = "hybrid_search"
+required-features = ["sentence-transformers"]

rust/lancedb/examples/hybrid_search.rs

@@ -0,0 +1,116 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+use arrow_array::{RecordBatch, RecordBatchIterator, StringArray};
+use arrow_schema::{DataType, Field, Schema};
+use futures::TryStreamExt;
+use lance_index::scalar::FullTextSearchQuery;
+use lancedb::index::scalar::FtsIndexBuilder;
+use lancedb::index::Index;
+use lancedb::{
+    arrow::IntoArrow,
+    connect,
+    embeddings::{
+        sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
+        EmbeddingFunction,
+    },
+    query::{QueryBase, QueryExecutionOptions},
+    Result, Table,
+};
+use std::{iter::once, sync::Arc};
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    let tempdir = tempfile::tempdir().unwrap();
+    let tempdir = tempdir.path().to_str().unwrap();
+    let embedding = SentenceTransformersEmbeddings::builder().build()?;
+    let embedding = Arc::new(embedding);
+    let db = connect(tempdir).execute().await?;
+    db.embedding_registry()
+        .register("sentence-transformers", embedding.clone())?;
+
+    // Create the table with embeddings
+    let table = db
+        .create_table("vectors", make_data())
+        .add_embedding(EmbeddingDefinition::new(
+            "facts",
+            "sentence-transformers",
+            Some("embeddings"),
+        ))?
+        .execute()
+        .await?;
+
+    // Create the FTS index
+    create_index(&table).await?;
+
+    // Perform a hybrid search using the FTS index and embeddings
+    let query_str = "world records";
+    let query = Arc::new(StringArray::from_iter_values(once(query_str)));
+    let query_vector = embedding.compute_query_embeddings(query)?;
+    let mut results = table
+        .query()
+        .full_text_search(FullTextSearchQuery::new(query_str.to_owned()))
+        .nearest_to(query_vector)?
+        .limit(5)
+        .execute_hybrid(QueryExecutionOptions::default())
+        .await?;
+
+    while let Some(batch) = results.try_next().await? {
+        let out = batch
+            .column_by_name("facts")
+            .unwrap()
+            .as_any()
+            .downcast_ref::<StringArray>()
+            .unwrap();
+        for text in out.iter() {
+            if let Some(text) = text {
+                println!("Result: {}", text);
+            }
+        }
+    }
+
+    Ok(())
+}
+
+fn make_data() -> impl IntoArrow {
+    let schema = Schema::new(vec![Field::new("facts", DataType::Utf8, false)]);
+
+    let facts = StringArray::from_iter_values(vec![
+        "Albert Einstein was a theoretical physicist.",
+        "The capital of France is Paris.",
+        "The Great Wall of China is one of the Seven Wonders of the World.",
+        "Python is a popular programming language.",
+        "Mount Everest is the highest mountain in the world.",
+        "Leonardo da Vinci painted the Mona Lisa.",
+        "Shakespeare wrote Hamlet.",
+        "The human body has 206 bones.",
+        "The speed of light is approximately 299,792 kilometers per second.",
+        "Water boils at 100 degrees Celsius.",
+        "The Earth orbits the Sun.",
+        "The Pyramids of Giza are located in Egypt.",
+        "Coffee is one of the most popular beverages in the world.",
+        "Tokyo is the capital city of Japan.",
+        "Photosynthesis is the process by which plants make their food.",
+        "The Pacific Ocean is the largest ocean on Earth.",
+        "Mozart was a prolific composer of classical music.",
+        "The Internet is a global network of computers.",
+        "Basketball is a sport played with a ball and a hoop.",
+        "The first computer virus was created in 1983.",
+        "Artificial neural networks are inspired by the human brain.",
+        "Deep learning is a subset of machine learning.",
+        "IBM's Watson won Jeopardy! in 2011.",
+        "The first computer programmer was Ada Lovelace.",
+        "The first chatbot was ELIZA, created in the 1960s.",
+    ]);
+    let schema = Arc::new(schema);
+    let rb = RecordBatch::try_new(schema.clone(), vec![Arc::new(facts)]).unwrap();
+    Box::new(RecordBatchIterator::new(vec![Ok(rb)], schema))
+}
+
+async fn create_index(table: &Table) -> Result<()> {
+    table
+        .create_index(&["facts"], Index::FTS(FtsIndexBuilder::default()))
+        .execute()
+        .await?;
+    Ok(())
+}