Add rerank

README.md

@@ -487,7 +487,7 @@ UpdateResponse updateResponse = index.update("v1", values, "example-namespace");
 
 # Collections
 
-Collections fall under data plane operations.
+Collections fall under control plane operations.
 
 ## Create collection
 
@@ -545,8 +545,8 @@ Pinecone pinecone = new Pinecone.Builder("PINECONE_API_KEY").build();
 pinecone.deleteCollection("example-collection");
 ```
 
-## Inference
-
+# Inference
+## Embed
 The Pinecone SDK now supports creating embeddings via the [Inference API](https://docs.pinecone.io/guides/inference/understanding-inference).
 
 ```java
@@ -583,6 +583,66 @@ EmbeddingsList embeddings = inference.embed(embeddingModel, parameters, inputs);
 List<Embedding> embeddedData = embeddings.getData();
 ```
 
+## Rerank
+The following example shows how to rerank items according to their relevance to a query.
+
+```java
+import io.pinecone.clients.Inference;
+import io.pinecone.clients.Pinecone;
+import org.openapitools.inference.client.model.RerankResult;
+
+import java.util.*;
+
+...
+
+// The model to use for reranking
+String model = "bge-reranker-v2-m3";
+
+// The query to rerank documents against
+String query = "The tech company Apple is known for its innovative products like the iPhone.";
+
+// Add the documents to rerank
+List<Map<String, String>> documents = new ArrayList<>();
+Map<String, String> doc1 = new HashMap<>();
+doc1.put("id", "vec1");
+doc1.put("my_field", "Apple is a popular fruit known for its sweetness and crisp texture.");
+documents.add(doc1);
+
+Map<String, String> doc2 = new HashMap<>();
+doc2.put("id", "vec2");
+doc2.put("my_field", "Many people enjoy eating apples as a healthy snack.");
+documents.add(doc2);
+
+Map<String, String> doc3 = new HashMap<>();
+doc3.put("id", "vec3");
+doc3.put("my_field", "Apple Inc. has revolutionized the tech industry with its sleek designs and user-friendly interfaces.");
+documents.add(doc3);
+
+Map<String, String> doc4 = new HashMap<>();
+doc4.put("id", "vec4");
+doc4.put("my_field", "An apple a day keeps the doctor away, as the saying goes.");
+documents.add(doc4);
+
+// The fields to rank the documents by. If not provided, the default is "text"
+List<String> rankFields = Arrays.asList("my_field");
+
+// The number of results to return sorted by relevance. Defaults to the number of inputs
+int topN = 2;
+
+// Whether to return the documents in the response
+boolean returnDocuments = true;
+
+// Additional model-specific parameters for the reranker
+Map<String, Object> parameters = new HashMap<>();
+parameters.put("truncate", "END");
+
+// Send ranking request
+RerankResult result = inference.rerank(model, query, documents, rankFields, topN, returnDocuments, parameters);
+
+// Get ranked data
+System.out.println(result.getData());
+```
+
 ## Examples
 
 - The data and control plane operation examples can be found in `io/pinecone/integration` folder.

src/integration/java/io/pinecone/integration/inference/RerankTest.java

@@ -0,0 +1,95 @@
+package io.pinecone.integration.inference;
+
+import io.pinecone.clients.Inference;
+import io.pinecone.clients.Pinecone;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.Test;
+import org.openapitools.inference.client.ApiException;
+import org.openapitools.inference.client.model.RerankResult;
+
+import java.util.*;
+
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+
+public class RerankTest {
+    private static final Pinecone pinecone = new Pinecone
+            .Builder(System.getenv("PINECONE_API_KEY"))
+            .withSourceTag("pinecone_test")
+            .build();
+    private static final Inference inference = pinecone.getInferenceClient();
+
+    @Test
+    public void testRerank() throws ApiException {
+        String model = "bge-reranker-v2-m3";
+        String query = "The tech company Apple is known for its innovative products like the iPhone.";
+        List<Map<String, String>> documents = new ArrayList<>();
+
+        Map<String, String> doc1 = new HashMap<>();
+        doc1.put("id", "vec1");
+        doc1.put("my_field", "Apple is a popular fruit known for its sweetness and crisp texture.");
+        documents.add(doc1);
+
+        Map<String, String> doc2 = new HashMap<>();
+        doc2.put("id", "vec2");
+        doc2.put("my_field", "Many people enjoy eating apples as a healthy snack.");
+        documents.add(doc2);
+
+        Map<String, String> doc3 = new HashMap<>();
+        doc3.put("id", "vec3");
+        doc3.put("my_field", "Apple Inc. has revolutionized the tech industry with its sleek designs and user-friendly interfaces.");
+        documents.add(doc3);
+
+        Map<String, String> doc4 = new HashMap<>();
+        doc4.put("id", "vec4");
+        doc4.put("my_field", "An apple a day keeps the doctor away, as the saying goes.");
+        documents.add(doc4);
+
+        List<String> rankFields = Arrays.asList("my_field");
+        int topN = 2;
+        boolean returnDocuments = true;
+        Map<String, Object> parameters = new HashMap<>();
+        parameters.put("truncate", "END");
+
+        RerankResult result = inference.rerank(model, query, documents, rankFields, topN, returnDocuments, parameters);
+
+        assertNotNull(result);
+        Assertions.assertEquals(result.getData().size(), topN);
+        Assertions.assertEquals(result.getData().get(0).getIndex(), 2);
+        Assertions.assertEquals(result.getData().get(0).getDocument().get("my_field"), doc3.get("my_field"));
+        Assertions.assertEquals(result.getData().size(), 2);
+    }
+
+    @Test
+    public void testRerankWithRequiredParameters() throws ApiException {
+        String model = "bge-reranker-v2-m3";
+        String query = "The tech company Apple is known for its innovative products like the iPhone.";
+        List<Map<String, String>> documents = new ArrayList<>();
+
+        Map<String, String> doc1 = new HashMap<>();
+        doc1.put("id", "vec1");
+        doc1.put("text", "Apple is a popular fruit known for its sweetness and crisp texture.");
+        documents.add(doc1);
+
+        Map<String, String> doc2 = new HashMap<>();
+        doc2.put("id", "vec2");
+        doc2.put("text", "Many people enjoy eating apples as a healthy snack.");
+        documents.add(doc2);
+
+        Map<String, String> doc3 = new HashMap<>();
+        doc3.put("id", "vec3");
+        doc3.put("text", "Apple Inc. has revolutionized the tech industry with its sleek designs and user-friendly interfaces.");
+        documents.add(doc3);
+
+        Map<String, String> doc4 = new HashMap<>();
+        doc4.put("id", "vec4");
+        doc4.put("text", "An apple a day keeps the doctor away, as the saying goes.");
+        documents.add(doc4);
+
+        RerankResult result = inference.rerank(model, query, documents);
+
+        assertNotNull(result);
+        Assertions.assertEquals(result.getData().size(), documents.size());
+        Assertions.assertEquals(result.getData().get(0).getIndex(), 2);
+        Assertions.assertEquals(result.getData().get(0).getDocument().get("text"), doc3.get("text"));
+    }
+}

src/main/java/io/pinecone/clients/Inference.java

@@ -60,6 +60,65 @@ public EmbeddingsList embed(String model, Map<String, Object> parameters, List<S
         return inferenceApi.embed(embedRequest);
     }
 
+    /**
+     * Reranks a list of documents based on the relevance to a query using the specified model. Since rest of the
+     * parameters are optional, they are set to their default values.
+     *
+     * @param model      The model to be used for reranking the documents.
+     * @param query      The query string to rank the documents against.
+     * @param documents  A list of maps representing the documents to be ranked.
+     *                   Each map should contain document attributes, such as "text".
+     *
+     * @return RerankResult containing the ranked documents and their scores.
+     * @throws ApiException If the API call fails, an ApiException is thrown.
+     */
+    public RerankResult rerank(String model,
+                               String query,
+                               List<Map<String, String>> documents) throws ApiException {
+        return rerank(model,
+                query,
+                documents,
+                Arrays.asList("text"),
+                documents.size(),
+                true,
+                new HashMap<>());
+    }
+
+    /**
+     * Reranks a list of documents based on the relevance to a query using the specified model with additional options.
+     *
+     * @param model            The model to be used for reranking the documents.
+     * @param query            The query string to rank the documents against.
+     * @param documents        A list of maps representing the documents to be ranked.
+     *                         Each map should contain document attributes, such as "text".
+     * @param rankFields       A list of fields in the documents to be used for ranking, typically "text".
+     * @param topN             The number of top-ranked documents to return.
+     * @param returnDocuments  Whether to return the documents along with the ranking scores.
+     * @param parameters       A map containing additional model-specific parameters for reranking.
+     * @return RerankResult containing the ranked documents and their scores.
+     * @throws ApiException If the API call fails, an ApiException is thrown.
+     */
+    public RerankResult rerank(String model,
+                               String query,
+                               List<Map<String, String>> documents,
+                               List<String> rankFields,
+                               int topN,
+                               boolean returnDocuments,
+                               Map<String, Object> parameters) throws ApiException {
+        RerankRequest rerankRequest = new RerankRequest();
+
+        rerankRequest
+                .model(model)
+                .query(query)
+                .documents(documents)
+                .rankFields(rankFields)
+                .topN(topN)
+                .returnDocuments(returnDocuments)
+                .putAdditionalProperty("parameters", parameters);
+
+        return inferenceApi.rerank(rerankRequest);
+    }
+
     /**
      * Converts a list of input strings to EmbedRequestInputsInner objects.
      *