Add instance_id param to chat completions

src/main/java/io/github/stefanbratanov/jvm/openai/CreateChatCompletionRequest.java

@@ -9,6 +9,7 @@ public record CreateChatCompletionRequest(
     String model,
     List<ChatMessage> messages,
     Optional<Double> frequencyPenalty,
+    Optional<String> instanceId,
     Optional<Map<Integer, Integer>> logitBias,
     Optional<Boolean> logprobs,
     Optional<Integer> topLogprobs,
@@ -48,6 +49,7 @@ public static class Builder {
     private final List<ChatMessage> messages = new LinkedList<>();
 
     private Optional<Double> frequencyPenalty = Optional.empty();
+    private Optional<String> instanceId = Optional.empty();
     private Optional<Map<Integer, Integer>> logitBias = Optional.empty();
     private Optional<Boolean> logprobs = Optional.empty();
     private Optional<Integer> topLogprobs = Optional.empty();
@@ -102,6 +104,15 @@ public Builder frequencyPenalty(double frequencyPenalty) {
       return this;
     }
 
+    /**
+     * @param instanceId A unique identifier to a custom instance to execute the request. The
+     *     requesting organization is required to have access to the instance.
+     */
+    public Builder instanceId(String instanceId) {
+      this.instanceId = Optional.of(instanceId);
+      return this;
+    }
+
     /**
      * @param logitBias A map that maps tokens (specified by their token ID in the tokenizer) to an
      *     associated bias value from -100 to 100. Mathematically, the bias is added to the logits
@@ -305,6 +316,7 @@ public CreateChatCompletionRequest build() {
           model,
           List.copyOf(messages),
           frequencyPenalty,
+          instanceId,
           logitBias,
           logprobs,
           topLogprobs,

src/test/java/io/github/stefanbratanov/jvm/openai/TestDataUtil.java

@@ -35,6 +35,7 @@ public CreateChatCompletionRequest randomCreateChatCompletionRequest() {
             .model(randomModel())
             .messages(listOf(randomInt(1, 3), this::randomChatMessage))
             .frequencyPenalty(randomDouble(-2.0, 2.0))
+            .instanceId(randomString(7))
             .logitBias(randomLogitBias(randomInt(0, 6)))
             .logprobs(randomBoolean())
             .topLogprobs(randomInt(0, 5))