Add maxTokens as prompt parameters

prompt/prompt-executor/prompt-executor-clients/prompt-executor-anthropic-client/src/commonMain/kotlin/ai/koog/prompt/executor/clients/anthropic/AnthropicLLMClient.kt

@@ -282,7 +282,7 @@
             model = settings.modelVersionsMap[model]
                 ?: throw IllegalArgumentException("Unsupported model: $model"),
             messages = messages,
-            maxTokens = 2048, // This is required by the API
+            maxTokens = prompt.params.maxTokens ?: AnthropicMessageRequest.MAX_TOKENS_DEFAULT,
             temperature = prompt.params.temperature,
             system = systemMessage,
             tools = if (tools.isNotEmpty()) anthropicTools else emptyList(), // Always provide a list for tools
@@ -467,7 +467,7 @@
      * @return This method does not return a value as it always throws an exception.
      * @throws UnsupportedOperationException Always thrown, as moderation is not supported by the Anthropic API.
      */
     public override suspend fun moderate(prompt: Prompt, model: LLModel): ModerationResult {
         logger.warn { "Moderation is not supported by Anthropic API" }
         throw UnsupportedOperationException("Moderation is not supported by Anthropic API.")
     }

prompt/prompt-executor/prompt-executor-clients/prompt-executor-anthropic-client/src/commonMain/kotlin/ai/koog/prompt/executor/clients/anthropic/DataModel.kt

@@ -27,13 +27,30 @@ import kotlinx.serialization.json.JsonObject
 public data class AnthropicMessageRequest(
     val model: String,
     val messages: List<AnthropicMessage>,
-    val maxTokens: Int = 2048,
+    val maxTokens: Int = MAX_TOKENS_DEFAULT,
     val temperature: Double? = null,
     val system: List<SystemAnthropicMessage>? = null,
     val tools: List<AnthropicTool>? = null,
     val stream: Boolean = false,
     val toolChoice: AnthropicToolChoice? = null,
-)
+) {
+    init {
+        require(maxTokens > 0) { "maxTokens must be greater than 0, but was $maxTokens" }
+        if (temperature != null) {
+            require(temperature >= 0) { "temperature must be greater than 0, but was $temperature" }
+        }
+    }
+
+    /**
+     * Companion object with default values for request
+     */
+    public companion object {
+        /**
+         * Default max tokens
+         */
+        public const val MAX_TOKENS_DEFAULT: Int = 2048
+    }
+}
 
 /**
  * Represents a message within the Anthropic LLM system. This data class encapsulates

prompt/prompt-executor/prompt-executor-clients/prompt-executor-anthropic-client/src/jvmTest/kotlin/ai/koog/prompt/executor/clients/anthropic/AnthropicModelsTest.kt

@@ -3,6 +3,8 @@ package ai.koog.prompt.executor.clients.anthropic
 import ai.koog.prompt.executor.clients.list
 import ai.koog.prompt.llm.LLMProvider
 import kotlin.test.Test
+import kotlin.test.assertEquals
+import kotlin.test.assertFailsWith
 import kotlin.test.assertSame
 
 class AnthropicModelsTest {
@@ -19,4 +21,38 @@ class AnthropicModelsTest {
             )
         }
     }
+
+    @Test
+    fun `AnthropicMessageRequest should use custom maxTokens when provided`() {
+        val customMaxTokens = 4000
+        val request = AnthropicMessageRequest(
+            model = AnthropicModels.Opus_3.id,
+            messages = emptyList(),
+            maxTokens = customMaxTokens
+        )
+
+        assertEquals(customMaxTokens, request.maxTokens)
+    }
+
+    @Test
+    fun `AnthropicMessageRequest should use default maxTokens when not provided`() {
+        val request = AnthropicMessageRequest(
+            model = AnthropicModels.Opus_3.id,
+            messages = emptyList()
+        )
+
+        assertEquals(AnthropicMessageRequest.MAX_TOKENS_DEFAULT, request.maxTokens)
+    }
+
+    @Test
+    fun `AnthropicMessageRequest should reject zero maxTokens`() {
+        val exception = assertFailsWith<IllegalArgumentException> {
+            AnthropicMessageRequest(
+                model = AnthropicModels.Opus_3.id,
+                messages = emptyList(),
+                maxTokens = 0
+            )
+        }
+        assertEquals("maxTokens must be greater than 0, but was 0", exception.message)
+    }
 }

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmMain/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/ai21/BedrockAI21JambaSerialization.kt

@@ -123,7 +123,7 @@
         return JambaRequest(
             model = model.id,
             messages = messages,
-            maxTokens = 4096,
+            maxTokens = JambaRequest.MAX_TOKENS_DEFAULT,
             temperature = if (model.capabilities.contains(
                     LLMCapability.Temperature
                 )
@@ -137,7 +137,7 @@
     }
 
     @OptIn(ExperimentalUuidApi::class)
     internal fun parseJambaResponse(responseBody: String, clock: Clock = Clock.System): List<Message.Response> {
         val response = json.decodeFromString<JambaResponse>(responseBody)
 
         val inputTokens = response.usage?.promptTokens

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmMain/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/ai21/JambaDataModel.kt

@@ -6,107 +6,126 @@
 
 @Serializable
 internal data class JambaRequest(
-    public val model: String,
-    public val messages: List<JambaMessage>,
-    @SerialName("max_tokens")
-    public val maxTokens: Int? = null,
-    public val temperature: Double? = null,
-    @SerialName("top_p")
-    public val topP: Double? = null,
-    public val stop: List<String>? = null,
-    public val n: Int? = null,
-    public val stream: Boolean? = null,
-    public val tools: List<JambaTool>? = null,
-    @SerialName("response_format")
-    public val responseFormat: JambaResponseFormat? = null
-)
+    val model: String,
+    val messages: List<JambaMessage>,
+    @SerialName("max_tokens") val maxTokens: Int? = MAX_TOKENS_DEFAULT,
+    val temperature: Double? = null,
+    @SerialName("top_p") val topP: Double? = null,
+    val stop: List<String>? = null,
+    val n: Int? = null,
+    val stream: Boolean? = null,
+    val tools: List<JambaTool>? = null,
+    @SerialName("response_format") val responseFormat: JambaResponseFormat? = null
+) {
+    init {
+        if (maxTokens != null) {
+            require(maxTokens > 0) { "maxTokens must be greater than 0, but was $maxTokens" }
+        }
+        if (temperature != null) {
+            require(temperature >= 0) { "temperature must be greater than 0, but was $temperature" }
+        }
+        if (topP != null) {
+            require(topP in 0.0..1.0) { "topP must be between 0 and 1, but was $topP" }
+        }
+    }
+
+    /**
+     * Companion object with default values for request
+     */
+    companion object {
+        /**
+         * Default max tokens
+         */
+        const val MAX_TOKENS_DEFAULT: Int = 4096
+    }
+}
 
 @Serializable
 internal data class JambaMessage(
-    public val role: String,
-    public val content: String? = null,
+    val role: String,
+    val content: String? = null,
     @SerialName("tool_calls")
-    public val toolCalls: List<JambaToolCall>? = null,
+    val toolCalls: List<JambaToolCall>? = null,
     @SerialName("tool_call_id")
-    public val toolCallId: String? = null
+    val toolCallId: String? = null
 )
 
 @Serializable
 internal data class JambaTool(
-    public val type: String = "function",
-    public val function: JambaFunction
+    val type: String = "function",
+    val function: JambaFunction
 )
 
 @Serializable
 internal data class JambaFunction(
-    public val name: String,
-    public val description: String,
-    public val parameters: JsonObject
+    val name: String,
+    val description: String,
+    val parameters: JsonObject
 )
 
 @Serializable
 internal data class JambaToolCall(
-    public val id: String,
-    public val type: String = "function",
-    public val function: JambaFunctionCall
+    val id: String,
+    val type: String = "function",
+    val function: JambaFunctionCall
 )
 
 @Serializable
 internal data class JambaFunctionCall(
-    public val name: String,
-    public val arguments: String
+    val name: String,
+    val arguments: String
 )
 
 @Serializable
 internal data class JambaResponseFormat(
-    public val type: String
+    val type: String
 )
 
 @Serializable
 internal data class JambaResponse(
-    public val id: String,
-    public val model: String,
-    public val choices: List<JambaChoice>,
-    public val usage: JambaUsage? = null
+    val id: String,
+    val model: String,
+    val choices: List<JambaChoice>,
+    val usage: JambaUsage? = null
 )
 
 @Serializable
 internal data class JambaChoice(
-    public val index: Int,
-    public val message: JambaMessage,
+    val index: Int,
+    val message: JambaMessage,
     @SerialName("finish_reason")
-    public val finishReason: String? = null
+    val finishReason: String? = null
 )
 
 @Serializable
 internal data class JambaUsage(
     @SerialName("prompt_tokens")
-    public val promptTokens: Int,
+    val promptTokens: Int,
     @SerialName("completion_tokens")
-    public val completionTokens: Int,
+    val completionTokens: Int,
     @SerialName("total_tokens")
-    public val totalTokens: Int
+    val totalTokens: Int
 )
 
 @Serializable
 internal data class JambaStreamResponse(
-    public val id: String,
-    public val choices: List<JambaStreamChoice>,
-    public val usage: JambaUsage? = null
+    val id: String,
+    val choices: List<JambaStreamChoice>,
+    val usage: JambaUsage? = null
 )
 
 @Serializable
 internal data class JambaStreamChoice(
-    public val index: Int,
-    public val delta: JambaStreamDelta,
+    val index: Int,
+    val delta: JambaStreamDelta,
     @SerialName("finish_reason")
-    public val finishReason: String? = null
+    val finishReason: String? = null
 )
 
 @Serializable
 internal data class JambaStreamDelta(
-    public val role: String? = null,
-    public val content: String? = null,
+    val role: String? = null,
+    val content: String? = null,
     @SerialName("tool_calls")
-    public val toolCalls: List<JambaToolCall>? = null
+    val toolCalls: List<JambaToolCall>? = null
 )

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmMain/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/amazon/BedrockAmazonNovaSerialization.kt

@@ -44,7 +44,7 @@
             }
 
         val inferenceConfig = NovaInferenceConfig(
-            maxTokens = 4096,
+            maxTokens = prompt.params.maxTokens ?: NovaInferenceConfig.MAX_TOKENS_DEFAULT,
             temperature = if (model.capabilities.contains(LLMCapability.Temperature)) {
                 prompt.params.temperature
             } else {
@@ -59,7 +59,7 @@
         )
     }
 
     internal fun parseNovaResponse(responseBody: String, clock: Clock = Clock.System): List<Message.Response> {
         val response = json.decodeFromString<NovaResponse>(responseBody)
         val messageContent = response.output.message.content.firstOrNull()?.text ?: ""
         val outputTokens = response.usage?.outputTokens

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmMain/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/amazon/NovaDataModels.kt

@@ -45,8 +45,18 @@ internal data class NovaInferenceConfig(
     @SerialName("topK")
     val topK: Int? = null,
     @SerialName("maxTokens")
-    val maxTokens: Int? = null
-)
+    val maxTokens: Int? = MAX_TOKENS_DEFAULT
+) {
+    /**
+     * Companion object with default values for request
+     */
+    companion object {
+        /**
+         * Default max tokens
+         */
+        const val MAX_TOKENS_DEFAULT: Int = 4096
+    }
+}
 
 /**
  * Response data classes for Amazon Nova models

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmMain/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/anthropic/BedrockAnthropicClaudeSerialization.kt

@@ -170,7 +170,7 @@
         return AnthropicMessageRequest(
             model = model.id,
             messages = messages,
-            maxTokens = 4096,
+            maxTokens = prompt.params.maxTokens ?: AnthropicMessageRequest.MAX_TOKENS_DEFAULT,
             temperature = if (model.capabilities.contains(
                     LLMCapability.Temperature
                 )
@@ -186,7 +186,7 @@
     }
 
     @OptIn(ExperimentalUuidApi::class)
     internal fun parseAnthropicResponse(responseBody: String, clock: Clock = Clock.System): List<Message.Response> {
         val response = json.decodeFromString<AnthropicResponse>(responseBody)
 
         val inputTokens = response.usage?.inputTokens

prompt/prompt-executor/prompt-executor-clients/prompt-executor-bedrock-client/src/jvmTest/kotlin/ai/koog/prompt/executor/clients/bedrock/modelfamilies/ai21/BedrockAI21JambaSerializationTest.kt

@@ -5,6 +5,7 @@ import ai.koog.agents.core.tools.ToolParameterDescriptor
 import ai.koog.agents.core.tools.ToolParameterType
 import ai.koog.prompt.dsl.Prompt
 import ai.koog.prompt.executor.clients.bedrock.BedrockModels
+import ai.koog.prompt.executor.clients.bedrock.modelfamilies.ai21.JambaRequest.Companion.MAX_TOKENS_DEFAULT
 import ai.koog.prompt.llm.LLMCapability
 import ai.koog.prompt.llm.LLMProvider
 import ai.koog.prompt.llm.LLModel
@@ -43,7 +44,7 @@ class BedrockAI21JambaSerializationTest {
 
         assertNotNull(request)
         assertEquals(model.id, request.model)
-        assertEquals(4096, request.maxTokens)
+        assertEquals(MAX_TOKENS_DEFAULT, request.maxTokens)
         assertEquals(temperature, request.temperature)
 
         assertEquals(2, request.messages.size)
@@ -55,6 +56,22 @@ class BedrockAI21JambaSerializationTest {
         assertEquals(userMessage, request.messages[1].content)
     }
 
+    @Test
+    fun `createJambaRequest with custom maxTokens`() {
+        val maxTokens = 1000
+
+        val prompt = Prompt.build("test", params = LLMParams(maxTokens = maxTokens)) {
+            system(systemMessage)
+            user(userMessage)
+        }
+
+        val request = BedrockAI21JambaSerialization.createJambaRequest(prompt, model, emptyList())
+
+        assertNotNull(request)
+        assertEquals(model.id, request.model)
+        assertEquals(MAX_TOKENS_DEFAULT, request.maxTokens)
+    }
+
     @Test
     fun `createJambaRequest with conversation history`() {
         val userNewMessage = "Hello, who are you?"