fix(agents): Add ids for reasoning messages and improve reasoning process to fix status 400 from openai

agents/agents-core/src/commonMain/kotlin/ai/koog/agents/core/agent/AIAgentBuilder.kt

@@ -79,6 +79,18 @@ public class GraphAgentBuilder<Input, Output>(
         }
     }
 
+    /**
+     * Installs a new feature into the GraphAgentBuilder.
+     *
+     * @param featureInstaller A lambda function that utilizes the FeatureContext to define the feature to be installed.
+     * @return The updated instance of GraphAgentBuilder with the newly added feature.
+     */
+    public fun install(
+        featureInstaller: FeatureContext.() -> Unit,
+    ): GraphAgentBuilder<Input, Output> = apply {
+        this.featureInstallers += featureInstaller
+    }
+
     /**
      * Builds and returns an instance of `AIAgent` configured using the parameters
      * provided to the `GraphAgentBuilder`.

examples/simple-examples/build.gradle.kts

@@ -24,10 +24,6 @@ dependencies {
     //noinspection UseTomlInstead
     implementation("ai.koog:agents-features-chat-memory-sql")
     //noinspection UseTomlInstead
-    implementation("ai.koog:agents-features-chat-history-jdbc")
-    //noinspection UseTomlInstead
-    implementation("ai.koog:agents-features-persistence-jdbc")
-    //noinspection UseTomlInstead
     implementation("ai.koog:agents-features-a2a-server")
     //noinspection UseTomlInstead
     implementation("ai.koog:agents-features-a2a-client")

examples/simple-examples/src/main/kotlin/ai/koog/agents/example/streaming/StreamingAgentWithTools.kt

@@ -13,8 +13,13 @@ import ai.koog.agents.example.ApiKeyService
 import ai.koog.agents.example.simpleapi.Switch
 import ai.koog.agents.example.simpleapi.SwitchTools
 import ai.koog.agents.features.eventHandler.feature.handleEvents
+import ai.koog.prompt.dsl.prompt
 import ai.koog.prompt.executor.clients.anthropic.AnthropicModels
 import ai.koog.prompt.executor.clients.openai.OpenAIModels
+import ai.koog.prompt.executor.clients.openai.OpenAIResponsesParams
+import ai.koog.prompt.executor.clients.openai.base.models.ReasoningEffort
+import ai.koog.prompt.executor.clients.openai.models.ReasoningConfig
+import ai.koog.prompt.executor.clients.openai.models.ReasoningSummary
 import ai.koog.prompt.executor.llms.all.simpleOpenAIExecutor
 import ai.koog.prompt.executor.model.PromptExecutor
 import ai.koog.prompt.message.Message
@@ -35,8 +40,14 @@ suspend fun main() {
                     println("\n🔧 Using ${context.toolName} with ${context.toolArgs}... ")
                 }
                 onLLMStreamingFrameReceived { context ->
-                    (context.streamFrame as? StreamFrame.TextDelta)?.let { frame ->
-                        print(frame.text)
+                    when (val frame = context.streamFrame) {
+                        is StreamFrame.ReasoningComplete -> println("Reasoning complete:id=${frame.id}\ntext=${frame.text}\nsummary=${frame.summary}")
+                        is StreamFrame.TextComplete -> println("Text complete")
+                        is StreamFrame.ToolCallComplete -> println("Tool call complete")
+                        is StreamFrame.ReasoningDelta -> println("Reasoning delta:id=${frame.id}\ntext=${frame.text}\nsummary=${frame.summary}")
+                        is StreamFrame.TextDelta -> println("Text delta:\n${frame.text}")
+                        is StreamFrame.ToolCallDelta -> println("Tool call delta:\n${frame.content}")
+                        is StreamFrame.End -> println("End")
                     }
                 }
                 onLLMStreamingFailed {
@@ -68,15 +79,20 @@ private fun openAiAgent(
     toolRegistry: ToolRegistry,
     executor: PromptExecutor,
     installFeatures: FeatureContext.() -> Unit = {}
-) = AIAgent(
-    promptExecutor = executor,
-    strategy = streamingWithToolsStrategy(),
-    llmModel = OpenAIModels.Chat.GPT4oMini,
-    systemPrompt = "You're responsible for running a Switch and perform operations on it by request",
-    temperature = 0.0,
-    toolRegistry = toolRegistry,
-    installFeatures = installFeatures
-)
+) = AIAgent.builder()
+    .graphStrategy { streamingWithToolsStrategy() }
+    .promptExecutor(executor)
+    .prompt(prompt("agent", OpenAIResponsesParams(
+        temperature = 1.0,
+        reasoning = ReasoningConfig(effort = ReasoningEffort.MEDIUM, summary = ReasoningSummary.AUTO)
+    ))
+    {
+        system("You're responsible for running a Switch and perform operations on it by request")
+    })
+    .llmModel(OpenAIModels.Chat.GPT5_1)
+    .toolRegistry(toolRegistry)
+    .install(installFeatures)
+    .build()
 
 @Suppress("unused")
 private fun anthropicAgent(

integration-tests/src/jvmTest/kotlin/ai/koog/integration/tests/executor/ExecutorIntegrationTestBase.kt

@@ -103,6 +103,7 @@ abstract class ExecutorIntegrationTestBase {
     private val testScope = TestScope()
     private val basicLimit = 256
     private val extendedLimit = 512
+    private val reasoningLimit = 10000
 
     @AfterEach
     fun cleanup() {
@@ -136,22 +137,22 @@ abstract class ExecutorIntegrationTestBase {
                     summary = ReasoningSummary.AUTO
                 ),
                 include = listOf(OpenAIInclude.REASONING_ENCRYPTED_CONTENT),
-                maxTokens = basicLimit
+                maxTokens = reasoningLimit
             )
 
             is GoogleLLMProvider -> {
                 val thinkingConfig = GoogleThinkingConfig(
                     includeThoughts = true,
-                    thinkingBudget = extendedLimit
+                    thinkingBudget = reasoningLimit
                 )
                 GoogleParams(
                     thinkingConfig = thinkingConfig,
                     // Slightly higher limit to avoid truncation in multi-step reasoning tests
-                    maxTokens = extendedLimit
+                    maxTokens = reasoningLimit
                 )
             }
 
-            else -> LLMParams(maxTokens = basicLimit)
+            else -> LLMParams(maxTokens = reasoningLimit)
         }
     }
 
@@ -214,8 +215,9 @@ abstract class ExecutorIntegrationTestBase {
         )
 
         val executor = getExecutor(model)
+        val params = createReasoningParams(model)
 
-        val prompt = Prompt.build("test-streaming") {
+        val prompt = Prompt.build("test-streaming", params = params) {
             system("You are a helpful assistant.")
             user("Count from 1 to 5. Like 1, 2, 3 ...")
         }
@@ -1100,17 +1102,11 @@ abstract class ExecutorIntegrationTestBase {
     open fun integration_testReasoningStreamingSummaryDeltas(model: LLModel) = runTest(timeout = 300.seconds) {
         Models.assumeAvailable(model.provider)
 
-        val params = OpenAIResponsesParams(
-            reasoning = ReasoningConfig(
-                effort = ReasoningEffort.MEDIUM,
-                summary = ReasoningSummary.DETAILED
-            ),
-            include = listOf(OpenAIInclude.REASONING_ENCRYPTED_CONTENT),
-            maxTokens = basicLimit
-        )
+        val params = createReasoningParams(model)
+
         val prompt = Prompt.build("reasoning-streaming-test", params = params) {
             system("You are a helpful assistant.")
-            user("Think about this step by step: What is 12 * 15?")
+            user("Reason about what is 8 * 9?. Include summary.")
         }
 
         val executor = getExecutor(model)
@@ -1137,7 +1133,7 @@ abstract class ExecutorIntegrationTestBase {
             (reasoningText + reasoningSummary).length shouldBeGreaterThan 0
 
             val finalAnswer = textDeltaFrames.joinToString("") { it.text }
-            finalAnswer.shouldContain("180")
+            finalAnswer.shouldContain("72")
         }
     }
 

integration-tests/src/jvmTest/kotlin/ai/koog/integration/tests/executor/MultipleLLMPromptExecutorIntegrationTest.kt

@@ -12,7 +12,6 @@ import ai.koog.prompt.executor.model.PromptExecutor
 import ai.koog.prompt.llm.LLMProvider
 import ai.koog.prompt.llm.LLModel
 import org.junit.jupiter.api.Assumptions.assumeTrue
-import org.junit.jupiter.api.Disabled
 import org.junit.jupiter.params.ParameterizedTest
 import org.junit.jupiter.params.provider.Arguments
 import org.junit.jupiter.params.provider.MethodSource
@@ -141,6 +140,18 @@ class MultipleLLMPromptExecutorIntegrationTest : ExecutorIntegrationTestBase() {
         super.integration_testExecuteStreamingWithTools(model)
     }
 
+    @ParameterizedTest
+    @MethodSource("ai.koog.integration.tests.utils.Models#openAIReasoningModels")
+    override fun integration_testReasoningStreamingSummaryDeltas(model: LLModel) {
+        super.integration_testReasoningStreamingSummaryDeltas(model)
+    }
+
+    @ParameterizedTest
+    @MethodSource("ai.koog.integration.tests.utils.Models#openAIReasoningModels")
+    override fun integration_testReasoningStreamingWithEncryptedContent(model: LLModel) {
+        super.integration_testReasoningStreamingWithEncryptedContent(model)
+    }
+
     @ParameterizedTest
     @MethodSource("ai.koog.integration.tests.utils.Models#latestModels")
     override fun integration_testToolWithRequiredParams(model: LLModel) {
@@ -295,19 +306,6 @@ class MultipleLLMPromptExecutorIntegrationTest : ExecutorIntegrationTestBase() {
         super.integration_testReasoningWithEncryption(model)
     }
 
-    @Disabled("KG-767 OpenAILLMClient loses Responses API reasoning summary stream events")
-    @ParameterizedTest
-    @MethodSource("ai.koog.integration.tests.utils.Models#openAIReasoningModels")
-    override fun integration_testReasoningStreamingSummaryDeltas(model: LLModel) {
-        super.integration_testReasoningStreamingSummaryDeltas(model)
-    }
-
-    @ParameterizedTest
-    @MethodSource("ai.koog.integration.tests.utils.Models#openAIReasoningModels")
-    override fun integration_testReasoningStreamingWithEncryptedContent(model: LLModel) {
-        super.integration_testReasoningStreamingWithEncryptedContent(model)
-    }
-
     @ParameterizedTest
     @MethodSource("ai.koog.integration.tests.utils.Models#reasoningCapableModels")
     override fun integration_testReasoningMultiStep(model: LLModel) {

integration-tests/src/jvmTest/kotlin/ai/koog/integration/tests/utils/Models.kt

@@ -119,7 +119,7 @@ object Models {
     @JvmStatic
     fun openAIReasoningModels(): Stream<LLModel> {
         return Stream.of(
-            OpenAIModels.Chat.GPT5_2,
+            OpenAIModels.Chat.GPT5_4,
         )
     }
 

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

@@ -105,7 +105,7 @@ public object AnthropicModels : LLModelDefinitions {
             LLMCapability.ToolChoice,
             LLMCapability.Vision.Image,
             LLMCapability.Document,
-            LLMCapability.Completion
+            LLMCapability.Completion,
         ) + thinkingCapabilities,
         contextLength = 200_000,
         maxOutputTokens = 64_000,
@@ -184,7 +184,7 @@ public object AnthropicModels : LLModelDefinitions {
             LLMCapability.ToolChoice,
             LLMCapability.Vision.Image,
             LLMCapability.Document,
-            LLMCapability.Completion
+            LLMCapability.Completion,
         ) + thinkingCapabilities,
         contextLength = 200_000,
         maxOutputTokens = 32_000,
@@ -209,7 +209,7 @@ public object AnthropicModels : LLModelDefinitions {
             LLMCapability.ToolChoice,
             LLMCapability.Vision.Image,
             LLMCapability.Document,
-            LLMCapability.Completion
+            LLMCapability.Completion,
         ) + thinkingCapabilities,
         contextLength = 200_000,
         maxOutputTokens = 32_000,

prompt/prompt-executor/prompt-executor-clients/prompt-executor-deepseek-client/src/commonMain/kotlin/ai/koog/prompt/executor/clients/deepseek/DeepSeekModels.kt

@@ -63,6 +63,7 @@ public object DeepSeekModels : LLModelDefinitions {
             LLMCapability.Schema.JSON.Basic,
             LLMCapability.Schema.JSON.Standard,
             LLMCapability.MultipleChoices,
+            LLMCapability.Thinking,
         ),
         contextLength = 64_000,
         maxOutputTokens = 64_000

prompt/prompt-executor/prompt-executor-clients/prompt-executor-google-client/src/commonMain/kotlin/ai/koog/prompt/executor/clients/google/GoogleModels.kt

@@ -64,7 +64,7 @@ public object GoogleModels : LLModelDefinitions {
     )
 
     /**
-     * Full capabilities including standard, multimodal, tools and native structured output
+     * Full capabilities including standard, multimodal, tools, native structured output
      */
     private val fullCapabilities: List<LLMCapability> =
         standardCapabilities + multimodalCapabilities + toolCapabilities + structuredOutputCapabilities
@@ -130,7 +130,7 @@ public object GoogleModels : LLModelDefinitions {
     public val Gemini2_5Pro: LLModel = LLModel(
         provider = LLMProvider.Google,
         id = "gemini-2.5-pro",
-        capabilities = fullCapabilities,
+        capabilities = fullCapabilities + LLMCapability.Thinking,
         contextLength = 1_048_576,
         maxOutputTokens = 65_536,
     )
@@ -144,7 +144,7 @@ public object GoogleModels : LLModelDefinitions {
     public val Gemini2_5Flash: LLModel = LLModel(
         provider = LLMProvider.Google,
         id = "gemini-2.5-flash",
-        capabilities = fullCapabilities,
+        capabilities = fullCapabilities + LLMCapability.Thinking,
         contextLength = 1_048_576,
         maxOutputTokens = 65_536,
     )

prompt/prompt-executor/prompt-executor-clients/prompt-executor-mistralai-client/src/commonMain/kotlin/ai/koog/prompt/executor/clients/mistralai/MistralAIModels.kt

@@ -122,7 +122,8 @@ public object MistralAIModels : LLModelDefinitions {
                 LLMCapability.Speculation,
                 LLMCapability.Vision.Image,
                 LLMCapability.Document,
-                LLMCapability.MultipleChoices
+                LLMCapability.MultipleChoices,
+                LLMCapability.Thinking,
             ),
             contextLength = 128_000
         )

prompt/prompt-executor/prompt-executor-clients/prompt-executor-ollama-client/src/commonMain/kotlin/ai/koog/prompt/executor/ollama/client/OllamaClient.kt

@@ -302,10 +302,10 @@ public class OllamaClient @JvmOverloads constructor(
                     val chunk = ollamaJson.decodeFromString<OllamaChatResponseDTO>(line)
                     chunk.message?.let { message ->
                         if (message.content.isNotEmpty()) {
-                            emitTextDelta(message.content)
+                            emitTextDelta(text = message.content)
                         }
                         if (message.thinking.isNullOrEmpty().not()) {
-                            emitReasoningDelta(message.thinking)
+                            emitReasoningDelta(text = message.thinking)
                         }
                         message.toolCalls?.forEachIndexed { index, toolCall ->
                             val name = toolCall.function.name

prompt/prompt-executor/prompt-executor-clients/prompt-executor-ollama-client/src/commonMain/kotlin/ai/koog/prompt/executor/ollama/client/OllamaModels.kt

@@ -226,7 +226,8 @@ public object OllamaModels : LLModelDefinitions {
             capabilities = listOf(
                 LLMCapability.Temperature,
                 LLMCapability.Schema.JSON.Basic,
-                LLMCapability.Tools
+                LLMCapability.Tools,
+                LLMCapability.Thinking,
             ),
             contextLength = 40_960,
         )
@@ -250,7 +251,8 @@ public object OllamaModels : LLModelDefinitions {
             capabilities = listOf(
                 LLMCapability.Temperature,
                 LLMCapability.Schema.JSON.Basic,
-                LLMCapability.Tools
+                LLMCapability.Tools,
+                LLMCapability.Thinking,
             ),
             contextLength = 40_960,
         )
@@ -359,7 +361,8 @@ public object OllamaModels : LLModelDefinitions {
             capabilities = listOf(
                 LLMCapability.Temperature,
                 LLMCapability.Schema.JSON.Basic,
-                LLMCapability.Tools
+                LLMCapability.Tools,
+                LLMCapability.Thinking,
             ),
             contextLength = 32_768,
         )