0.5.4

Published 03 December 2025

Improvements

• LLM clients: better error reporting (#1149). Potential breaking change: LLM clients now throw LLMClientException instead of IllegalStateException (KG-552)
• Add support for OpenAI GPT-5.1 and GPT-5 pro (#1121) and (#1113) and Anthropic Claude Opus 4.5 (#1199)
• Add Bedrock support in Ktor for configuring and initializing Bedrock LLM clients. (#1141)
• Improve Bedrock moderation implementation (#1105)
• Add handler for GooglePart.InlineData in GoogleLLMClient (#1094) (KG-487)
• Improvements in ReadFileTool (#1182) and (#1213)

Bug Fixes

• Fix and simplify McpTool to properly support updated Tool serialization (#1128)
• Fix file tools to properly use newer API to provide textual tool result representation (#1201)
• Fix empty list condition check in onMultipleToolResults and onMultipleAssistantMessages (#1192)
• Fix reasoning message handling in strategy (#1166)
• Fix timeout in JvmShellCommandExecutor (#1005)

0.5.3

Published 12 November 2025

New Features

• Reasoning messages support (#943)
• Add get models list request to OpenAI-based LLMClients (#1074)

Improvements

• Support subgraph execution events in an agent pipeline and features, including OpenTelemetry (#1052)
• Make systemPrompt and temperature optional, set default temperature to null in AIAgent factory functions (#1078)
• Improve compatibility with kotlinx-coroutines 1.8 in runtime by removing featurePrepareDispatcher from AIAgentPipeline (#1083)

Bug Fixes

• Fix persistence feature by making ReceivedToolResult serializable (#1049)
• Make clients properly rethrow cancellations and remove exception wrapping (#1057)
• Fix StructureFixingParser to do the right number of retires (#1084)

0.5.2

Published 29 Oct 2025

New Features

• Add subtask extension for non-graph agents similar to subgraphWithTask (#982)
• Add MistralAI LLM Client (#622)

Improvements

• Replace string content and attachments list in messages with a unified content parts list to make the API more flexible and preserve text/attachment parts order (#1004)
• Add input and output attributes to the NodeExecuteSpan span in OpenTelemetry to improve observability (KG-501)
• Set the JVM target to 11 to support older JVM versions and explicitly specify the JVM target. (#1015)
• Support multi-responses from LLM in the subgraphWithTask API (KG-507)

0.5.1

Published 15 Oct 2025

Improvements

• Add error handling in LocalFileMemoryProvider (#905)
• Add GPT-5 Codex model support (#888)
• Added support for filters in PersistenceProvider (#936)
• Added DashScope (Qwen) LLM client support (#687)
• Excluded Ktor engine dependencies (KG-315)
• Support additional Bedrock auth options (#923)
• requestLLMStreaming now respect AgentConfig.missingToolsConversionStrategy (#944)

Bug Fixes

• Make subgraphWithTask work with models without ToolChoice support (KG-440)
• Fix for KTOR-8881 - Ktor/Koog configuration in application.yaml gives error
• Fixed the ordering issue for Persistence checkpoints (#964)
• Fixed issue with the tool name in @Tool annotation - now we take it into account (#930)

Examples

• Supported Multi-LLM Prompt Executor Spring Bean by adding llmProvider method to LLM clients (#842)

0.5.0

Published 2 Oct 2025

Major Features

• Full Agent-to-Agent (A2A) Protocol Support:
  • Multiplatform Kotlin A2A SDK: Including server and client with JSON-RPC HTTP support.
  • A2A Agent Feature: seamlessly integrate A2A in your Koog agents
• Non-Graph API for Strategies: Introduced non-graph API for creating AI Agent strategies as Kotlin extension functions with most of Koog's features supported (#560)
• Agent Persistence and Checkpointing:
  • Roll back Tool Side-Effects: Add RollbackToolRegistry in the Persistence feature in order to roll back tool calls with side effects when checkpointing.
  • State-Machine Persistence / Message History Switch: Support switching between full state-machine persistence and message history persistence (#856)
• Tool API Improvements:
  • Make ToolDescriptor auto-generated for class-based tools (#791)
  • Get rid of ToolArgs and ToolResult limitations for Tool<*, *> class (#791)
• subgraphWithTask Simplification: Get rid of required finishTool and support tools as functions in subgraphWithTask, deduce final step automatically by data class (#791)
• AIAgentService Introduced: Make AIAgent state-manageable and single-run explicitly, introduce AIAgentService to manage multiple uniform running agents.
• New components:
  • Add LLM as a Judge component (#866)
  • Tool Calling loop with Structured Output strategy (#829)

Improvements

• Make Koog-based tools exportable via MCP server (KG-388)
• Add additionalProperties to LLM clients in order to support custom LLM configurations (#836)
• Allow adjusting context window sizes for Ollama dynamically (#883)
• Refactor streaming api to support tool calls (#747)
• Provide an ability to collect and send a list of nodes and edges out of AIAgentStrategy to the client when running an agent (KG-160)
• Add excludedProperties to inline createJsonStructure too, update KDocs (#826)
• Refactor binary attachment handling and introduce Base64 serializer (#838)
• In JsonStructuredData.defaultJson instance rename class discriminator from #type to kind to align with common practices (#772, KG-384)
• Make standard json generator default when creating JsonStructuredData (it was basic before) (#772, KG-384)
• Add default audio configuration and modalities (#817)
• Add GptAudio model in OpenAI client (#818)
• Allow re-running of finished agents that have Persistence feature installed (#828, KG-193)
• Allow ideomatic node transformations with .transform { ...} lambda function (#684)
• Add ability to filter messages for every agent feature (KG-376)
• Add support for trace-level attributes in Langfuse integration (#860, KG-427)
• Keep all system messages when compressing message history of the agent(#857)
• Add support for Anthropic's Sonnet 4.5 model in Anthropic/Bedrock providers (#885)
• Refactored LLM client auto-configuration in Spring Boot integration, to modular provider-specific classes with improved validation and security (#886)
• Add LLM Streaming agent events (KG-148)

Bug Fixes

• Fix broken Anthropic models support via Amazon Bedrock (#789)
• Make AIAgentStorageKey in agent storage actually unique by removing data modifier (#825)
• Fix rerun for agents with Persistence (#828, KG-193)
• Update mcp version to 0.7.2 with fix for Android target (#835)
• Do not include an empty system message in Anthropic request (#887, KG-317)
• Use maxTokens from params in Google models (#734)
• Fix finishReason nullability (#771)

Deprecations

• Rename agent interceptors in EventHandler and related feature events (KG-376)
• Deprecate concurrent unsafe AIAgent.asTool in favor of AIAgentService.createAgentTool (#873)
• Rename Persistency to Persistence everywhere (#896)
• Add agentId argument to all Persistence methods instead of persistencyId class field (#904)

Examples

• Add a basic code-agent example (#808, KG-227)
• Add iOS and Web targets for demo-compose-app (#779, #780)

0.4.2

Published 15 Sep 2025

Bug Fixes

• Add missing tool calling support for Bedrock Nova models so agents can invoke functions when using Nova (KG-239).
• Add Android target support and migrate Android app to Kotlin Multiplatform to widen KMP coverage (KG-315, #728, #767).
• Add Spring Boot Java example to jump‑start integration (#739).
• Add Java Spring auto‑config fixes: correct property binding and make Koog starter work out of the box (#698).
• Fix split package issues in OpenAI LLM clients to avoid classpath/load errors (KG-305, #694).
• Ensure Anthropic tool schemas include the required "type" field in serialized request bodies to prevent validation errors during tool calling (#582).
• Fix AbstractOpenAILLMClient to correctly handle plain‑text responses in capabilities flow; add integration tests to prevent regressions (#564).
• Fix GraalVM native image build failure so projects can compile native binaries again (#774).
• Fix usages in OpenAI‑based data model to align with recent API changes (#688).

Improvements

• Make agents‑mcp support KMP targets to run across more platforms (#756).
• Add LLM client retry support to Spring Boot auto‑configuration to improve resilience on transient failures (#748).
• Add Claude Opus 4.1 model support to Anthropic client to unlock latest reasoning capabilities (#730).
• Add Gemini 2.5 Flash Lite model support to Google client to enable lower‑latency, cost‑efficient generations (#769).
• Add Java‑compatible non‑streaming Prompt Executor so Java apps can call Koog without coroutines (KG-312, #715).
• Support excluding properties in JSON Schema generation to fine‑tune structured outputs (#638).
• Update AWS SDK to latest compatible version for Bedrock integrations.
• Introduce Postgres persistence provider to store agent state and artifacts (#705).
• Update Kotlin to 2.2.10 in dependency configuration for improved performance and language features (#764).
• Refactor executeStreaming to remove suspend for simpler interop and better call sites (#720).
• Add Java‑compatible prompt executor (non‑streaming) wiring and polish across modules (KG-312, #715).
• Decouple FileSystemEntry from FileSystemProvider to simplify testing and enable alternative providers (#664).

CI and Build

• Nightly build configuration and dependency submission workflow added (#695, #737).

0.4.1

Published 28 Aug 2025

Bug Fixes

Fixed iOS target publication

0.4.0

Published 27 Aug 2025

Major Features

• Integration with Observability Tools:
  • Langfuse Integration: Span adapters for Langfuse client, including open telemetry and graph visualisation (KG-217, KG-223)
  • W&B Weave Integration: Span adapters for W&B Weave open telemetry and observability (KG-217, KG-218)
• Ktor Integration: First-class Ktor support via the "Koog" Ktor plugin to register and run agents in Ktor applications (#422).
• iOS Target Support: Multiplatform expanded with native iOS targets, enabling agents to run on Apple platforms (#512).
• Upgraded Structured Output: Refactored structured output API to be more flexible and add built-in/native provider support for OpenAI and Google, reducing prompt boilerplate and improving validation (#443).
• GPT5 and Custom LLM Parameters Support: Now GPT5 is available together with custom additional LLM parameters for OpenAI-compatible clients (#631, #517)
• Resilience and Retries:
  • Retryable LLM Clients: Introduce retry logic for LLM clients with sensible defaults to reduce transient failures (#592)
  • Retry Anything with LLM Feedback: Add a feedback mechanism to the retry component (subgraphWithRetry) to observe and tune behavior (#459).

Improvements

• OpenTelemetry and Observability:
  • Finish reason and unified attributes for inference/tool/message spans and events; extract event body fields to attributes for better querying (KG-218).
  • Mask sensitive data in events/attributes and introduce a “hidden-by-default” string type to keep secrets safe in logs (KG-259).
  • Include all messages into the inference span and add an index for ChoiceEvent to simplify analysis (KG-172).
  • Add tool arguments to gen_ai.choice and gen_ai.assistant.message events (#462).
  • Allow setting a custom OpenTelemetry SDK instance in Koog (KG-169).
• LLM and Providers:
  • Support Google’s “thinking” mode in generation config to improve reasoning quality (#414).
  • Add responses API support for OpenAI (#645)
  • AWS Bedrock: support Inference Profiles for simpler, consistent configuration (#506) and accept AWS_SESSION_TOKEN (#456).
  • Add maxTokens as prompt parameters for finer control over generation length (#579).
  • Add contextLength and maxOutputTokens to LLModel (#438, KG-134)
• Agent Engine:
  • Add AIAgentPipeline interceptors to uniformly handle node errors; propagate NodeExecutionError across features (KG-170).
  • Include finish node processing in the pipeline to ensure finalizers run reliably (#598).
• File Tools and RAG:
  • Reworked FileSystemProvider with API cleanups and better ergonomics; moved blocking/suspendable operations to Dispatchers.IO for improved performance and responsiveness (#557, “Move suspendable operations to Dispatchers.IO”).
  • Introduce filterByRoot helpers and allow custom path filters in FilteredFileSystemProvider for safer agent sandboxes (#494, #508).
  • Rename PathFilter to TraversalFilter and make its methods suspendable to support async checks.
  • Rename fromAbsoluteString to fromAbsolutePathString for clarity (#567).
  • Add ReadFileTool for reading local file contents where appropriate (#628).
• Update kotlin-mcp dependency to v0.6.0 (#523)

Bug Fixes

• Make parts field nullable in Google responses to handle missing content from Gemini models (#652).
• Fix enum parsing in MCP when type is not mentioned (#601, KG-49)
• Fix function calling for gemini-2.5-flash models to correctly route tool invocations (#586).
• Restore OpenAI responseFormat option support in requests (#643).
• Correct o4-mini vs gpt-4o-mini model mix-up in configuration (#573).
• Ensure event body for function calls is valid JSON for telemetry ingestion (KG-268).
• Fix duplicated tool names resolution in AIAgentSubgraphExt to prevent conflicts (#493).
• Fix Azure OpenAI client settings to generate valid endpoint URLs (#478).
• Restore llama3.2:latest as the default for LLAMA_3_2 to match the provider expectations (#522).
• Update missing Document capabilities for LLModel (#543)
• Fix Anthropic json schema validation error (#457)

Removals / Breaking Changes

• Remove Google Gemini 1.5 Flash/Pro variants from the catalog (KG-216, #574).
• Drop execute extensions for PromptExecutor in favor of the unified API (#591).
• File system API cleanup: removed deprecated FSProvider interfaces and methods; PathFilter renamed to TraversalFilter with suspendable operations; fromAbsoluteString renamed to fromAbsolutePathString.

Examples

• Add a web search agent (from Koog live stream 1) showcasing retrieval + summarization (#575).
• Add a trip planning agent example (from Koog live stream 2) demonstrating tools + planning + composite strategy (#595).
• Improve BestJokeAgent sample and fix NumberGuessingAgent example (#503, #445).

0.3.0

Published 15 Jul 2025

Major Features

• Agent Persistency and Checkpoints: Save and restore agent state to local disk, memory, or easily integrate with
  any cloud storages or databases. Agents can now roll back to any prior state on demand or automatically restore from
  the latest checkpoint (#305)
• Vector Document Storage: Store embeddings and documents in persistent storage for retrieval-augmented generation (
  RAG), with in-memory and local file implementations (#272)
• OpenTelemetry Support: Native integration with OpenTelemetry for unified tracing logs across AI agents (#369, #401,
  #423, #426)
• Content Moderation: Built-in support for moderating models, enabling AI agents to automatically review and filter
  outputs for safety and compliance (#395)
• Parallel Node Execution: Parallelize different branches of your agent graph with a MapReduce-style API to speed up
  agent execution or to choose the best of the parallel attempts (#220, #404)
• Spring Integration: Ready-to-use Spring Boot starter with auto-configured LLM clients and beans (#334)
• AWS Bedrock Support: Native support for Amazon Bedrock provider covering several crucial models and services (
  #285, #419)
• WebAssembly Support: Full support for compiling AI agents to WebAssembly (WASM) for browser deployment (#349)

Improvements

• Multimodal Data Support: Seamlessly integrate and reason over diverse data types such as text, images, and audio (
  #277)
• Arbitrary Input/Output Types: More flexibility over how agents receive data and produce responses (#326)
• Improved History Compression: Enhanced fact-retrieval history compression for better context management (#394,
  #261)
• ReAct Strategy: Built-in support for ReAct (Reasoning and Acting) agent strategy, enabling step-by-step reasoning
  and dynamic action taking (#370)
• Retry Component: Robust retry mechanism to enhance agent resilience (#371)
• Multiple Choice LLM Requests: Generate or evaluate responses using structured multiple-choice formats (#260)
• Azure OpenAI Integration: Support for Azure OpenAI services (#352)
• Ollama Enhancements: Native image input support for agents running with Ollama-backed models (#250)
• Customizable LLM in fact search: Support providing custom LLM for fact retrieval in the history (#289)
• Tool Execution Improvements: Better support for complex parameters in tool execution (#299, #310)
• Agent Pipeline enhancements: More handlers and context available in AIAgentPipeline (#263)
• Default support of tools and messages mixture: Simple single run strategies variants for multiple message and
  parallel tool calls (#344)
• ResponseMetaInfo Enhancement: Add additionalInfo field to ResponseMetaInfo (#367)
• Subgraph Customization: Support custom LLModel and LLMParams in subgraphs, make nodeUpdatePrompt a
  pass-through node (#354)
• Attachments API simplification: Remove additional content builder from MessageContentBuilder, introduce
  TextContentBuilderBase (#331)
• Nullable MCP parameters: Added support for nullable MCP tool parameters (#252)
• ToolSet API enhancement: Add missing tools(ToolSet) convenience method for ToolRegistry builder (#294)
• Thinking support in Ollama: Add THINKING capability and it's serialization for Ollama API 0.9 (#248)
• kotlinx.serialization version update: Update kotlinx-serialization version to 1.8.1
• Host settings in FeatureMessageRemoteServer: Allow configuring custom host in FeatureMessageRemoteServer (#256)

Bug Fixes

• Make CachedPromptExecutor and PromptCache timestamp-insensitive to enable correct caching (#402)
• Fix requestLLMWithoutTools generating tool calls (#325)
• Fix Ollama function schema generation from ToolDescriptor (#313)
• Fix OpenAI and OpenRouter clients to produce simple text user message when no attachments are present (#392)
• Fix intput/output token counts for OpenAILLMClient (#370)
• Using correct Ollama LLM provider for ollama llama4 model (#314)
• Fixed an issue where structured data examples were prompted incorrectly (#325)
• Correct mistaken model IDs in DEFAULT_ANTHROPIC_MODEL_VERSIONS_MAP (#327)
• Remove possibility of calling tools in structured LLM request (#304)
• Fix prompt update in subgraphWithTask (#304)
• Removed suspend modifier from LLMClient.executeStreaming (#240)
• Fix requestLLMWithoutTools to work properly across all providers (#268)

Examples

• W&B Weave Tracing example
• LangFuse Tracing example
• Moderation example: Moderating iterative joke-generation conversation
• Parallel Nodes Execution example: Generating jokes using 3 different LLMs in parallel, and choosing the funniest one
• Snapshot and Persistency example: Taking agent snapshots and restoring its state example

0.2.1

Published 6 Jun 2025

Bug Fixes

• Support MCP enum arg types and object additionalParameters (#214)
• Allow appending handlers for the EventHandler feature (#234)
• Fix LLM clients after #195, make LLM request construction again more explicit in LLM clients (#229)

Improvements

• Migrating of simple agents to AIAgent constructor, simpleSingleRunAgent deprecation (#222)