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@koshachy koshachy requested a review from a team as a code owner November 14, 2025 13:51
@koshachy koshachy force-pushed the update-ai-development-overview branch from 3e47f14 to 2d3a65e Compare November 17, 2025 11:04
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lgtm 👍
left a couple of comments

}
```

<a href="https://www.google.com/url?q=https://docs.koog.ai/getting-started/"><img src="get-started-with-koog.svg" width="700" alt="Get started with Koog" style="block"/></a>
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Why is this link being used?
When I followed it, I got a "Redirect Notice", was that intentional?

}
```

<a href="https://www.google.com/url?q=https://docs.koog.ai/getting-started/"><img src="get-started-with-koog.svg" width="700" alt="Get started with Koog" style="block"/></a>
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width="700"

Wouldn’t using a fixed width break the layout on mobile devices?

such as W&B Weave and Langfuse for monitoring and debugging AI applications.
* **LLM switching and seamless history adaptation**. Koog allows switching to a different LLM with a new set of tools
at any point without losing the existing conversation history.
It also enables rerouting between multiple LLM providers, including OpenAI, Anthropic, Google, and others.
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I think it would be worth mentioning the ability to run agents locally. I couldn’t find "local" or "ollama" mentioned

@@ -1,4 +1,4 @@
[//]: # (title: Build a Kotlin app that uses Spring AI to answer questions based on documents stored in Qdrant — tutorial)
[//]: # (title: Create a Kotlin app that answers questions with Spring AI — tutorial)
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Should keep qdrant in the title?

Comment on lines +84 to +85
* [OpenAI](https://github.com/openai/openai-java) — official Java SDK for the OpenAI API. It covers responses and chat, images, and audio.
* [Anthropic (Claude)](https://github.com/anthropics/anthropic-sdk-java) — official Java SDK for the Claude Messages API. It includes modules for Vertex AI and Bedrock integrations.
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Do you think it’s worth mentioning that these sdk (openai and anthropic) are written entirely in kotlin?

* Provide context for LLMs in a structured and standardized way, separating context handling from the interaction with LLMs.
* Build MCP clients that consume resources from the existing servers.
* Create MCP servers that expose prompts, tools, and resources for LLMs.
* Use standard communication transports such as stdio, SSE, and WebSocket.
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FYI
the mcp specification currently defines two transports: stdio and streamable. sse has been deprecated.

In our mcp kotlin sdk, streamable support is only partially implemented right now, but it will be fully completed within the next month. So the statement is technically correct at the moment, but it will need to be updated soon

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3 participants