Add Ollama models (gpt-oss, qwen3-vl) and update simple examples

examples/simple-examples/src/main/kotlin/ai/koog/agents/example/attachments/InstagramPostDescriber.kt

@@ -5,11 +5,13 @@ import ai.koog.prompt.dsl.prompt
 import ai.koog.prompt.executor.clients.anthropic.AnthropicModels
 import ai.koog.prompt.executor.clients.google.GoogleModels
 import ai.koog.prompt.executor.clients.openai.OpenAIModels
+import ai.koog.prompt.executor.llms.SingleLLMPromptExecutor
 import ai.koog.prompt.executor.llms.all.simpleAnthropicExecutor
 import ai.koog.prompt.executor.llms.all.simpleGoogleAIExecutor
 import ai.koog.prompt.executor.llms.all.simpleOpenAIExecutor
+import ai.koog.prompt.executor.ollama.client.OllamaClient
+import ai.koog.prompt.llm.OllamaModels
 import ai.koog.prompt.markdown.markdown
-import kotlinx.coroutines.runBlocking
 import kotlinx.io.files.Path
 
 suspend fun main() {
@@ -40,18 +42,24 @@ suspend fun main() {
         }
     }
 
+    val ollamaModel = OllamaModels.Alibaba.QWEN3_VL_8B
+    val llmClient = OllamaClient().also { it.getModelOrNull(ollamaModel.id, pullIfMissing = true) }
+    val ollamaExecutor = SingleLLMPromptExecutor(llmClient)
     val openaiExecutor = simpleOpenAIExecutor(ApiKeyService.openAIApiKey)
     val anthropicExecutor = simpleAnthropicExecutor(ApiKeyService.anthropicApiKey)
     val googleExecutor = simpleGoogleAIExecutor(ApiKeyService.googleApiKey)
 
     try {
+        println("OllamaAI response:")
+        ollamaExecutor.execute(prompt, ollamaModel).single().content.also(::println)
         println("OpenAI response:")
         openaiExecutor.execute(prompt, OpenAIModels.Chat.GPT4_1).single().content.also(::println)
         println("Anthropic response:")
         anthropicExecutor.execute(prompt, AnthropicModels.Sonnet_4).single().content.also(::println)
         println("Google response:")
         googleExecutor.execute(prompt, GoogleModels.Gemini2_0Flash).single().content.also(::println)
     } finally {
+        ollamaExecutor.close()
         openaiExecutor.close()
         anthropicExecutor.close()
         googleExecutor.close()

prompt/prompt-llm/src/commonMain/kotlin/ai/koog/prompt/llm/OllamaModels.kt

@@ -291,6 +291,32 @@ public object OllamaModels {
             ),
             contextLength = 32_768,
         )
+
+        /**
+         * Represents the Alibaba Qwen vision-language model version 3 with 8 billion parameters.
+         *
+         * This predefined instance of `LLModel` is provided by Alibaba and supports the following capabilities:
+         * - `Schema.JSON.Simple`: Supports tasks requiring JSON schema validation and handling in a simplified manner.
+         * - `Temperature`: Allows adjustment of the temperature setting for controlling the randomness in responses.
+         * - `Tools`: Enables interaction with external tools or functionalities within the model's ecosystem.
+         * - `Vision.Image`: Enables processing and understanding of image inputs alongside text.
+         *
+         * The model is identified by the unique ID "qwen3-vl:8b" and categorized under the Ollama provider.
+         *
+         * <a href="https://ollama.com/library/qwen3-vl">
+         */
+        public val QWEN3_VL_8B: LLModel = LLModel(
+            provider = LLMProvider.Ollama,
+            id = "qwen3-vl:8b",
+            capabilities =
+            listOf(
+                LLMCapability.Schema.JSON.Basic,
+                LLMCapability.Temperature,
+                LLMCapability.Tools,
+                LLMCapability.Vision.Image,
+            ),
+            contextLength = 256_000,
+        )
     }
 
     /**
@@ -327,4 +353,33 @@ public object OllamaModels {
             contextLength = 16_384,
         )
     }
+
+    /**
+     * The `OpenAI` object represents the configuration for OpenAI large language models (LLMs).
+     * It contains the predefined model specifications for OpenAI LLMs, including their identifiers
+     * and supported capabilities.
+     */
+    public object OpenAI {
+        /**
+         * Represents the OpenAI gpt-oss model with 20 billion parameters.
+         *
+         * It leverages a standard set of capabilities for interaction.
+         *
+         * @see <a href="https://ollama.com/library/gpt-oss">
+         */
+        public val GPT_OSS_20B: LLModel = LLModel(
+            provider = LLMProvider.Ollama,
+            id = "gpt-oss:20b",
+            capabilities =
+            listOf(
+                LLMCapability.Completion,
+                LLMCapability.Schema.JSON.Standard,
+                LLMCapability.Speculation,
+                LLMCapability.Temperature,
+                LLMCapability.ToolChoice,
+                LLMCapability.Tools,
+            ),
+            contextLength = 128_000,
+        )
+    }
 }