[goose-llm] fix image content bug, add optional request_id field (#3439)

bindings/kotlin/example/RuntimeStats.kt

@@ -0,0 +1,115 @@
+import kotlin.system.measureNanoTime
+import kotlinx.coroutines.runBlocking
+import uniffi.goose_llm.*
+
+import java.net.URI
+import java.net.http.HttpClient
+import java.net.http.HttpRequest
+import java.net.http.HttpResponse
+
+/* ---------- Goose helpers ---------- */
+
+fun buildProviderConfig(host: String, token: String): String =
+    """{ "host": "$host", "token": "$token" }"""
+
+suspend fun timeGooseCall(
+    modelCfg: ModelConfig,
+    providerName: String,
+    providerCfg: String
+): Pair<Double, CompletionResponse> {
+
+    val req = createCompletionRequest(
+        providerName,
+        providerCfg,
+        modelCfg,
+        systemPreamble = "You are a helpful assistant.",
+        messages = listOf(
+            Message(
+                Role.USER,
+                System.currentTimeMillis() / 1000,
+                listOf(MessageContent.Text(TextContent("Write me a 1000 word chapter about learning Go vs Rust in the world of LLMs and AI.")))
+            )
+        ),
+        extensions = emptyList()
+    )
+
+    lateinit var resp: CompletionResponse
+    val wallMs = measureNanoTime { resp = completion(req) } / 1_000_000.0
+    return wallMs to resp
+}
+
+/* ---------- OpenAI helpers ---------- */
+
+fun timeOpenAiCall(client: HttpClient, apiKey: String): Double {
+    val body = """
+        {
+          "model": "gpt-4.1",
+          "max_tokens": 500,
+          "messages": [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user",   "content": "Write me a 1000 word chapter about learning Go vs Rust in the world of LLMs and AI."}
+          ]
+        }
+    """.trimIndent()
+
+    val request = HttpRequest.newBuilder()
+        .uri(URI.create("https://api.openai.com/v1/chat/completions"))
+        .header("Authorization", "Bearer $apiKey")
+        .header("Content-Type", "application/json")
+        .POST(HttpRequest.BodyPublishers.ofString(body))
+        .build()
+
+    val wallMs = measureNanoTime {
+        client.send(request, HttpResponse.BodyHandlers.ofString())
+    } / 1_000_000.0
+
+    return wallMs
+}
+
+/* ---------- main ---------- */
+
+fun main() = runBlocking {
+    /* Goose provider setup */
+    val providerName  = "databricks"
+    val host  = System.getenv("DATABRICKS_HOST") ?: error("DATABRICKS_HOST not set")
+    val token = System.getenv("DATABRICKS_TOKEN") ?: error("DATABRICKS_TOKEN not set")
+    val providerCfg   = buildProviderConfig(host, token)
+
+    /* OpenAI setup */
+    val openAiKey = System.getenv("OPENAI_API_KEY") ?: error("OPENAI_API_KEY not set")
+    val httpClient = HttpClient.newBuilder().build()
+
+    val gooseModels  = listOf("goose-claude-4-sonnet", "goose-gpt-4-1")
+    val runsPerModel = 3
+
+    /* --- Goose timing --- */
+    for (model in gooseModels) {
+        val maxTokens = 500
+        val cfg = ModelConfig(model, 100_000u, 0.0f, maxTokens)
+        var wallSum = 0.0
+        var gooseSum = 0.0
+
+        println("=== Goose: $model ===")
+        repeat(runsPerModel) { run ->
+            val (wall, resp) = timeGooseCall(cfg, providerName, providerCfg)
+            val gooseMs = resp.runtimeMetrics.totalTimeSec * 1_000
+            val overhead = wall - gooseMs
+            wallSum += wall
+            gooseSum += gooseMs
+            println("run ${run + 1}: wall = %.1f ms | goose-llm = %.1f ms | overhead = %.1f ms"
+                .format(wall, gooseMs, overhead))
+        }
+        println("-- avg wall = %.1f ms | avg overhead = %.1f ms --\n"
+            .format(wallSum / runsPerModel, (wallSum - gooseSum) / runsPerModel))
+    }
+
+    /* --- OpenAI direct timing --- */
+    var oaSum = 0.0
+    println("=== OpenAI: gpt-4.1 (direct HTTPS) ===")
+    repeat(runsPerModel) { run ->
+        val wall = timeOpenAiCall(httpClient, openAiKey)
+        oaSum += wall
+        println("run ${run + 1}: wall = %.1f ms".format(wall))
+    }
+    println("-- avg wall = %.1f ms --".format(oaSum / runsPerModel))
+}