feat(inference): pass [[models]] params through to llama-server (enables draft-MTP) (#243)

ModelConfig.params was loaded from config but never consumed — the spawn
command in DefaultModelManager was hardcoded. Thread it through: params (a
flag->value map) flattens to token order on ModelDescriptor.extraArgs and
appends to the llama-server argv. This engages Multi-Token Prediction
speculative decoding purely from config:

  [[models]]
  params = { "-md" = "/path/draft.gguf", "-ngld" = "99", "--spec-type" = "draft-mtp", "--spec-draft-n-max" = "4" }

Each entry stays a distinct argv token (no shell), so paths with spaces are safe.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

infrastructure/inference/commons/src/main/kotlin/com/correx/infrastructure/inference/commons/ModelDescriptor.kt

@@ -12,4 +12,7 @@ data class ModelDescriptor(
     val idleTimeoutMs: Long = 60_000L,
     val contextSize: Int = 24_576,
     val capabilities: Set<CapabilityScore> = emptySet(),
+    /** Extra llama-server CLI args (already flattened to token order), e.g. draft-MTP speculative
+     * decoding: `-md <draft.gguf> -ngld 99 --spec-type draft-mtp --spec-draft-n-max 4`. */
+    val extraArgs: List<String> = emptyList(),
 )

infrastructure/inference/llama_cpp/src/main/kotlin/com/correx/infrastructure/inference/llama/cpp/DefaultModelManager.kt

@@ -66,7 +66,7 @@ class DefaultModelManager(
                 "--ctx-size", descriptor.contextSize.toString(),
                 "--host", host,
                 "--port", port.toString(),
-            )
+            ) + descriptor.extraArgs
             val lp = LlamaProcess(command, logFile)
             lp.start()
             lp