Add devcontainer configuration for Vast.ai serverless Ollama template

.devcontainer/devcontainer.json

@@ -0,0 +1,37 @@
+// .devcontainer/devcontainer.json
+// Dev container for the Vast.ai serverless Ollama template.
+// Includes Docker-in-Docker so you can build and test images from inside the container.
+{
+  "name": "vast.ai-serverless-ollama",
+  "image": "mcr.microsoft.com/devcontainers/base:trixie",
+  "features": {
+    "ghcr.io/devcontainers/features/python:1": {
+      "installTools": true,
+      "version": "3.12"
+    },
+    "ghcr.io/devcontainers/features/docker-in-docker:3.0.0": {
+      "moby": false,
+      "version": "latest",
+      "installDockerBuildx": true,
+      "dockerDashComposeVersion": "v2"
+    }
+  },
+  "runArgs": ["--privileged"],
+  "containerEnv": {
+    "DOCKER_BUILDKIT": "1"
+  },
+  "postCreateCommand": "python3 -m pip install --user --upgrade pip && python3 -m pip install --user -r requirements.txt pyyaml",
+  "customizations": {
+    "vscode": {
+      "extensions": [
+        "ms-python.python",
+        "ms-azuretools.vscode-docker"
+      ],
+      "settings": {
+        "python.defaultInterpreterPath": "/usr/bin/python3",
+        "terminal.integrated.defaultProfile.linux": "bash",
+        "docker.showStartPage": false
+      }
+    }
+  }
+}

workers/openai/worker.py

@@ -7,12 +7,15 @@ from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, Benchma
 # vLLM model configuration
 MODEL_SERVER_URL           = 'http://127.0.0.1'
 MODEL_SERVER_PORT          = 18000
-MODEL_LOG_FILE             = '/var/log/portal/vllm.log'
+MODEL_LOG_FILE             = '/var/log/onstart.log'
 MODEL_HEALTHCHECK_ENDPOINT = "/health"
 
 # vLLM-specific log messages
 MODEL_LOAD_LOG_MSG = [
     "Application startup complete.",
+    "llama runner started in",
+    "Server listening on",
+    "msg=\"Listening on",
 ]
 
 MODEL_ERROR_LOG_MSGS = [