Update log action configuration to specify model loading message

.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:3.0.1": {
+      "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
+      }
+    }
+  }
+}

requirements.txt

@@ -1,2 +1 @@
-vastai-sdk>=0.3.0
+vastai-sdk
-nltk==3.9.4 

workers/openai/worker.py

@@ -1,33 +1,19 @@
-import nltk
 import random
 import os
+import re
+import logging
 
 from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, BenchmarkConfig
 
-# vLLM model configuration
+logging.getLogger().setLevel(logging.WARNING)  # Only show warnings and errors
+
+# Ollama model configuration
 MODEL_SERVER_URL           = 'http://127.0.0.1'
-MODEL_SERVER_PORT          = 18000
+MODEL_SERVER_PORT          = 11434
-MODEL_LOG_FILE             = '/var/log/portal/vllm.log'
+MODEL_LOG_FILE             = '/var/log/onstart.log'
-MODEL_HEALTHCHECK_ENDPOINT = "/health"
+MODEL_HEALTHCHECK_ENDPOINT = "/"
-
-# vLLM-specific log messages
-MODEL_LOAD_LOG_MSG = [
-    "Application startup complete.",
-]
-
-MODEL_ERROR_LOG_MSGS = [
-    "INFO exited: vllm",
-    "RuntimeError: Engine",
-    "Traceback (most recent call last):"
-]
-
-MODEL_INFO_LOG_MSGS = [
-    '"message":"Download'
-]
-
-nltk.download("words")
-WORD_LIST = nltk.corpus.words.words()
 
+# Ollama-specific log messages
 def request_parser(request):
     data = request
     if request.get("input") is not None:
@@ -36,8 +22,24 @@ def request_parser(request):
 
 
 def completions_benchmark_generator() -> dict:
+    # extract words from the python source code of the worker to create a list of words for generating prompts
+
+    WORD_LIST = []
+
+    # Try to load from perl copyright file first
+    try:
+        with open("/usr/share/doc/perl/copyright", 'r') as f:
+            source_code = f.read()
+            WORD_LIST = re.findall(r'\b\w+\b', source_code)
+    except (FileNotFoundError, IOError):
+        # Fallback to loading from python file
+        with open(__file__, 'r') as f:
+            source_code = f.read()
+            WORD_LIST = re.findall(r'\b\w+\b', source_code)
+
     prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
     model = os.environ.get("MODEL_NAME")
+
     if not model:
         raise ValueError("MODEL_NAME environment variable not set")
 
@@ -77,9 +79,9 @@ worker_config = WorkerConfig(
         )
     ],
     log_action_config=LogActionConfig(
-        on_load=MODEL_LOAD_LOG_MSG,
+        on_load=["llama_server: model loaded"],
-        on_error=MODEL_ERROR_LOG_MSGS,
+        on_error=["Traceback (most recent call last):","Error:"],
-        on_info=MODEL_INFO_LOG_MSGS
+        #on_info=["load_tensors:","llama_context:","print_info:","llama_model_loader:"]
     )
 )