Update log action configuration to specify model loading message

.devcontainer/devcontainer.json

@@ -9,7 +9,7 @@
       "installTools": true,
       "version": "3.12"
     },
-    "ghcr.io/devcontainers/features/docker-in-docker:3.0.0": {
+    "ghcr.io/devcontainers/features/docker-in-docker:3.0.1": {
       "moby": false,
       "version": "latest",
       "installDockerBuildx": true,

requirements.txt

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

workers/openai/worker.py

@@ -1,28 +1,19 @@
-import nltk
 import random
 import os
+import re
+import logging
 
 from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, BenchmarkConfig
 
+logging.getLogger().setLevel(logging.WARNING)  # Only show warnings and errors
+
 # Ollama model configuration
-MODEL_SERVER_URL           = 'http://127.0.0.1:11434'
+MODEL_SERVER_URL           = 'http://127.0.0.1'
 MODEL_SERVER_PORT          = 11434
 MODEL_LOG_FILE             = '/var/log/onstart.log'
 MODEL_HEALTHCHECK_ENDPOINT = "/"
 
 # Ollama-specific log messages
-MODEL_LOAD_LOG_MSG = [
-]
-
-MODEL_ERROR_LOG_MSGS = [
-]
-
-MODEL_INFO_LOG_MSGS = [
-]
-
-nltk.download("words")
-WORD_LIST = nltk.corpus.words.words()
-
 def request_parser(request):
     data = request
     if request.get("input") is not None:
@@ -31,8 +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")
 
@@ -72,9 +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:"]
     )
 )