update test timeout and default LLAMA_SERVER_CMD_ARGS for improved performance

.runpod/hub.json

@@ -14,10 +14,10 @@
             {
                 "key": "LLAMA_SERVER_CMD_ARGS",
                 "input": {
-                    "name": "Model Name",
+                    "name": "Command line arguments for llama-server",
                     "type": "string",
                     "description": "Launch command line arguments (argv) for the llama-server binary. Do not define the port.",
-                    "default": "-hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:Q4_K_M -ctx_size 4096",
+                    "default": "-hf unsloth/gemma-3-270m-it-GGUF:Q6_K --ctx-size 4096 -ngl 99",
                     "advanced": false
                 }
             },

.runpod/tests.json

@@ -5,7 +5,7 @@
             "input": {
                 "prompt": "Hi! Who are you?"
             },
-            "timeout": 120000
+            "timeout": 60000
         }
     ],
     "config": {
@@ -14,7 +14,7 @@
         "env": [
             {
                 "key": "LLAMA_SERVER_CMD_ARGS",
-                "value": "-hf unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:Q4_K_M -ctx_size 4096"
+                "value": "-hf unsloth/gemma-3-270m-it-GGUF:IQ2_XXS --ctx-size 512 -ngl 999"
             }
         ],
         "allowedCudaVersions": [

README.md

@@ -4,8 +4,6 @@
 
 # Serverless llama.cpp inference worker for RunPod
 
-[![Runpod badge](https://api.runpod.io/badge/Jacob-ML/inference-worker)](https://console.runpod.io/hub/Jacob-ML/inference-worker)
-
 This repository contains a serverless inference worker for running llama.cpp models on RunPod. It uses the `llama-server` image to provide an API for interacting with the models.
 The following OpenAI API endpoints are supported:
 
@@ -15,6 +13,10 @@ The following OpenAI API endpoints are supported:
 
 Streaming responses is also supported.
 
+**Important!** This project is still relatively new. Please [open a new issue](https://github.com/Jacob-ML/inference-worker/issues/new) if you encounter any problems in order to get help.
+
+**This is a fork of [SvenBrnn's `runpod-worker-ollama`](https://github.com/SvenBrnn/runpod-worker-ollama).**
+
 ## Setup
 
 For the setup to work best, it is recommended to use a network volume attached to all workers which stores the model GGUFs and then reference those files in the launch arguments.
@@ -24,9 +26,11 @@ Make sure your RunPod worker has access to the network volume, i.e. is located i
 
 The worker can be configured via environment variables set in the RunPod hub configuration:
 
-- `LLAMA_SERVER_CMD_ARGS`: Command line arguments (argv) for the `llama-server` binary. Example: `-hf /path/to/model.gguf:Q4_K_M -ctx_size 4096`. **IMPORTANT**: Please do not define the port argument here, as the worker will always use port `3098` automatically.
+- `LLAMA_SERVER_CMD_ARGS`: Command line arguments (argv) for the `llama-server` binary. Example: `-hf /path/to/model.gguf:Q4_K_M --ctx-size 4096`. **IMPORTANT**: Please do not define the port argument here, as the worker will always use port `3098` automatically.
 - `MAX_CONCURRENCY`: Maximum number of concurrent requests the worker can handle. Default is `8`.
 
 ## License
 
 Please see the [LICENSE](./LICENSE) file for more information.
+
+[![Runpod badge](https://api.runpod.io/badge/Jacob-ML/inference-worker)](https://console.runpod.io/hub/Jacob-ML/inference-worker)

src/engine.py

@@ -21,7 +21,6 @@ Typical usage:
 """
 
 import json
-import os
 
 from dotenv import load_dotenv
 from openai import OpenAI

src/find_cached.py

@@ -0,0 +1,59 @@
+"""
+Finds the full LLM GGUF path from the Hugging Face cache.
+"""
+
+import os
+import argparse
+
+CACHE_DIR = "/runpod-volume/huggingface-cache/hub"
+
+
+def find_model_path(model_name, gguf_in_repo="model.gguf"):
+    """
+    Find the path to a cached model.
+
+    Args:
+        model_name: The model name from Hugging Face
+
+    Returns:
+        The full path to the cached model, or None if not found
+    """
+
+    cache_name = model_name.replace("/", "--")
+    snapshots_dir = os.path.join(
+        CACHE_DIR, f"models--{cache_name}", "snapshots"
+    )
+
+    if os.path.exists(snapshots_dir):
+        snapshots = os.listdir(snapshots_dir)
+
+        if snapshots:
+            return os.path.join(snapshots_dir, snapshots[0], gguf_in_repo)
+
+    return None
+
+
+def main():
+    """
+    Main function to find and print the model path.
+    """
+
+    parser = argparse.ArgumentParser(
+        description="Find the full GGUF path from the Hugging Face cache."
+    )
+    parser.add_argument(
+        "model", type=str, help="The model name from Hugging Face"
+    )
+    parser.add_argument(
+        "path",
+        type=str,
+        help="The path to the GGUF file within the model repository",
+    )
+    args = parser.parse_args()
+
+    model_path = find_model_path(args.model, args.path)
+    print(model_path, end="")
+
+
+if __name__ == "__main__":
+    main()

src/requirements.txt

@@ -1,4 +1,3 @@
 runpod
 python-dotenv
 openai
-orjson==3.10.14

src/start.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 
 # fail on error:
-set -e
+set -e -o pipefail
 
 # This script starts the llama-server with the command line arguments
 # specified in the environment variable LLAMA_SERVER_CMD_ARGS, ensuring
@@ -9,19 +9,25 @@ set -e
 # script after the server is up and running.
 
 cleanup() {
-    echo "Cleaning up..."
+    echo "start.sh: Cleaning up..."
     pkill -P $$ # kill all child processes of the current script
     exit 0
 }
 
-# check if the substring /workspace is in LLAMA_SERVER_CMD_ARGS
-if [[ "$LLAMA_SERVER_CMD_ARGS" != *"/workspace"* ]]; then
-    echo "Tip: For reduced downloads and faster startup times, consider using a model stored in a network volume mounted to /workspace."
+# check if $LLAMA_SERVER_CMD_ARGS is set
+if [ -z "$LLAMA_SERVER_CMD_ARGS" ]; then
+    echo "start.sh: Warning: LLAMA_SERVER_CMD_ARGS is not set. Defaulting to -hf unsloth/gemma-3-270m-it-GGUF:IQ2_XXS --ctx-size 512 -ngl 999"
+    LLAMA_SERVER_CMD_ARGS="-hf unsloth/gemma-3-270m-it-GGUF:IQ2_XXS --ctx-size 512 -ngl 999"
 fi
 
-# check if the substring -port is in LLAMA_SERVER_CMD_ARGS and if yes, raise an error:
-if [[ "$LLAMA_SERVER_CMD_ARGS" == *"-port"* ]]; then
-    echo "Error: You must not define -port in LLAMA_SERVER_CMD_ARGS, as port 3098 is required."
+# check if the substring /workspace is in LLAMA_SERVER_CMD_ARGS
+if [[ "$LLAMA_SERVER_CMD_ARGS" != *"/workspace"* ]]; then
+    echo "start.sh: Tip: For reduced downloads and faster startup times, consider using a model stored in the RunPod cache."
+fi
+
+# check if the substring --port is in LLAMA_SERVER_CMD_ARGS and if yes, raise an error:
+if [[ "$LLAMA_SERVER_CMD_ARGS" == *"--port"* ]]; then
+    echo "start.sh: Error: You must not define --port in LLAMA_SERVER_CMD_ARGS, as port 3098 is required."
     exit 1
 fi
 
@@ -29,18 +35,27 @@ fi
 trap cleanup SIGINT SIGTERM
 
 # kill any existing llama-server processes
-pkill llama-server
+echo "start.sh: Stopping existing llama-server instances (if any)..."
+{
+    pkill llama-server 2>/dev/null
+} || {
+    echo "start.sh: No llama-server running"
+}
 
 # we have a string with all the command line arguments in the env var LLAMA_SERVER_CMD_ARGS;
-# it contains a.e. "-hf modelname -ctx_size 4096".
+# it contains a.e. "-hf modelname --ctx-size 4096 -ngl 99".
+
+echo "start.sh: Running llama-server $LLAMA_SERVER_CMD_ARGS --port 3098"
+
+touch llama.server.log
 
 # We need to pass these arguments to llama-server verbatim.
-/app/llama-server $LLAMA_SERVER_CMD_ARGS -port 3098 2>&1 | tee llama.server.log &
+LD_LIBRARY_PATH=/app /app/llama-server $LLAMA_SERVER_CMD_ARGS --port 3098 2>&1 | tee llama.server.log &
 
 LLAMA_SERVER_PID=$! # store the process ID (PID) of the background command
 
 check_server_is_running() {
-    echo "Checking if llama-server is done initializing..."
+    echo "start.sh: Checking if llama-server is done initializing..."
 
     if cat llama.server.log | grep -q "listening"; then
         return 0 # success
@@ -49,9 +64,14 @@ check_server_is_running() {
     fi
 }
 
+echo "start.sh: Waiting for llama-server to start..."
+
 # wait for the server to start
 while ! check_server_is_running; do
-    sleep 5
+    # we don't want to lose too much time, so we check very frequently
+    sleep 0.5
 done
 
+echo "start.sh: llama-server is up and running, delegating to the handler script."
+
 python -u handler.py $1