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common: llama_load_model_from_url using --model-url (#6098)

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* common: llama_load_model_from_url with libcurl dependency

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Pierrick Hymbert 2024-03-17 19:12:37 +01:00 committed by GitHub
parent cd776c37c9
commit d01b3c4c32
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GPG Key ID: B5690EEEBB952194
16 changed files with 397 additions and 55 deletions
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22
.github/workflows/build.yml vendored
View File

@ -48,6 +48,28 @@ jobs:
CC=gcc-8 make tests -j $(nproc)
make test -j $(nproc)
ubuntu-focal-make-curl:
runs-on: ubuntu-20.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v3
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential gcc-8 libcurl4-openssl-dev
- name: Build
id: make_build
env:
LLAMA_FATAL_WARNINGS: 1
LLAMA_CURL: 1
run: |
CC=gcc-8 make -j $(nproc)
ubuntu-latest-cmake:
runs-on: ubuntu-latest

20
.github/workflows/server.yml vendored
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@ -57,7 +57,8 @@ jobs:
cmake \
python3-pip \
wget \
language-pack-en
language-pack-en \
libcurl4-openssl-dev
- name: Build
id: cmake_build
@ -67,6 +68,7 @@ jobs:
cmake .. \
-DLLAMA_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build . --config ${{ matrix.build_type }} -j $(nproc) --target server
@ -101,12 +103,21 @@ jobs:
with:
fetch-depth: 0
- name: libCURL
id: get_libcurl
env:
CURL_VERSION: 8.6.0_6
run: |
curl.exe -o $env:RUNNER_TEMP/curl.zip -L "https://curl.se/windows/dl-${env:CURL_VERSION}/curl-${env:CURL_VERSION}-win64-mingw.zip"
mkdir $env:RUNNER_TEMP/libcurl
tar.exe -xvf $env:RUNNER_TEMP/curl.zip --strip-components=1 -C $env:RUNNER_TEMP/libcurl
- name: Build
id: cmake_build
run: |
mkdir build
cd build
cmake .. -DLLAMA_BUILD_SERVER=ON -DCMAKE_BUILD_TYPE=Release ;
cmake .. -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
- name: Python setup
@ -120,6 +131,11 @@ jobs:
run: |
pip install -r examples/server/tests/requirements.txt
- name: Copy Libcurl
id: prepare_libcurl
run: |
cp $env:RUNNER_TEMP/libcurl/bin/libcurl-x64.dll ./build/bin/Release/libcurl-x64.dll
- name: Tests
id: server_integration_tests
if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}

1
CMakeLists.txt
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@ -99,6 +99,7 @@ option(LLAMA_CUDA_F16 "llama: use 16 bit floats for some
set(LLAMA_CUDA_KQUANTS_ITER "2" CACHE STRING "llama: iters./thread per block for Q2_K/Q6_K")
set(LLAMA_CUDA_PEER_MAX_BATCH_SIZE "128" CACHE STRING
"llama: max. batch size for using peer access")
option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF)
option(LLAMA_HIPBLAS "llama: use hipBLAS" OFF)
option(LLAMA_HIP_UMA "llama: use HIP unified memory architecture" OFF)
option(LLAMA_CLBLAST "llama: use CLBlast" OFF)

5
Makefile
View File

@ -595,6 +595,11 @@ include scripts/get-flags.mk
CUDA_CXXFLAGS := $(BASE_CXXFLAGS) $(GF_CXXFLAGS) -Wno-pedantic
endif
ifdef LLAMA_CURL
override CXXFLAGS := $(CXXFLAGS) -DLLAMA_USE_CURL
override LDFLAGS := $(LDFLAGS) -lcurl
endif
#
# Print build information
#

13
common/CMakeLists.txt
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@ -68,6 +68,17 @@ if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endif()
set(LLAMA_COMMON_EXTRA_LIBS build_info)
# Use curl to download model url
if (LLAMA_CURL)
find_package(CURL REQUIRED)
add_definitions(-DLLAMA_USE_CURL)
include_directories(${CURL_INCLUDE_DIRS})
find_library(CURL_LIBRARY curl REQUIRED)
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY})
endif ()
target_include_directories(${TARGET} PUBLIC .)
target_compile_features(${TARGET} PUBLIC cxx_std_11)
target_link_libraries(${TARGET} PRIVATE build_info PUBLIC llama)
target_link_libraries(${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama)

238
common/common.cpp
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@ -37,6 +37,9 @@
#include <sys/stat.h>
#include <unistd.h>
#endif
#if defined(LLAMA_USE_CURL)
#include <curl/curl.h>
#endif
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
@ -50,6 +53,18 @@
#define GGML_USE_CUBLAS_SYCL_VULKAN
#endif
#if defined(LLAMA_USE_CURL)
#ifdef __linux__
#include <linux/limits.h>
#elif defined(_WIN32)
#define PATH_MAX MAX_PATH
#else
#include <sys/syslimits.h>
#endif
#define LLAMA_CURL_MAX_PATH_LENGTH PATH_MAX
#define LLAMA_CURL_MAX_HEADER_LENGTH 256
#endif // LLAMA_USE_CURL
int32_t get_num_physical_cores() {
#ifdef __linux__
// enumerate the set of thread siblings, num entries is num cores
@ -644,6 +659,13 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
}
params.model = argv[i];
}
if (arg == "-mu" || arg == "--model-url") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.model_url = argv[i];
}
if (arg == "-md" || arg == "--model-draft") {
arg_found = true;
if (++i >= argc) {
@ -1368,6 +1390,8 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" layer range to apply the control vector(s) to, start and end inclusive\n");
printf(" -m FNAME, --model FNAME\n");
printf(" model path (default: %s)\n", params.model.c_str());
printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
printf(" model download url (default: %s)\n", params.model_url.c_str());
printf(" -md FNAME, --model-draft FNAME\n");
printf(" draft model for speculative decoding\n");
printf(" -ld LOGDIR, --logdir LOGDIR\n");
@ -1613,10 +1637,222 @@ void llama_batch_add(
batch.n_tokens++;
}
#ifdef LLAMA_USE_CURL
struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model,
struct llama_model_params params) {
// Basic validation of the model_url
if (!model_url || strlen(model_url) == 0) {
fprintf(stderr, "%s: invalid model_url\n", __func__);
return NULL;
}
// Initialize libcurl globally
auto curl = curl_easy_init();
if (!curl) {
fprintf(stderr, "%s: error initializing libcurl\n", __func__);
return NULL;
}
// Set the URL, allow to follow http redirection
curl_easy_setopt(curl, CURLOPT_URL, model_url);
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
#if defined(_WIN32)
// CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of
// operating system. Currently implemented under MS-Windows.
curl_easy_setopt(curl, CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA);
#endif
// Check if the file already exists locally
struct stat model_file_info;
auto file_exists = (stat(path_model, &model_file_info) == 0);
// If the file exists, check for ${path_model}.etag or ${path_model}.lastModified files
char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
char etag_path[LLAMA_CURL_MAX_PATH_LENGTH] = {0};
snprintf(etag_path, sizeof(etag_path), "%s.etag", path_model);
char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
char last_modified_path[LLAMA_CURL_MAX_PATH_LENGTH] = {0};
snprintf(last_modified_path, sizeof(last_modified_path), "%s.lastModified", path_model);
if (file_exists) {
auto * f_etag = fopen(etag_path, "r");
if (f_etag) {
if (!fgets(etag, sizeof(etag), f_etag)) {
fprintf(stderr, "%s: unable to read file %s\n", __func__, etag_path);
} else {
fprintf(stderr, "%s: previous model file found %s: %s\n", __func__, etag_path, etag);
}
fclose(f_etag);
}
auto * f_last_modified = fopen(last_modified_path, "r");
if (f_last_modified) {
if (!fgets(last_modified, sizeof(last_modified), f_last_modified)) {
fprintf(stderr, "%s: unable to read file %s\n", __func__, last_modified_path);
} else {
fprintf(stderr, "%s: previous model file found %s: %s\n", __func__, last_modified_path,
last_modified);
}
fclose(f_last_modified);
}
}
// Send a HEAD request to retrieve the etag and last-modified headers
struct llama_load_model_from_url_headers {
char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
};
llama_load_model_from_url_headers headers;
{
typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *);
auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t {
llama_load_model_from_url_headers *headers = (llama_load_model_from_url_headers *) userdata;
const char * etag_prefix = "etag: ";
if (strncmp(buffer, etag_prefix, strlen(etag_prefix)) == 0) {
strncpy(headers->etag, buffer + strlen(etag_prefix), n_items - strlen(etag_prefix) - 2); // Remove CRLF
}
const char * last_modified_prefix = "last-modified: ";
if (strncmp(buffer, last_modified_prefix, strlen(last_modified_prefix)) == 0) {
strncpy(headers->last_modified, buffer + strlen(last_modified_prefix),
n_items - strlen(last_modified_prefix) - 2); // Remove CRLF
}
return n_items;
};
curl_easy_setopt(curl, CURLOPT_NOBODY, 1L); // will trigger the HEAD verb
curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 1L); // hide head request progress
curl_easy_setopt(curl, CURLOPT_HEADERFUNCTION, static_cast<CURLOPT_HEADERFUNCTION_PTR>(header_callback));
curl_easy_setopt(curl, CURLOPT_HEADERDATA, &headers);
CURLcode res = curl_easy_perform(curl);
if (res != CURLE_OK) {
curl_easy_cleanup(curl);
fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res));
return NULL;
}
long http_code = 0;
curl_easy_getinfo(curl, CURLINFO_RESPONSE_CODE, &http_code);
if (http_code != 200) {
// HEAD not supported, we don't know if the file has changed
// force trigger downloading
file_exists = false;
fprintf(stderr, "%s: HEAD invalid http status code received: %ld\n", __func__, http_code);
}
}
// If the ETag or the Last-Modified headers are different: trigger a new download
if (!file_exists || strcmp(etag, headers.etag) != 0 || strcmp(last_modified, headers.last_modified) != 0) {
char path_model_temporary[LLAMA_CURL_MAX_PATH_LENGTH] = {0};
snprintf(path_model_temporary, sizeof(path_model_temporary), "%s.downloadInProgress", path_model);
if (file_exists) {
fprintf(stderr, "%s: deleting previous downloaded model file: %s\n", __func__, path_model);
if (remove(path_model) != 0) {
curl_easy_cleanup(curl);
fprintf(stderr, "%s: unable to delete file: %s\n", __func__, path_model);
return NULL;
}
}
// Set the output file
auto * outfile = fopen(path_model_temporary, "wb");
if (!outfile) {
curl_easy_cleanup(curl);
fprintf(stderr, "%s: error opening local file for writing: %s\n", __func__, path_model);
return NULL;
}
typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * data, size_t size, size_t nmemb, void * fd);
auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t {
return fwrite(data, size, nmemb, (FILE *)fd);
};
curl_easy_setopt(curl, CURLOPT_NOBODY, 0L);
curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, static_cast<CURLOPT_WRITEFUNCTION_PTR>(write_callback));
curl_easy_setopt(curl, CURLOPT_WRITEDATA, outfile);
// display download progress
curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L);
// start the download
fprintf(stderr, "%s: downloading model from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__,
model_url, path_model, headers.etag, headers.last_modified);
auto res = curl_easy_perform(curl);
if (res != CURLE_OK) {
fclose(outfile);
curl_easy_cleanup(curl);
fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res));
return NULL;
}
long http_code = 0;
curl_easy_getinfo (curl, CURLINFO_RESPONSE_CODE, &http_code);
if (http_code < 200 || http_code >= 400) {
fclose(outfile);
curl_easy_cleanup(curl);
fprintf(stderr, "%s: invalid http status code received: %ld\n", __func__, http_code);
return NULL;
}
// Clean up
fclose(outfile);
// Write the new ETag to the .etag file
if (strlen(headers.etag) > 0) {
auto * etag_file = fopen(etag_path, "w");
if (etag_file) {
fputs(headers.etag, etag_file);
fclose(etag_file);
fprintf(stderr, "%s: model etag saved %s: %s\n", __func__, etag_path, headers.etag);
}
}
// Write the new lastModified to the .etag file
if (strlen(headers.last_modified) > 0) {
auto * last_modified_file = fopen(last_modified_path, "w");
if (last_modified_file) {
fputs(headers.last_modified, last_modified_file);
fclose(last_modified_file);
fprintf(stderr, "%s: model last modified saved %s: %s\n", __func__, last_modified_path,
headers.last_modified);
}
}
if (rename(path_model_temporary, path_model) != 0) {
curl_easy_cleanup(curl);
fprintf(stderr, "%s: unable to rename file: %s to %s\n", __func__, path_model_temporary, path_model);
return NULL;
}
}
curl_easy_cleanup(curl);
return llama_load_model_from_file(path_model, params);
}
#else
struct llama_model * llama_load_model_from_url(const char * /*model_url*/, const char * /*path_model*/,
struct llama_model_params /*params*/) {
fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
return nullptr;
}
#endif // LLAMA_USE_CURL
std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(gpt_params & params) {
auto mparams = llama_model_params_from_gpt_params(params);
llama_model * model = llama_load_model_from_file(params.model.c_str(), mparams);
llama_model * model = nullptr;
if (!params.model_url.empty()) {
model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams);
} else {
model = llama_load_model_from_file(params.model.c_str(), mparams);
}
if (model == NULL) {
fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
return std::make_tuple(nullptr, nullptr);

4
common/common.h
View File

@ -89,6 +89,7 @@ struct gpt_params {
struct llama_sampling_params sparams;
std::string model = "models/7B/ggml-model-f16.gguf"; // model path
std::string model_url = ""; // model url to download
std::string model_draft = ""; // draft model for speculative decoding
std::string model_alias = "unknown"; // model alias
std::string prompt = "";
@ -191,6 +192,9 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
struct llama_model_params llama_model_params_from_gpt_params (const gpt_params & params);
struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params);
struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model,
struct llama_model_params params);
// Batch utils
void llama_batch_clear(struct llama_batch & batch);

1
examples/main/README.md
View File

@ -67,6 +67,7 @@ main.exe -m models\7B\ggml-model.bin --ignore-eos -n -1 --random-prompt
In this section, we cover the most commonly used options for running the `main` program with the LLaMA models:
- `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`).
- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf).
- `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
- `-ins, --instruct`: Run the program in instruction mode, which is particularly useful when working with Alpaca models.
- `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text.

1
examples/server/README.md
View File

@ -20,6 +20,7 @@ The project is under active development, and we are [looking for feedback and co
- `-tb N, --threads-batch N`: Set the number of threads to use during batch and prompt processing. If not specified, the number of threads will be set to the number of threads used for generation.
- `--threads-http N`: number of threads in the http server pool to process requests (default: `max(std::thread::hardware_concurrency() - 1, --parallel N + 2)`)
- `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`).
- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf).
- `-a ALIAS`, `--alias ALIAS`: Set an alias for the model. The alias will be returned in API responses.
- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of 4096.
- `-ngl N`, `--n-gpu-layers N`: When compiled with appropriate support (currently CLBlast or cuBLAS), this option allows offloading some layers to the GPU for computation. Generally results in increased performance.

8
examples/server/server.cpp
View File

@ -2195,6 +2195,8 @@ static void server_print_usage(const char * argv0, const gpt_params & params, co
}
printf(" -m FNAME, --model FNAME\n");
printf(" model path (default: %s)\n", params.model.c_str());
printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
printf(" model download url (default: %s)\n", params.model_url.c_str());
printf(" -a ALIAS, --alias ALIAS\n");
printf(" set an alias for the model, will be added as `model` field in completion response\n");
printf(" --lora FNAME apply LoRA adapter (implies --no-mmap)\n");
@ -2317,6 +2319,12 @@ static void server_params_parse(int argc, char ** argv, server_params & sparams,
break;
}
params.model = argv[i];
} else if (arg == "-mu" || arg == "--model-url") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.model_url = argv[i];
} else if (arg == "-a" || arg == "--alias") {
if (++i >= argc) {
invalid_param = true;

2
examples/server/tests/README.md
View File

@ -57,7 +57,7 @@ Feature or Scenario must be annotated with `@llama.cpp` to be included in the de
To run a scenario annotated with `@bug`, start:
```shell
DEBUG=ON ./tests.sh --no-skipped --tags bug
DEBUG=ON ./tests.sh --no-skipped --tags bug --stop
```
After changing logic in `steps.py`, ensure that `@bug` and `@wrong_usage` scenario are updated.

3
examples/server/tests/features/embeddings.feature
View File

@ -4,7 +4,8 @@ Feature: llama.cpp server
Background: Server startup
Given a server listening on localhost:8080
And a model file bert-bge-small/ggml-model-f16.gguf from HF repo ggml-org/models
And a model url https://huggingface.co/ggml-org/models/resolve/main/bert-bge-small/ggml-model-f16.gguf
And a model file ggml-model-f16.gguf
And a model alias bert-bge-small
And 42 as server seed
And 2 slots

93
examples/server/tests/features/environment.py
View File

@ -1,10 +1,12 @@
import errno
import os
import socket
import subprocess
import time
from contextlib import closing
import signal
import socket
import sys
import time
import traceback
from contextlib import closing
import psutil
def before_scenario(context, scenario):
@ -20,33 +22,40 @@ def before_scenario(context, scenario):
def after_scenario(context, scenario):
if context.server_process is None:
return
if scenario.status == "failed":
if 'GITHUB_ACTIONS' in os.environ:
print(f"\x1b[33;101mSCENARIO FAILED: {scenario.name} server logs:\x1b[0m\n\n")
if os.path.isfile('llama.log'):
with closing(open('llama.log', 'r')) as f:
for line in f:
print(line)
if not is_server_listening(context.server_fqdn, context.server_port):
print("\x1b[33;101mERROR: Server stopped listening\x1b[0m\n")
try:
if 'server_process' not in context or context.server_process is None:
return
if scenario.status == "failed":
if 'GITHUB_ACTIONS' in os.environ:
print(f"\x1b[33;101mSCENARIO FAILED: {scenario.name} server logs:\x1b[0m\n\n")
if os.path.isfile('llama.log'):
with closing(open('llama.log', 'r')) as f:
for line in f:
print(line)
if not is_server_listening(context.server_fqdn, context.server_port):
print("\x1b[33;101mERROR: Server stopped listening\x1b[0m\n")
if not pid_exists(context.server_process.pid):
assert False, f"Server not running pid={context.server_process.pid} ..."
if not pid_exists(context.server_process.pid):
assert False, f"Server not running pid={context.server_process.pid} ..."
server_graceful_shutdown(context)
server_graceful_shutdown(context)
# Wait few for socket to free up
time.sleep(0.05)
# Wait few for socket to free up
time.sleep(0.05)
attempts = 0
while pid_exists(context.server_process.pid) or is_server_listening(context.server_fqdn, context.server_port):
server_kill(context)
time.sleep(0.1)
attempts += 1
if attempts > 5:
server_kill_hard(context)
attempts = 0
while pid_exists(context.server_process.pid) or is_server_listening(context.server_fqdn, context.server_port):
server_kill(context)
time.sleep(0.1)
attempts += 1
if attempts > 5:
server_kill_hard(context)
except:
exc = sys.exception()
print("error in after scenario: \n")
print(exc)
print("*** print_tb: \n")
traceback.print_tb(exc.__traceback__, file=sys.stdout)
def server_graceful_shutdown(context):
@ -67,11 +76,11 @@ def server_kill_hard(context):
path = context.server_path
print(f"Server dangling exits, hard killing force {pid}={path}...\n")
if os.name == 'nt':
process = subprocess.check_output(['taskkill', '/F', '/pid', str(pid)]).decode()
print(process)
else:
os.kill(-pid, signal.SIGKILL)
try:
psutil.Process(pid).kill()
except psutil.NoSuchProcess:
return False
return True
def is_server_listening(server_fqdn, server_port):
@ -84,17 +93,9 @@ def is_server_listening(server_fqdn, server_port):
def pid_exists(pid):
"""Check whether pid exists in the current process table."""
if pid < 0:
try:
psutil.Process(pid)
except psutil.NoSuchProcess:
return False
if os.name == 'nt':
output = subprocess.check_output(['TASKLIST', '/FI', f'pid eq {pid}']).decode()
print(output)
return "No tasks are running" not in output
else:
try:
os.kill(pid, 0)
except OSError as e:
return e.errno == errno.EPERM
else:
return True
return True

3
examples/server/tests/features/server.feature
View File

@ -4,7 +4,8 @@ Feature: llama.cpp server
Background: Server startup
Given a server listening on localhost:8080
And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
And a model url https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K.gguf
And a model file stories260K.gguf
And a model alias tinyllama-2
And 42 as server seed
# KV Cache corresponds to the total amount of tokens

37
examples/server/tests/features/steps/steps.py
View File

@ -5,6 +5,8 @@ import os
import re
import socket
import subprocess
import sys
import threading
import time
from contextlib import closing
from re import RegexFlag
@ -32,6 +34,8 @@ def step_server_config(context, server_fqdn, server_port):
context.base_url = f'http://{context.server_fqdn}:{context.server_port}'
context.model_alias = None
context.model_file = None
context.model_url = None
context.n_batch = None
context.n_ubatch = None
context.n_ctx = None
@ -65,6 +69,16 @@ def step_download_hf_model(context, hf_file, hf_repo):
print(f"model file: {context.model_file}\n")
@step('a model file {model_file}')
def step_model_file(context, model_file):
context.model_file = model_file
@step('a model url {model_url}')
def step_model_url(context, model_url):
context.model_url = model_url
@step('a model alias {model_alias}')
def step_model_alias(context, model_alias):
context.model_alias = model_alias
@ -141,7 +155,8 @@ def step_start_server(context):
async def step_wait_for_the_server_to_be_started(context, expecting_status):
match expecting_status:
case 'healthy':
await wait_for_health_status(context, context.base_url, 200, 'ok')
await wait_for_health_status(context, context.base_url, 200, 'ok',
timeout=30)
case 'ready' | 'idle':
await wait_for_health_status(context, context.base_url, 200, 'ok',
@ -1038,8 +1053,11 @@ def start_server_background(context):
server_args = [
'--host', server_listen_addr,
'--port', context.server_port,
'--model', context.model_file
]
if context.model_file:
server_args.extend(['--model', context.model_file])
if context.model_url:
server_args.extend(['--model-url', context.model_url])
if context.n_batch:
server_args.extend(['--batch-size', context.n_batch])
if context.n_ubatch:
@ -1079,8 +1097,23 @@ def start_server_background(context):
pkwargs = {
'creationflags': flags,
'stdout': subprocess.PIPE,
'stderr': subprocess.PIPE
}
context.server_process = subprocess.Popen(
[str(arg) for arg in [context.server_path, *server_args]],
**pkwargs)
def log_stdout(process):
for line in iter(process.stdout.readline, b''):
print(line.decode('utf-8'), end='')
thread_stdout = threading.Thread(target=log_stdout, args=(context.server_process,))
thread_stdout.start()
def log_stderr(process):
for line in iter(process.stderr.readline, b''):
print(line.decode('utf-8'), end='', file=sys.stderr)
thread_stderr = threading.Thread(target=log_stderr, args=(context.server_process,))
thread_stderr.start()
print(f"server pid={context.server_process.pid}, behave pid={os.getpid()}")

1
examples/server/tests/requirements.txt
View File

@ -3,4 +3,5 @@ behave~=1.2.6
huggingface_hub~=0.20.3
numpy~=1.24.4
openai~=0.25.0
psutil~=5.9.8
prometheus-client~=0.20.0