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Improve cli (#179)

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Adil Hafeez 2024-10-10 17:44:41 -07:00 • committed by GitHub
parent ceca0dba28
commit 7d5f760884
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18 changed files with 611 additions and 445 deletions
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5
.github/workflows/checks.yml vendored
View file

@ -1,6 +1,9 @@
name: Checks name: Checks
on: pull_request on:
pull_request:
push:
branches: [main]
jobs: jobs:
test: test:

2
README.md
View file

@ -69,7 +69,7 @@ llm_providers:
- name: OpenAI - name: OpenAI
provider: openai provider: openai
access_key: OPENAI_API_KEY access_key: OPENAI_API_KEY
model: gpt-4o model: gpt-3.5-turbo
default: true default: true
stream: true stream: true

13
arch/tools/README.md
View file

@ -56,9 +56,18 @@ sh build_cli.sh
archgw build archgw build
``` ```
## Step 5: start model server in the background ### Step 5: download models
This will help download models so model_server can load faster. This should be done once.
```bash
archgw download-models
``` ```
archgw up --services model_server
### Logs
`archgw` command can also view logs from gateway and model_server. Use following command to view logs,
```bash
archgw logs --follow
``` ```
## Uninstall Instructions: archgw CLI ## Uninstall Instructions: archgw CLI

1
arch/tools/cli/consts.py Normal file
View file

@ -0,0 +1 @@
KATANEMO_DOCKERHUB_REPO = "katanemo/archgw"

67
arch/tools/cli/core.py
View file

@ -4,6 +4,37 @@ import time
import pkg_resources import pkg_resources
import select import select
from cli.utils import run_docker_compose_ps, print_service_status, check_services_state from cli.utils import run_docker_compose_ps, print_service_status, check_services_state
from cli.utils import getLogger
import sys
log = getLogger(__name__)
def stream_gateway_logs(follow):
"""
Stream logs from the arch gateway service.
"""
compose_file = pkg_resources.resource_filename(
__name__, "../config/docker-compose.yaml"
)
log.info("Logs from arch gateway service.")
options = ["docker", "compose", "-p", "arch", "logs"]
if follow:
options.append("-f")
try:
# Run `docker-compose logs` to stream logs from the gateway service
subprocess.run(
options,
cwd=os.path.dirname(compose_file),
check=True,
stdout=sys.stdout,
stderr=sys.stderr,
)
except subprocess.CalledProcessError as e:
log.info(f"Failed to stream logs: {str(e)}")
def start_arch(arch_config_file, env, log_timeout=120): def start_arch(arch_config_file, env, log_timeout=120):
@ -14,7 +45,7 @@ def start_arch(arch_config_file, env, log_timeout=120):
path (str): The path where the prompt_confi.yml file is located. path (str): The path where the prompt_confi.yml file is located.
log_timeout (int): Time in seconds to show logs before checking for healthy state. log_timeout (int): Time in seconds to show logs before checking for healthy state.
""" """
log.info("Starting arch gateway")
compose_file = pkg_resources.resource_filename( compose_file = pkg_resources.resource_filename(
__name__, "../config/docker-compose.yaml" __name__, "../config/docker-compose.yaml"
) )
@ -35,9 +66,10 @@ def start_arch(arch_config_file, env, log_timeout=120):
), # Ensure the Docker command runs in the correct path ), # Ensure the Docker command runs in the correct path
env=env, # Pass the modified environment env=env, # Pass the modified environment
check=True, # Raise an exception if the command fails check=True, # Raise an exception if the command fails
stderr=subprocess.PIPE,
stdout=subprocess.PIPE,
) )
print(f"Arch docker-compose started in detached.") log.info(f"Arch docker-compose started in detached.")
print("Monitoring `docker-compose ps` logs...")
start_time = time.time() start_time = time.time()
services_status = {} services_status = {}
@ -51,14 +83,14 @@ def start_arch(arch_config_file, env, log_timeout=120):
# Check if timeout is reached # Check if timeout is reached
if elapsed_time > log_timeout: if elapsed_time > log_timeout:
print(f"Stopping log monitoring after {log_timeout} seconds.") log.info(f"Stopping log monitoring after {log_timeout} seconds.")
break break
current_services_status = run_docker_compose_ps( current_services_status = run_docker_compose_ps(
compose_file=compose_file, env=env compose_file=compose_file, env=env
) )
if not current_services_status: if not current_services_status:
print( log.info(
"Status for the services could not be detected. Something went wrong. Please run docker logs" "Status for the services could not be detected. Something went wrong. Please run docker logs"
) )
break break
@ -74,11 +106,11 @@ def start_arch(arch_config_file, env, log_timeout=120):
running_states = ["running", "up"] running_states = ["running", "up"]
if check_services_state(current_services_status, running_states): if check_services_state(current_services_status, running_states):
print("Arch is up and running!") log.info("Arch gateway is up and running!")
break break
if check_services_state(current_services_status, unhealthy_states): if check_services_state(current_services_status, unhealthy_states):
print( log.info(
"One or more Arch services are unhealthy. Please run `docker logs` for more information" "One or more Arch services are unhealthy. Please run `docker logs` for more information"
) )
print_service_status( print_service_status(
@ -92,7 +124,7 @@ def start_arch(arch_config_file, env, log_timeout=120):
services_status[service_name]["State"] services_status[service_name]["State"]
!= current_services_status[service_name]["State"] != current_services_status[service_name]["State"]
): ):
print( log.info(
"One or more Arch services have changed state. Printing current state" "One or more Arch services have changed state. Printing current state"
) )
print_service_status(current_services_status) print_service_status(current_services_status)
@ -101,7 +133,7 @@ def start_arch(arch_config_file, env, log_timeout=120):
services_status = current_services_status services_status = current_services_status
except subprocess.CalledProcessError as e: except subprocess.CalledProcessError as e:
print(f"Failed to start Arch: {str(e)}") log.info(f"Failed to start Arch: {str(e)}")
def stop_arch(): def stop_arch():
@ -115,17 +147,21 @@ def stop_arch():
__name__, "../config/docker-compose.yaml" __name__, "../config/docker-compose.yaml"
) )
log.info("Shutting down arch gateway service.")
try: try:
# Run `docker-compose down` to shut down all services # Run `docker-compose down` to shut down all services
subprocess.run( subprocess.run(
["docker", "compose", "-p", "arch", "down"], ["docker", "compose", "-p", "arch", "down"],
cwd=os.path.dirname(compose_file), cwd=os.path.dirname(compose_file),
check=True, check=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
) )
print("Successfully shut down all services.") log.info("Successfully shut down arch gateway service.")
except subprocess.CalledProcessError as e: except subprocess.CalledProcessError as e:
print(f"Failed to shut down services: {str(e)}") log.info(f"Failed to shut down services: {str(e)}")
def start_arch_modelserver(): def start_arch_modelserver():
@ -134,12 +170,13 @@ def start_arch_modelserver():
""" """
try: try:
log.info("archgw_modelserver restart")
subprocess.run( subprocess.run(
["archgw_modelserver", "restart"], check=True, start_new_session=True ["archgw_modelserver", "restart"], check=True, start_new_session=True
) )
print("Successfull run the archgw model_server") log.info("Successfull ran model_server")
except subprocess.CalledProcessError as e: except subprocess.CalledProcessError as e:
print(f"Failed to start model_server. Please check archgw_modelserver logs") log.info(f"Failed to start model_server. Please check archgw_modelserver logs")
sys.exit(1) sys.exit(1)
@ -153,7 +190,7 @@ def stop_arch_modelserver():
["archgw_modelserver", "stop"], ["archgw_modelserver", "stop"],
check=True, check=True,
) )
print("Successfull stopped the archgw model_server") log.info("Successfull stopped the archgw model_server")
except subprocess.CalledProcessError as e: except subprocess.CalledProcessError as e:
print(f"Failed to start model_server. Please check archgw_modelserver logs") log.info(f"Failed to start model_server. Please check archgw_modelserver logs")
sys.exit(1) sys.exit(1)

120
arch/tools/cli/main.py
View file

@ -10,8 +10,17 @@ from cli.core import (
stop_arch_modelserver, stop_arch_modelserver,
start_arch, start_arch,
stop_arch, stop_arch,
stream_gateway_logs,
) )
from cli.utils import get_llm_provider_access_keys, load_env_file_to_dict from cli.utils import get_llm_provider_access_keys, load_env_file_to_dict
from cli.consts import KATANEMO_DOCKERHUB_REPO
from cli.utils import getLogger
import multiprocessing
from huggingface_hub import snapshot_download
import joblib
log = getLogger(__name__)
logo = r""" logo = r"""
_ _ _ _
@ -39,17 +48,17 @@ MODEL_SERVER_BUILD_FILE = "./model_server/pyproject.toml"
@click.command() @click.command()
@click.option( @click.option(
"--services", "--service",
default="all", default="all",
help="Services to build. Options are all, model_server, archgw. Default is all", help="Optioanl parameter to specify which service to build. Options are model_server, archgw",
) )
def build(services): def build(service):
"""Build Arch from source. Must be in root of cloned repo.""" """Build Arch from source. Must be in root of cloned repo."""
if services not in ["all", "model_server", "archgw"]: if service not in ["model_server", "archgw", "all"]:
print(f"Error: Invalid service {services}. Exiting") print(f"Error: Invalid service {service}. Exiting")
sys.exit(1) sys.exit(1)
# Check if /arch/Dockerfile exists # Check if /arch/Dockerfile exists
if services == "archgw" or services == "all": if service == "archgw" or service == "all":
if os.path.exists(ARCHGW_DOCKERFILE): if os.path.exists(ARCHGW_DOCKERFILE):
click.echo("Building archgw image...") click.echo("Building archgw image...")
try: try:
@ -60,7 +69,7 @@ def build(services):
"-f", "-f",
ARCHGW_DOCKERFILE, ARCHGW_DOCKERFILE,
"-t", "-t",
"archgw:latest", f"{KATANEMO_DOCKERHUB_REPO}:latest",
".", ".",
"--add-host=host.docker.internal:host-gateway", "--add-host=host.docker.internal:host-gateway",
], ],
@ -77,7 +86,7 @@ def build(services):
click.echo("archgw image built successfully.") click.echo("archgw image built successfully.")
"""Install the model server dependencies using Poetry.""" """Install the model server dependencies using Poetry."""
if services == "model_server" or services == "all": if service == "model_server" or service == "all":
# Check if pyproject.toml exists # Check if pyproject.toml exists
if os.path.exists(MODEL_SERVER_BUILD_FILE): if os.path.exists(MODEL_SERVER_BUILD_FILE):
click.echo("Installing model server dependencies with Poetry...") click.echo("Installing model server dependencies with Poetry...")
@ -102,17 +111,17 @@ def build(services):
"--path", default=".", help="Path to the directory containing arch_config.yaml" "--path", default=".", help="Path to the directory containing arch_config.yaml"
) )
@click.option( @click.option(
"--services", "--service",
default="all", default="all",
help="Services to start. Options are all, model_server, archgw. Default is all", help="Service to start. Options are model_server, archgw.",
) )
def up(file, path, services): def up(file, path, service):
"""Starts Arch.""" """Starts Arch."""
if services not in ["all", "model_server", "archgw"]: if service not in ["all", "model_server", "archgw"]:
print(f"Error: Invalid service {services}. Exiting") print(f"Error: Invalid service {service}. Exiting")
sys.exit(1) sys.exit(1)
if services == "model_server": if service == "model_server":
start_arch_modelserver() start_arch_modelserver()
return return
@ -142,7 +151,7 @@ def up(file, path, services):
print(f"Exiting archgw up: {e}") print(f"Exiting archgw up: {e}")
sys.exit(1) sys.exit(1)
print("Starting Arch gateway and Arch model server services via docker ") log.info("Starging arch model server and arch gateway")
# Set the ARCH_CONFIG_FILE environment variable # Set the ARCH_CONFIG_FILE environment variable
env_stage = {} env_stage = {}
@ -184,7 +193,7 @@ def up(file, path, services):
env.update(env_stage) env.update(env_stage)
env["ARCH_CONFIG_FILE"] = arch_config_file env["ARCH_CONFIG_FILE"] = arch_config_file
if services == "archgw": if service == "archgw":
start_arch(arch_config_file, env) start_arch(arch_config_file, env)
else: else:
start_arch_modelserver() start_arch_modelserver()
@ -193,19 +202,19 @@ def up(file, path, services):
@click.command() @click.command()
@click.option( @click.option(
"--services", "--service",
default="all", default="all",
help="Services to down. Options are all, model_server, archgw. Default is all", help="Service to down. Options are all, model_server, archgw. Default is all",
) )
def down(services): def down(service):
"""Stops Arch.""" """Stops Arch."""
if services not in ["all", "model_server", "archgw"]: if service not in ["all", "model_server", "archgw"]:
print(f"Error: Invalid service {services}. Exiting") print(f"Error: Invalid service {service}. Exiting")
sys.exit(1) sys.exit(1)
if services == "model_server": if service == "model_server":
stop_arch_modelserver() stop_arch_modelserver()
elif services == "archgw": elif service == "archgw":
stop_arch() stop_arch()
else: else:
stop_arch_modelserver() stop_arch_modelserver()
@ -234,9 +243,74 @@ def generate_prompt_targets(file):
targets.generate_prompt_targets(file) targets.generate_prompt_targets(file)
def stream_model_server_logs(follow):
log_file = "~/archgw_logs/modelserver.log"
log_file_expanded = os.path.expanduser(log_file)
stream_command = ["tail"]
if follow:
stream_command.append("-f")
stream_command.append(log_file_expanded)
subprocess.run(
stream_command,
check=True,
stdout=sys.stdout,
stderr=sys.stderr,
)
@click.command()
@click.option(
"--service",
default="all",
help="Service to monitor. By default it will monitor both gateway and model_serve",
)
@click.option("--follow", help="Follow the logs", is_flag=True)
def logs(service, follow):
"""Stream logs from arch services."""
if service not in ["all", "model_server", "archgw"]:
print(f"Error: Invalid service {service}. Exiting")
sys.exit(1)
archgw_process = None
if service == "archgw" or service == "all":
archgw_process = multiprocessing.Process(
target=stream_gateway_logs, args=(follow,)
)
archgw_process.start()
model_server_process = None
if service == "model_server" or service == "all":
model_server_process = multiprocessing.Process(
target=stream_model_server_logs, args=(follow,)
)
model_server_process.start()
if archgw_process:
archgw_process.join()
if model_server_process:
model_server_process.join()
model_list = [
"katanemo/Arch-Guard-cpu",
"katanemo/Arch-Guard",
"katanemo/bge-large-en-v1.5",
]
@click.command()
def download_models():
"""Download required models from Hugging Face Hub in the cache directory"""
for model in model_list:
log.info(f"Downloading model: {model}")
snapshot_download(repo_id=model)
main.add_command(up) main.add_command(up)
main.add_command(down) main.add_command(down)
main.add_command(build) main.add_command(build)
main.add_command(logs)
main.add_command(download_models)
main.add_command(generate_prompt_targets) main.add_command(generate_prompt_targets)
if __name__ == "__main__": if __name__ == "__main__":

29
arch/tools/cli/utils.py
View file

@ -5,6 +5,23 @@ import select
import shlex import shlex
import yaml import yaml
import json import json
import logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
def getLogger(name="cli"):
import logging
logger = logging.getLogger(name)
logger.setLevel(logging.INFO)
return logger
log = getLogger(__name__)
def run_docker_compose_ps(compose_file, env): def run_docker_compose_ps(compose_file, env):
@ -15,7 +32,7 @@ def run_docker_compose_ps(compose_file, env):
path (str): The path where the docker-compose.yml file is located. path (str): The path where the docker-compose.yml file is located.
""" """
try: try:
# Run `docker-compose ps` to get the health status of each service # Run `docker compose ps` to get the health status of each service
ps_process = subprocess.Popen( ps_process = subprocess.Popen(
[ [
"docker", "docker",
@ -38,7 +55,7 @@ def run_docker_compose_ps(compose_file, env):
# Check if there is any error output # Check if there is any error output
if error_output: if error_output:
print( log.info(
f"Error while checking service status:\n{error_output}", f"Error while checking service status:\n{error_output}",
file=os.sys.stderr, file=os.sys.stderr,
) )
@ -48,18 +65,18 @@ def run_docker_compose_ps(compose_file, env):
return services return services
except subprocess.CalledProcessError as e: except subprocess.CalledProcessError as e:
print(f"Failed to check service status. Error:\n{e.stderr}") log.info(f"Failed to check service status. Error:\n{e.stderr}")
return e return e
# Helper method to print service status # Helper method to print service status
def print_service_status(services): def print_service_status(services):
print(f"{'Service Name':<25} {'State':<20} {'Ports'}") log.info(f"{'Service Name':<25} {'State':<20} {'Ports'}")
print("=" * 72) log.info("=" * 72)
for service_name, info in services.items(): for service_name, info in services.items():
status = info["STATE"] status = info["STATE"]
ports = info["PORTS"] ports = info["PORTS"]
print(f"{service_name:<25} {status:<20} {ports}") log.info(f"{service_name:<25} {status:<20} {ports}")
# check for states based on the states passed in # check for states based on the states passed in

561
arch/tools/poetry.lock generated
View file

@ -44,102 +44,102 @@ files = [
[[package]] [[package]]
name = "aiohttp" name = "aiohttp"
version = "3.10.9" version = "3.10.10"
description = "Async http client/server framework (asyncio)" description = "Async http client/server framework (asyncio)"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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{file = "aiohttp-3.10.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:91aa966858593f64c8a65cdefa3d6dc8fe3c2768b159da84c1ddbbb2c01ab4ef"}, {file = "aiohttp-3.10.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7b06b7843929e41a94ea09eb1ce3927865387e3e23ebe108e0d0d09b08d25be9"},
{file = "aiohttp-3.10.9-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:63649309da83277f06a15bbdc2a54fbe75efb92caa2c25bb57ca37762789c746"}, {file = "aiohttp-3.10.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:333cf6cf8e65f6a1e06e9eb3e643a0c515bb850d470902274239fea02033e9a8"},
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dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"] dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.20,<0.21)", "urllib3 (<2.0.0)"]
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"] flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
ftfy = ["ftfy"] ftfy = ["ftfy"]
@ -3160,7 +3170,7 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"] onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"] onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
optuna = ["optuna"] optuna = ["optuna"]
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.5.1)", "urllib3 (<2.0.0)"] quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "libcst", "rich", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
ray = ["ray[tune] (>=2.7.0)"] ray = ["ray[tune] (>=2.7.0)"]
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"] retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
ruff = ["ruff (==0.5.1)"] ruff = ["ruff (==0.5.1)"]
@ -3170,16 +3180,17 @@ serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
sigopt = ["sigopt"] sigopt = ["sigopt"]
sklearn = ["scikit-learn"] sklearn = ["scikit-learn"]
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"] tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
tiktoken = ["blobfile", "tiktoken"]
timm = ["timm (<=0.9.16)"] timm = ["timm (<=0.9.16)"]
tokenizers = ["tokenizers (>=0.19,<0.20)"] tokenizers = ["tokenizers (>=0.20,<0.21)"]
torch = ["accelerate (>=0.21.0)", "torch"] torch = ["accelerate (>=0.26.0)", "torch"]
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"] torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
video = ["av (==9.2.0)", "decord (==0.6.0)"] video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow (>=10.0.1,<=15.0)"] vision = ["Pillow (>=10.0.1,<=15.0)"]
@ -3521,4 +3532,4 @@ propcache = ">=0.2.0"
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.10" python-versions = "^3.10"
content-hash = "11509af5007ffed46d1a84a53de8fb2f816eca24247064b2d85560e80d5eaf24" content-hash = "35ffc7511fb162b24cc24f3d2884128b8e34b68c42811eba4f878479d98b55b7"

5
arch/tools/pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "archgw" name = "archgw"
version = "0.0.1" version = "0.0.3"
description = "Python-based CLI tool to manage Arch Gateway." description = "Python-based CLI tool to manage Arch Gateway."
authors = ["Katanemo Labs, Inc."] authors = ["Katanemo Labs, Inc."]
packages = [ packages = [
@ -22,7 +22,8 @@ click = "^8.1.7"
jinja2 = "^3.1.4" jinja2 = "^3.1.4"
jsonschema = "^4.23.0" jsonschema = "^4.23.0"
setuptools = "75.1.0" setuptools = "75.1.0"
archgw_modelserver= "0.0.2" archgw_modelserver= "0.0.3"
huggingface_hub = "^0.25.2"
[tool.poetry.scripts] [tool.poetry.scripts]
archgw = "cli.main:main" archgw = "cli.main:main"

4
demos/function_calling/arch_config.yaml
View file

@ -16,10 +16,10 @@ overrides:
prompt_target_intent_matching_threshold: 0.6 prompt_target_intent_matching_threshold: 0.6
llm_providers: llm_providers:
- name: gpt-4o - name: gpt
access_key: OPENAI_API_KEY access_key: OPENAI_API_KEY
provider: openai provider: openai
model: gpt-4o model: gpt-3.5-turbo
default: true default: true
system_prompt: | system_prompt: |

2
demos/network_agent/arch_config.yaml
View file

@ -9,7 +9,7 @@ llm_providers:
- name: OpenAI - name: OpenAI
provider: openai provider: openai
access_key: OPENAI_API_KEY access_key: OPENAI_API_KEY
model: gpt-4o model: gpt-3.5-turbo
default: true default: true
# default system prompt used by all prompt targets # default system prompt used by all prompt targets

2
docs/source/build_with_arch/includes/agent/function-calling-agent.yaml
View file

@ -9,7 +9,7 @@ llm_providers:
- name: OpenAI - name: OpenAI
provider: openai provider: openai
access_key: OPENAI_API_KEY access_key: OPENAI_API_KEY
model: gpt-4o model: gpt-3.5-turbo
default: true default: true
# default system prompt used by all prompt targets # default system prompt used by all prompt targets

107
model_server/app/__init__.py
View file

@ -1,107 +0,0 @@
import sys
import os
import time
import requests
import psutil
import tempfile
import subprocess
# Path to the file where the server process ID will be stored
PID_FILE = os.path.join(tempfile.gettempdir(), "model_server.pid")
def run_server():
"""Start, stop, or restart the Uvicorn server based on command-line arguments."""
if len(sys.argv) > 1:
action = sys.argv[1]
else:
action = "start"
if action == "start":
start_server()
elif action == "stop":
stop_server()
elif action == "restart":
restart_server()
else:
print(f"Unknown action: {action}")
sys.exit(1)
def start_server():
"""Start the Uvicorn server and save the process ID."""
if os.path.exists(PID_FILE):
print("Server is already running. Use 'model_server restart' to restart it.")
sys.exit(1)
print(
"Starting Archgw Model Server - Loading some awesomeness, this may take a little time.)"
)
process = subprocess.Popen(
["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "51000"],
start_new_session=True,
stdout=subprocess.DEVNULL, # Suppress standard output. There is a logger that model_server prints to
stderr=subprocess.DEVNULL, # Suppress standard error. There is a logger that model_server prints to
)
if wait_for_health_check("http://0.0.0.0:51000/healthz"):
# Write the process ID to the PID file
with open(PID_FILE, "w") as f:
f.write(str(process.pid))
print(f"Archgw Model Server started with PID {process.pid}")
else:
# Add model_server boot-up logs
print("Archgw Model Server - Didn't Sart In Time. Shutting Down")
process.terminate()
def wait_for_health_check(url, timeout=180):
"""Wait for the Uvicorn server to respond to health-check requests."""
start_time = time.time()
while time.time() - start_time < timeout:
try:
response = requests.get(url)
if response.status_code == 200:
return True
except requests.ConnectionError:
time.sleep(1)
print("Timed out waiting for Archgw Model Server to respond.")
return False
def stop_server():
"""Stop the running Uvicorn server."""
if not os.path.exists(PID_FILE):
print("Status: Archgw Model Server not running")
return
# Read the process ID from the PID file
with open(PID_FILE, "r") as f:
pid = int(f.read())
try:
# Get process by PID
process = psutil.Process(pid)
# Gracefully terminate the process
process.terminate() # Sends SIGTERM by default
process.wait(timeout=10) # Wait for up to 10 seconds for the process to exit
print(f"Server with PID {pid} stopped.")
os.remove(PID_FILE)
except psutil.NoSuchProcess:
print(f"Process with PID {pid} not found. Cleaning up PID file.")
os.remove(PID_FILE)
except psutil.TimeoutExpired:
print(f"Process with PID {pid} did not terminate in time. Forcing shutdown.")
process.kill() # Forcefully kill the process
os.remove(PID_FILE)
def restart_server():
"""Restart the Uvicorn server."""
print("Check: Is Archgw Model Server running?")
stop_server()
start_server()

119
model_server/app/cli.py Normal file
View file

@ -0,0 +1,119 @@
import sys
import os
import time
import requests
import psutil
import tempfile
import subprocess
import logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
log = logging.getLogger("model_server.cli")
log.setLevel(logging.INFO)
# Path to the file where the server process ID will be stored
PID_FILE = os.path.join(tempfile.gettempdir(), "model_server.pid")
def run_server():
"""Start, stop, or restart the Uvicorn server based on command-line arguments."""
if len(sys.argv) > 1:
action = sys.argv[1]
else:
action = "start"
if action == "start":
start_server()
elif action == "stop":
stop_server()
elif action == "restart":
restart_server()
else:
log.info(f"Unknown action: {action}")
sys.exit(1)
def start_server():
"""Start the Uvicorn server and save the process ID."""
if os.path.exists(PID_FILE):
log.info("Server is already running. Use 'model_server restart' to restart it.")
sys.exit(1)
log.info(
"Starting model server - loading some awesomeness, this may take some time :)"
)
process = subprocess.Popen(
["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "51000"],
start_new_session=True,
bufsize=1,
universal_newlines=True,
stdout=subprocess.PIPE, # Suppress standard output. There is a logger that model_server prints to
stderr=subprocess.PIPE, # Suppress standard error. There is a logger that model_server prints to
)
if wait_for_health_check("http://0.0.0.0:51000/healthz"):
# Write the process ID to the PID file
with open(PID_FILE, "w") as f:
f.write(str(process.pid))
log.info(f"Model server started with PID {process.pid}")
else:
# Add model_server boot-up logs
log.info("Model server - Didn't Sart In Time. Shutting Down")
process.terminate()
def wait_for_health_check(url, timeout=180):
"""Wait for the Uvicorn server to respond to health-check requests."""
start_time = time.time()
while time.time() - start_time < timeout:
try:
response = requests.get(url)
if response.status_code == 200:
return True
except requests.ConnectionError:
time.sleep(1)
print("Timed out waiting for model server to respond.")
return False
def stop_server():
"""Stop the running Uvicorn server."""
log.info("Stopping model server")
if not os.path.exists(PID_FILE):
log.info("Process id file not found, seems like model server was not running")
return
# Read the process ID from the PID file
with open(PID_FILE, "r") as f:
pid = int(f.read())
try:
# Get process by PID
process = psutil.Process(pid)
# Gracefully terminate the process
process.terminate() # Sends SIGTERM by default
process.wait(timeout=10) # Wait for up to 10 seconds for the process to exit
log.info(f"Model server with PID {pid} stopped.")
os.remove(PID_FILE)
except psutil.NoSuchProcess:
log.info(f"Model server with PID {pid} not found. Cleaning up PID file.")
os.remove(PID_FILE)
except psutil.TimeoutExpired:
log.info(
f"Model server with PID {pid} did not terminate in time. Forcing shutdown."
)
process.kill() # Forcefully kill the process
os.remove(PID_FILE)
def restart_server():
"""Restart the Uvicorn server."""
stop_server()
start_server()

2
model_server/app/commons/constants.py
View file

@ -5,6 +5,7 @@ import app.loader as loader
from app.function_calling.model_handler import ArchFunctionHandler from app.function_calling.model_handler import ArchFunctionHandler
from app.prompt_guard.model_handler import ArchGuardHanlder from app.prompt_guard.model_handler import ArchGuardHanlder
logger = utils.get_model_server_logger()
arch_function_hanlder = ArchFunctionHandler() arch_function_hanlder = ArchFunctionHandler()
arch_function_endpoint = "https://api.fc.archgw.com/v1" arch_function_endpoint = "https://api.fc.archgw.com/v1"
@ -19,7 +20,6 @@ arch_function_generation_params = {
arch_guard_model_type = {"cpu": "katanemo/Arch-Guard-cpu", "gpu": "katanemo/Arch-Guard"} arch_guard_model_type = {"cpu": "katanemo/Arch-Guard-cpu", "gpu": "katanemo/Arch-Guard"}
# Model definition # Model definition
embedding_model = loader.get_embedding_model() embedding_model = loader.get_embedding_model()
zero_shot_model = loader.get_zero_shot_model() zero_shot_model = loader.get_zero_shot_model()

9
model_server/app/loader.py
View file

@ -6,12 +6,15 @@ from optimum.onnxruntime import (
ORTModelForFeatureExtraction, ORTModelForFeatureExtraction,
ORTModelForSequenceClassification, ORTModelForSequenceClassification,
) )
import app.commons.utilities as utils
logger = utils.get_model_server_logger()
def get_embedding_model( def get_embedding_model(
model_name=os.getenv("MODELS", "katanemo/bge-large-en-v1.5"), model_name=os.getenv("MODELS", "katanemo/bge-large-en-v1.5"),
): ):
print("Loading Embedding Model...") logger.info("Loading Embedding Model...")
if glb.DEVICE != "cuda": if glb.DEVICE != "cuda":
model = ORTModelForFeatureExtraction.from_pretrained( model = ORTModelForFeatureExtraction.from_pretrained(
@ -32,7 +35,7 @@ def get_embedding_model(
def get_zero_shot_model( def get_zero_shot_model(
model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/bart-large-mnli"), model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/bart-large-mnli"),
): ):
print("Loading Zero-shot Model...") logger.info("Loading Zero-shot Model...")
if glb.DEVICE != "cuda": if glb.DEVICE != "cuda":
model = ORTModelForSequenceClassification.from_pretrained( model = ORTModelForSequenceClassification.from_pretrained(
@ -58,7 +61,7 @@ def get_zero_shot_model(
def get_prompt_guard(model_name, hardware_config="cpu"): def get_prompt_guard(model_name, hardware_config="cpu"):
print("Loading Guard Model...") logger.info("Loading Guard Model...")
if hardware_config == "cpu": if hardware_config == "cpu":
from optimum.intel import OVModelForSequenceClassification from optimum.intel import OVModelForSequenceClassification

4
model_server/app/main.py
View file

@ -4,7 +4,6 @@ import app.commons.utilities as utils
import app.commons.globals as glb import app.commons.globals as glb
import app.prompt_guard.model_utils as guard_utils import app.prompt_guard.model_utils as guard_utils
from typing import List, Dict from typing import List, Dict
from pydantic import BaseModel from pydantic import BaseModel
from fastapi import FastAPI, Response, HTTPException from fastapi import FastAPI, Response, HTTPException
@ -17,8 +16,7 @@ from app.function_calling.model_utils import (
logger = utils.get_model_server_logger() logger = utils.get_model_server_logger()
logger.info(f"Devices Avialble: {glb.DEVICE}") logger.info(f"Ready to serve traffic. available device: {glb.DEVICE}")
app = FastAPI() app = FastAPI()

4
model_server/pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "archgw_modelserver" name = "archgw_modelserver"
version = "0.0.2" version = "0.0.3"
description = "A model server for serving models" description = "A model server for serving models"
authors = ["Katanemo Labs, Inc <archgw@katanemo.com>"] authors = ["Katanemo Labs, Inc <archgw@katanemo.com>"]
license = "Apache 2.0" license = "Apache 2.0"
@ -31,7 +31,7 @@ onnx = "1.17.0"
onnxruntime = "1.19.2" onnxruntime = "1.19.2"
[tool.poetry.scripts] [tool.poetry.scripts]
archgw_modelserver = "app:run_server" archgw_modelserver = "app.cli:run_server"
[build-system] [build-system]
requires = ["poetry-core>=1.0.0"] requires = ["poetry-core>=1.0.0"]