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vAnalytics
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feat(config): add configuration options 

- add configuration options via environment variables
- move get_data.py functionality to graph.py to avoid using subprocess
- update .gitignore
- update .env.example
- create globals.py to store helper functions
- add run.bat to start and configure program
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BuildTools 2024-09-22 09:31:12 -07:00
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commit 9a94d5bbda
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8 changed files with 207 additions and 318 deletions
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7
.env.example Normal file
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@ -0,0 +1,7 @@
HOST=0.0.0.0
PORT=4421
DATA_DIR=./data
MODEL_CONFIG=./models.json
MODEL_DIRECTORY=
UPDATE_INTERVAL=30
LOG_LEVEL=WARNING

176
.gitignore vendored
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@ -1,163 +1,29 @@
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# Ignore everything
*
# C extensions
*.so
# Don't ignore directories, so we can recurse into them
!*/
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# Don't ignore .gitignore
!.gitignore
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Don't ignore LICENSE
!LICENSE
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Don't ignore these files
!*.example
!setup.py
!.pre-commit-config.yaml
!run.bat
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Don't ignore .github directory
!.github/**
# Translations
*.mo
*.pot
# Don't ignore Python files in src directory
!src/**/*.py
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Don't ignore requirements.txt in root
!requirements.txt
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
.pdm.toml
.pdm-python
.pdm-build/
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
.idea/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
# Don't ignore Markdown files in root
!*.md

3
.idea/.gitignore vendored Normal file
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@ -0,0 +1,3 @@
# Default ignored files
/shelf/
/workspace.xml

6
run.bat Normal file
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@ -0,0 +1,6 @@
@echo off
echo Starting monitor...
start python ./src/monitor.py
echo Starting web UI...
start python ./src/graph.py
pause

138
src/get_data.py
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@ -1,138 +0,0 @@
import os
import json
import argparse
import sqlite3
from datetime import datetime, timedelta
def get_latest_rows(db_file, hours=1):
now = datetime.now()
one_hour_ago = now - timedelta(hours=hours)
one_hour_ago_timestamp = int(one_hour_ago.timestamp())
conn = sqlite3.connect(db_file)
cursor = conn.cursor()
cursor.execute(
f"SELECT timestamp, data FROM json_data WHERE timestamp >= {one_hour_ago_timestamp} ORDER BY timestamp DESC"
)
rows = cursor.fetchall()
conn.close()
if not rows:
print(
f"No rows found in the last {hours} hour(s). Showing info for last 5 rows:"
)
conn = sqlite3.connect(db_file)
cursor = conn.cursor()
cursor.execute(
f"SELECT timestamp, data FROM json_data ORDER BY timestamp DESC LIMIT 5"
)
rows = cursor.fetchall()
conn.close()
for timestamp, _ in rows:
print(f" {datetime.fromtimestamp(timestamp)}")
return rows
def extract_stats(data_json):
try:
data = json.loads(data_json)
total_prompt_tokens = float(data["vllm:prompt_tokens_total"][0]["value"])
total_generation_tokens = float(
data["vllm:generation_tokens_total"][0]["value"]
)
total_requests = sum(
float(item["value"]) for item in data["vllm:request_success_total"]
)
avg_prompt_throughput = float(
data["vllm:avg_prompt_throughput_toks_per_s"][0]["value"]
)
avg_generation_throughput = float(
data["vllm:avg_generation_throughput_toks_per_s"][0]["value"]
)
gpu_cache_usage_perc = float(data["vllm:gpu_cache_usage_perc"][0]["value"])
num_requests_running = float(data["vllm:num_requests_running"][0]["value"])
except (KeyError, IndexError, json.JSONDecodeError) as e:
print(f"Error extracting stats from data: {str(e)}")
return None
return {
"total_prompt_tokens": total_prompt_tokens,
"total_generation_tokens": total_generation_tokens,
"total_requests": total_requests,
"avg_prompt_throughput": avg_prompt_throughput,
"avg_generation_throughput": avg_generation_throughput,
"gpu_cache_usage_perc": gpu_cache_usage_perc,
"num_requests_running": num_requests_running,
}
def main(db_file, hours):
latest_rows = get_latest_rows(db_file, hours)
if not latest_rows:
print(f"No rows found for the last {hours} hour(s).")
return
print(f"Processing {len(latest_rows)} rows.")
valid_stats = [
extract_stats(data)
for _, data in latest_rows
if extract_stats(data) is not None
]
if not valid_stats:
print("No valid statistics could be extracted from the rows.")
return
first_stats = valid_stats[-1] # Oldest row
last_stats = valid_stats[0] # Newest row
tokens_processed = (
last_stats["total_prompt_tokens"]
- first_stats["total_prompt_tokens"]
+ last_stats["total_generation_tokens"]
- first_stats["total_generation_tokens"]
)
requests_processed = last_stats["total_requests"] - first_stats["total_requests"]
avg_prompt_throughput = sum(
stat["avg_prompt_throughput"] for stat in valid_stats
) / len(valid_stats)
avg_generation_throughput = sum(
stat["avg_generation_throughput"] for stat in valid_stats
) / len(valid_stats)
avg_num_requests_running = sum(
stat["num_requests_running"] for stat in valid_stats
) / len(valid_stats)
avg_gpu_cache_usage_perc = sum(
stat["gpu_cache_usage_perc"] for stat in valid_stats
) / len(valid_stats)
print(f"\nStats for the last {hours} hour(s):")
print(f"Tokens processed: {tokens_processed:,.0f}")
print(f"Requests processed: {requests_processed:,.0f}")
print(f"Average prompt throughput: {avg_prompt_throughput:.2f} tokens/s")
print(f"Average generation throughput: {avg_generation_throughput:.2f} tokens/s")
print(
f"Average number of requests running: {avg_num_requests_running:.2f} requests"
)
print(f"Average GPU cache usage percent: {avg_gpu_cache_usage_perc * 100:.2f}%")
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract stats from a SQLite database for a specified time period"
)
parser.add_argument("db_file", help="Path to the SQLite database file")
parser.add_argument(
"--hours", type=int, default=1, help="Number of hours to look back (default: 1)"
)
args = parser.parse_args()
main(args.db_file, args.hours)

14
src/globals.py Normal file
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@ -0,0 +1,14 @@
import os
# Load environment variables from .env file
def load_env():
try:
with open(".env") as f:
for line in f:
line = line.strip()
if line and not line.startswith("#"):
key, value = line.split("=", 1)
os.environ[key.strip()] = value.strip()
except FileNotFoundError:
print("No .env file found. Using default environment variables.")

164
src/graph.py
View File

@ -3,7 +3,6 @@ import json
import logging
import os
import sqlite3
import subprocess
import threading
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
@ -14,9 +13,21 @@ import plotly.offline as pyo
from flask import Flask, render_template, request, send_file
from plotly.subplots import make_subplots
# Set up logging with a higher level
from globals import load_env
load_env()
# Configuration
HOST = os.getenv("HOST", "0.0.0.0")
PORT = int(os.getenv("PORT", 4421))
DATA_DIR = os.getenv("DATA_DIR", "./data")
UPDATE_INTERVAL = int(os.getenv("UPDATE_INTERVAL", 30))
LOG_LEVEL = os.getenv("LOG_LEVEL", "WARNING")
# Set up logging
logging.basicConfig(
level=logging.WARNING, # Changed from DEBUG to WARNING
level=getattr(logging, LOG_LEVEL),
format="%(asctime)s - %(levelname)s - %(message)s",
)
@ -75,12 +86,10 @@ async def load_data_from_db(filepath):
async def load_data():
data_dir = "./data"
tasks = []
for filename in os.listdir(data_dir):
for filename in os.listdir(DATA_DIR):
if filename.endswith(".sqlite"):
filepath = os.path.join(data_dir, filename)
filepath = os.path.join(DATA_DIR, filename)
tasks.append(load_data_from_db(filepath))
await asyncio.gather(*tasks)
@ -94,7 +103,7 @@ async def load_data():
async def background_data_loader():
while True:
await load_data()
await asyncio.sleep(30) # Check for updates every 30 seconds
await asyncio.sleep(UPDATE_INTERVAL)
def start_background_loop(loop):
@ -235,16 +244,136 @@ def create_plots(selected_model):
return fig
def get_latest_rows(db_file, hours=1):
now = datetime.now()
one_hour_ago = now - timedelta(hours=hours)
one_hour_ago_timestamp = int(one_hour_ago.timestamp())
conn = sqlite3.connect(db_file)
cursor = conn.cursor()
cursor.execute(
f"SELECT timestamp, data FROM json_data WHERE timestamp >= {one_hour_ago_timestamp} ORDER BY timestamp DESC"
)
rows = cursor.fetchall()
conn.close()
if not rows:
print(
f"No rows found in the last {hours} hour(s). Showing info for last 5 rows:"
)
conn = sqlite3.connect(db_file)
cursor = conn.cursor()
cursor.execute(
f"SELECT timestamp, data FROM json_data ORDER BY timestamp DESC LIMIT 5"
)
rows = cursor.fetchall()
conn.close()
for timestamp, _ in rows:
print(f" {datetime.fromtimestamp(timestamp)}")
return rows
def extract_stats(data_json):
try:
data = json.loads(data_json)
total_prompt_tokens = float(data["vllm:prompt_tokens_total"][0]["value"])
total_generation_tokens = float(
data["vllm:generation_tokens_total"][0]["value"]
)
total_requests = sum(
float(item["value"]) for item in data["vllm:request_success_total"]
)
avg_prompt_throughput = float(
data["vllm:avg_prompt_throughput_toks_per_s"][0]["value"]
)
avg_generation_throughput = float(
data["vllm:avg_generation_throughput_toks_per_s"][0]["value"]
)
gpu_cache_usage_perc = float(data["vllm:gpu_cache_usage_perc"][0]["value"])
num_requests_running = float(data["vllm:num_requests_running"][0]["value"])
except (KeyError, IndexError, json.JSONDecodeError) as e:
print(f"Error extracting stats from data: {str(e)}")
return None
return {
"total_prompt_tokens": total_prompt_tokens,
"total_generation_tokens": total_generation_tokens,
"total_requests": total_requests,
"avg_prompt_throughput": avg_prompt_throughput,
"avg_generation_throughput": avg_generation_throughput,
"gpu_cache_usage_perc": gpu_cache_usage_perc,
"num_requests_running": num_requests_running,
}
def get_data(db_file, hours):
latest_rows = get_latest_rows(db_file, hours)
if not latest_rows:
print(f"No rows found for the last {hours} hour(s).")
return
print(f"Processing {len(latest_rows)} rows.")
valid_stats = [
extract_stats(data)
for _, data in latest_rows
if extract_stats(data) is not None
]
if not valid_stats:
print("No valid statistics could be extracted from the rows.")
return
first_stats = valid_stats[-1] # Oldest row
last_stats = valid_stats[0] # Newest row
tokens_processed = (
last_stats["total_prompt_tokens"]
- first_stats["total_prompt_tokens"]
+ last_stats["total_generation_tokens"]
- first_stats["total_generation_tokens"]
)
requests_processed = last_stats["total_requests"] - first_stats["total_requests"]
avg_prompt_throughput = sum(
stat["avg_prompt_throughput"] for stat in valid_stats
) / len(valid_stats)
avg_generation_throughput = sum(
stat["avg_generation_throughput"] for stat in valid_stats
) / len(valid_stats)
avg_num_requests_running = sum(
stat["num_requests_running"] for stat in valid_stats
) / len(valid_stats)
avg_gpu_cache_usage_perc = sum(
stat["gpu_cache_usage_perc"] for stat in valid_stats
) / len(valid_stats)
return (
f"\nStats for the last {hours} hour(s):\n"
f"Tokens processed: {tokens_processed:,.0f}\n"
f"Requests processed: {requests_processed:,.0f}\n"
f"Average prompt throughput: {avg_prompt_throughput:.2f} tokens/s\n"
f"Average generation throughput: {avg_generation_throughput:.2f} tokens/s\n"
f"Average tokens per request: {tokens_processed/requests_processed:,.2f} tokens\n"
f"Average number of requests running: {avg_num_requests_running:.2f} requests\n"
f"Average GPU cache usage percent: {avg_gpu_cache_usage_perc * 100:.2f}%"
)
app = Flask(__name__)
@app.route("/", methods=["GET", "POST"])
def index():
data_dir = "./data"
model_names = [
name[:-7]
for name in os.listdir(data_dir)
if name.endswith(".sqlite") and os.path.isfile(os.path.join(data_dir, name))
for name in os.listdir(DATA_DIR)
if name.endswith(".sqlite") and os.path.isfile(os.path.join(DATA_DIR, name))
]
valid_model_names = set(model_names)
@ -269,14 +398,7 @@ def index():
"An error occurred while creating the plot. Please try again later."
)
command = [
"python",
"get_data.py",
"--hours",
"24",
f".\\data\\{selected_model}.sqlite",
]
result = subprocess.run(command, capture_output=True, text=True)
result = get_data(f"{DATA_DIR}/{selected_model}.sqlite", 24)
else:
logging.error(f"Invalid model selected: {selected_model}")
result = None
@ -286,7 +408,7 @@ def index():
plot_div=plot_div,
model_name=selected_model,
model_names=model_names,
result=result.stdout if result else None,
result=result,
error_message=error_message,
)
@ -317,4 +439,4 @@ if __name__ == "__main__":
t.start()
asgi_app = WsgiToAsgi(app)
uvicorn.run(asgi_app, host="0.0.0.0", port=4421)
uvicorn.run(asgi_app, host=HOST, port=PORT)

17
src/monitor.py
View File

@ -6,6 +6,8 @@ from datetime import datetime
import logging
import sqlite3
from globals import load_env
# Set up basic configuration for logging
logging.basicConfig(
level=logging.DEBUG,
@ -16,8 +18,17 @@ logging.basicConfig(
print("Starting monitor.")
load_env()
# Configuration
USER_AGENT = os.getenv(
"USER_AGENT",
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36",
)
MODEL_CONFIG = os.getenv("MODEL_CONFIG", "./models.json")
# Load model info
with open("models.json", "r") as file:
with open(MODEL_CONFIG, "r") as file:
models = json.load(file)
@ -25,9 +36,7 @@ def call_metrics_endpoint(model_name, base_url):
url = f"{base_url}/metrics"
logging.debug(f"Calling metrics endpoint: {url}")
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"
}
headers = {"User-Agent": USER_AGENT}
response = requests.get(url, headers=headers)
response.raise_for_status()
logging.debug(f"Received successful response from {url}")