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

.env.example

@@ -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

.gitignore

@@ -1,163 +1,29 @@
-# Byte-compiled / optimized / DLL files
+# Ignore everything
-__pycache__/
+*
-*.py[cod]
-*$py.class
 
-# C extensions
+# Don't ignore directories, so we can recurse into them
-*.so
+!*/
 
-# Distribution / packaging
+# Don't ignore .gitignore
-.Python
+!.gitignore
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
 
-# PyInstaller
+# Don't ignore LICENSE
-#  Usually these files are written by a python script from a template
+!LICENSE
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
 
-# Installer logs
+# Don't ignore these files
-pip-log.txt
+!*.example
-pip-delete-this-directory.txt
+!setup.py
+!.pre-commit-config.yaml
+!run.bat
 
-# Unit test / coverage reports
+# Don't ignore .github directory
-htmlcov/
+!.github/**
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-cover/
 
-# Translations
+# Don't ignore Python files in src directory
-*.mo
+!src/**/*.py
-*.pot
 
-# Django stuff:
+# Don't ignore requirements.txt in root
-*.log
+!requirements.txt
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
 
-# Flask stuff:
+# Don't ignore Markdown files in root
-instance/
+!*.md
-.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/

.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

run.bat

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

src/get_data.py

@@ -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)

src/globals.py

@@ -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.")

src/graph.py

@@ -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)
+        for name in os.listdir(DATA_DIR)
-        if name.endswith(".sqlite") and os.path.isfile(os.path.join(data_dir, name))
+        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 = [
+        result = get_data(f"{DATA_DIR}/{selected_model}.sqlite", 24)
-            "python",
-            "get_data.py",
-            "--hours",
-            "24",
-            f".\\data\\{selected_model}.sqlite",
-        ]
-        result = subprocess.run(command, capture_output=True, text=True)
     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)

src/monitor.py

@@ -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 = {
+        headers = {"User-Agent": USER_AGENT}
-            "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"
-        }
         response = requests.get(url, headers=headers)
         response.raise_for_status()
         logging.debug(f"Received successful response from {url}")