neurify-tokenwatch 0.1.1

TokenWatch by Neurify — Track, alert, and control your LLM API spending across OpenAI, Anthropic, and Gemini

🔭 TokenWatch

by Neurify

Track, alert, and control your LLM API spending — across OpenAI, Anthropic & Gemini

TokenWatch is Neurify's first open-source tool — a lightweight Python package that wraps your existing LLM clients transparently, tracks every token consumed, calculates real-time costs, enforces budget limits, and fires alerts before you overspend.

Zero code changes to your existing LLM calls. Just wrap, and watch.

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✨ Features

• 🔌 Zero-change integration — wrap your existing client, all calls tracked automatically
• 💰 Real-time cost tracking — per call, session, daily, monthly, all-time
• 🚨 Smart alerts — console, webhook, Slack, email, custom callbacks
• 🛡️ Budget enforcement — warn, raise error, or block when limits are hit
• 📊 13 models supported — OpenAI, Anthropic, Claude, Gemini
• 💾 SQLite persistence — local cost history, exportable to CSV
• 🖥️ CLI dashboard — tokenwatch report, tokenwatch history, tokenwatch models
• ➕ Custom models — add any model with your own pricing

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🚀 Installation

# All providers
pip install neurify-tokenwatch[all]

# Individual providers
pip install neurify-tokenwatch[openai]
pip install neurify-tokenwatch[anthropic]
pip install neurify-tokenwatch[gemini]

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⚡ Quick Start

OpenAI

import openai
from tokenwatch import CostTracker, Budget

tracker = CostTracker(
    budget=Budget(daily_limit=1.00, alert_threshold=0.80, on_exceed="warn")
)
client = tracker.wrap_openai(openai.OpenAI(api_key="sk-..."))

# Use exactly like normal OpenAI — zero code change
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(f"Session cost : ${tracker.get_session_cost():.6f}")
print(f"Daily cost   : ${tracker.get_daily_cost():.6f}")

Anthropic

import anthropic
from tokenwatch import CostTracker, Budget

tracker = CostTracker(budget=Budget(daily_limit=2.00, on_exceed="warn"))
client = tracker.wrap_anthropic(anthropic.Anthropic(api_key="sk-ant-..."))

response = client.messages.create(
    model="claude-haiku-4-5",
    max_tokens=100,
    messages=[{"role": "user", "content": "Hello!"}]
)

print(f"Session cost : ${tracker.get_session_cost():.6f}")

Gemini

import google.generativeai as genai
from tokenwatch import CostTracker

genai.configure(api_key="AI...")
tracker = CostTracker()
model = tracker.wrap_gemini(genai.GenerativeModel("gemini-1.5-flash"))

response = model.generate_content("Hello!")
print(f"Session cost : ${tracker.get_session_cost():.6f}")

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🛡️ Budget Enforcement

from tokenwatch import CostTracker, Budget, BudgetExceededError

# Warn mode — alert and continue
tracker = CostTracker(budget=Budget(
    daily_limit=1.00,
    monthly_limit=20.00,
    session_limit=0.50,
    alert_threshold=0.80,   # alert at 80%
    on_exceed="warn"
))

# Raise mode — throws BudgetExceededError
tracker = CostTracker(budget=Budget(session_limit=0.01, on_exceed="raise"))
try:
    client.chat.completions.create(...)
except BudgetExceededError as e:
    print(f"Over budget! Spent ${e.spent:.4f} of ${e.limit:.4f} ({e.period})")

# Block mode — stops the call entirely
tracker = CostTracker(budget=Budget(monthly_limit=50.00, on_exceed="block"))

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🔔 Alert System

from tokenwatch import AlertManager, CostTracker

alert_mgr = AlertManager()

# Console (default — rich colored panels)
alert_mgr.add_console_handler(level="WARNING")

# Custom callback
def my_alert(alert_type, message, data):
    print(f"[{alert_type}] {message}")
alert_mgr.add_callback_handler(my_alert)

# Webhook (Slack, Discord, etc.)
alert_mgr.add_webhook_handler("https://hooks.slack.com/...")

# Email
alert_mgr.add_email_handler(
    smtp_config={"host": "smtp.gmail.com", "port": 587, "user": "x", "password": "y"},
    to_email="[e-mail]"
)

tracker = CostTracker(alert_manager=alert_mgr, spike_threshold=0.05)

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📊 Cost Queries

tracker.get_session_cost()    # current session
tracker.get_daily_cost()      # today (UTC)
tracker.get_monthly_cost()    # this month
tracker.get_total_cost()      # all time
tracker.get_summary()         # full breakdown dict
tracker.export_report("costs.csv")  # export to CSV

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🎨 Usage Patterns

Decorator

@tracker.watch
def run_pipeline():
    client.chat.completions.create(...)
    client.chat.completions.create(...)

run_pipeline()
# prints: [tokenwatch] run_pipeline used $0.000081 (session total: $0.000081)

Context Manager

with CostTracker() as tracker:
    client = tracker.wrap_openai(openai.OpenAI(api_key="..."))
    client.chat.completions.create(...)
# Prints rich summary table on exit

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💰 Supported Models & Pricing

Provider	Model	Input /1M	Output /1M
OpenAI	gpt-4o	$2.50	$10.00
OpenAI	gpt-4o-mini	$0.15	$0.60
OpenAI	gpt-4-turbo	$10.00	$30.00
OpenAI	gpt-3.5-turbo	$0.50	$1.50
Anthropic	claude-opus-4-6	$15.00	$75.00
Anthropic	claude-sonnet-4-6	$3.00	$15.00
Anthropic	claude-haiku-4-5	$0.80	$4.00
Gemini	gemini-1.5-pro	$1.25	$5.00
Gemini	gemini-1.5-flash	$0.075	$0.30
Gemini	gemini-2.0-flash	$0.10	$0.40

Add custom models

from tokenwatch.pricing.tables import add_custom_model
add_custom_model("openai", "gpt-5", input_price_per_1m=10.00, output_price_per_1m=30.00)

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🖥️ CLI

tokenwatch report                    # spend today / month / all time
tokenwatch history --limit 20        # last 20 API calls
tokenwatch history --provider openai # filter by provider
tokenwatch models                    # all supported models + pricing
tokenwatch export --output costs.csv # export to CSV
tokenwatch clear                     # clear database

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🤝 Contributing

TokenWatch is Neurify's first open-source project and we welcome contributions!

1. Fork the repo
2. Create your branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push: git push origin feature/amazing-feature
5. Open a Pull Request

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📄 License

MIT License — see LICENSE for details.

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Made with ❤️ by Neurify — Our first open-source release 🎉