cogslayer 0.2.0

Lightweight Python SDK for LLM cost tracking and attribution. Track every OpenAI, Anthropic, and Gemini call — cost, tokens, latency — by feature, team, and user.

CogsLayer

Know the true cost of every feature you ship.

CogsLayer tracks the direct costs of delivering your software — starting with AI. Attribute spend to features, teams, and models. Cut what's wasted.

Start free at cogslayer.com.

Two ways in

1. Python SDK (2 lines of code)

pip install cogslayer

import cogslayer
from cogslayer.openai import OpenAI

cogslayer.init(api_key="cl_live_xxx", service="my-api")

client = OpenAI()

@cogslayer.track(feature="chat", team="growth")
def ask(prompt: str) -> str:
    resp = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": prompt}],
    )
    return resp.choices[0].message.content

Drop-in replacement clients for OpenAI, Anthropic, and Gemini. Every call is automatically tracked with cost, tokens, latency, and attribution context.

2. Provider integration (60 seconds, zero code)

Paste your OpenAI org key or Anthropic admin key. CogsLayer pulls actual billed costs — not token-based estimates — and syncs automatically.

Supported: OpenAI, Anthropic, Cursor, Claude Code.

Track. Understand. Save.

	What you get
Track	Every call tracked with cost, tokens, and latency. Attribute spend to features, teams, models, and services with @cogslayer.track. Agent sessions grouped automatically.
Understand	Dashboard with spend by team, feature, model, provider. Actual billed costs from provider APIs. Estimate vs. billed drift detection. Budget alerts and forecasting.
Save	Waste detection flags duplicates, retry bloat, and oversized models. Optimization rules with one-click apply. Realized savings ledger proves ROI.

Wrapped clients

OpenAI

from cogslayer.openai import OpenAI, AsyncOpenAI

client = OpenAI()           # exact same API as openai.OpenAI
async_client = AsyncOpenAI()  # exact same API as openai.AsyncOpenAI

Tracks chat.completions.create(), chat.completions.parse(), chat.completions.stream(), and responses.create().

OpenAI-compatible providers

from cogslayer.openai import OpenAI

groq = OpenAI(
    base_url="https://api.groq.com/openai/v1",
    api_key="gsk_...",
    provider="groq",
)

Works with Groq, Together, Fireworks, Ollama, or any OpenAI-compatible API.

Anthropic

from cogslayer.anthropic import Anthropic, AsyncAnthropic

client = Anthropic()

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)

Tracks messages.create() and messages.stream(). Captures cache tokens.

Google Gemini

from cogslayer.gemini import Client

client = Client(api_key="...")

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents="Hello",
)

Tracks models.generate_content() (sync and async). Streaming supported.

What gets tracked

Metric	Description
prompt_tokens	Input tokens
completion_tokens	Output tokens
reasoning_tokens	Thinking tokens (o1, o3, o4-mini)
cached_tokens	Prompt tokens served from cache
cost_usd	Estimated cost from pricing registry
latency_ms	Round-trip time
has_tool_calls	Whether the response included tool calls
api_type	chat / responses / messages / generate

Attribution

Every call is tagged with context from @cogslayer.track():

Field	Description
feature	Product feature (e.g. "chat", "code-review")
team	Owning team (e.g. "engineering", "support")
user_id	End-user identifier
service	Service name (set in init())
environment	"production" / "staging" / etc.

Streaming

Fully supported across all providers. CogsLayer injects stream_options for OpenAI and captures token counts from the final chunk automatically.

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

Custom pricing

cogslayer.register_model(
    "my-fine-tuned-gpt4",
    prompt_price_per_1k=0.006,
    completion_price_per_1k=0.012,
)

Running locally

python -m pip install -e ".[openai,dev]"
python -m pytest tests/ -q

Build the PyPI artifacts with:

python -m build
python -m twine check dist/*

Supported providers

Provider	SDK wrapper	Integration (billed costs)
OpenAI	from cogslayer.openai import OpenAI	Yes
Anthropic	from cogslayer.anthropic import Anthropic	Yes
Google Gemini	from cogslayer.gemini import Client	—
Cursor	—	Yes
Claude Code	—	Yes
Any OpenAI-compatible	OpenAI(base_url=..., provider="groq")	—