veritas-sdk 0.1.2

AI cost attribution and change detection for developers

Veritas

AI cost observability for developers. Track token usage, costs, and latency across every LLM call — automatically. Spot cost regressions before they hit production.

pip install veritas-sdk[anthropic]
# or
pip install veritas-sdk[openai]
# or
pip install veritas-sdk[all]

---

What it does

Veritas wraps your existing Anthropic or OpenAI client with a transparent proxy. Every API call is tracked silently in the background — your application code stays identical.

For every call, Veritas captures:

Field	Description
feature	The feature name you assign
model	Model used (e.g. claude-3-haiku, gpt-4o-mini)
tokens_in / tokens_out	Input and output token counts
cost_usd	Computed cost based on current pricing
latency_ms	End-to-end request time
code_version	Current git commit hash — auto-detected

Events are sent to your Veritas dashboard where you can track spend over time, break costs down by feature, and automatically detect cost regressions between code versions.

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Dashboard

Sign up free at web-production-82424.up.railway.app

Overview

The main dashboard shows your total spend, call volume, token usage, and average latency — with a week-over-week health banner that tells you if costs are rising or stable.

Cost by Commit

Every event is tagged with the git commit hash it ran on — automatically, with no configuration. The commit chart lets you see exactly which code version changed your costs.

Regression Detection

The regressions page automatically compares your two most recent commits across every tracked feature — no manual commit entry. Red rows = cost went up.

Trends

30-day cost and call volume trends with projected monthly spend and week-over-week comparison.

Feature Analytics

Break down costs by feature — total spend, average cost per call, error rate, and percentage share of your total AI bill.

Model Analytics

See which models you're spending on and how token usage is distributed across them.

---

Quickstart

1. Sign up and get your API key

Create a free account, then go to Settings to create a project and get your API key.

2. Configure

import veritas

veritas.init(
    api_key="sk-vrt-your-key-here",
    endpoint="https://web-production-82424.up.railway.app/api/v1/events",
)

Or use environment variables — Veritas auto-configures on import:

VERITAS_API_KEY=sk-vrt-your-key-here
VERITAS_API_URL=https://web-production-82424.up.railway.app/api/v1/events

3. Wrap your client

Anthropic:

import anthropic
import veritas

veritas.init(api_key="sk-vrt-...", endpoint="https://web-production-82424.up.railway.app/api/v1/events")

client = veritas.Anthropic(
    anthropic.Anthropic(),
    feature_name="chat_search",   # group calls by feature in the dashboard
)

response = client.messages.create(
    model="claude-3-haiku-20240307",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)
# ^ tracked automatically — response is unchanged

OpenAI:

import openai
import veritas

veritas.init(api_key="sk-vrt-...", endpoint="https://web-production-82424.up.railway.app/api/v1/events")

client = veritas.OpenAI(
    openai.OpenAI(),
    feature_name="summarizer",
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)

Streaming works too — just pass stream=True as normal.

4. Use the @track decorator (alternative)

from veritas import track

@track(feature="document_summary")
def summarize(text: str):
    return anthropic_client.messages.create(...)   # any call that returns usage data

---

CLI — Compare commits

After collecting data, compare any two commits from the terminal:

veritas diff --feature chat_search --from abc1234 --to def5678

---------------------------------------------------------------
Metric          |Commit A (Base)  |Commit B (Target)|Delta
---------------------------------------------------------------
Samples         |120              |134              |-
Avg Cost/Req    |$0.000412        |$0.000589        |$0.000177 (42.96%)
Avg Tokens In   |312.4            |451.2            |138.8
Avg Tokens Out  |89.1             |112.3            |23.2
---------------------------------------------------------------

Verdict:
❌ REGRESSION DETECTED: Cost increased beyond acceptable thresholds.

Exits with code 1 on regression — drop it straight into CI:

# .github/workflows/cost-check.yml
- name: Check cost regression
  run: veritas diff --feature chat_search --from ${{ github.event.before }} --to ${{ github.sha }}

---

Safety guarantees

• Never crashes your app — all tracking is fire-and-forget; exceptions are swallowed silently
• No prompt data transmitted — only metadata (tokens, cost, latency, model, commit hash)
• Async-safe — uses asyncio.to_thread in async contexts so the event loop is never blocked
• Zero-config git integration — commit hash is auto-detected via git rev-parse

---

Requirements

• Python 3.9+
• requests (for HTTP sink)
• anthropic>=0.39 (if using veritas-sdk[anthropic])
• openai>=1.0.0 (if using veritas-sdk[openai])

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Links

• GitHub
• Dashboard