LLM Cost Tracker

Self-hosted LLM cost tracking for Rails.

Every call your app makes to OpenAI, Anthropic, Gemini, RubyLLM, or any OpenAI-compatible API gets logged: tokens, cost, latency, tags. Calls go app → provider direct. No proxy.

Not Langfuse, Helicone, or LiteLLM. No prompts, no traces, no replay. Spend attribution only.

Requires Ruby 3.4+, Rails 7.1+, PostgreSQL or MySQL.

Quickstart

# Gemfile
gem "llm_cost_tracker"
gem "openai"

bin/rails llm_cost_tracker:setup

Runs the install generator, drops a price snapshot, migrates the database, and verifies via llm_cost_tracker:doctor.

# config/initializers/llm_cost_tracker.rb
LlmCostTracker.configure do |config|
  config.default_tags = -> { { environment: Rails.env } }
  config.instrument :openai
end

Tag your calls to attribute spend:

LlmCostTracker.with_tags(user_id: Current.user&.id, feature: "chat") do
  client = OpenAI::Client.new(api_key: ENV["OPENAI_API_KEY"])
  client.responses.create(model: "gpt-4o", input: "Hello")
end

Mount the dashboard in config/routes.rb, behind your auth:

authenticate :admin do
  mount LlmCostTracker::Engine => "/llm-costs"
end

The engine ships without authentication on purpose.

What lands in the ledger

• Calls. Provider, model, total tokens, total cost, latency, status.
• Line items. Per-component breakdown — text/audio/cached tokens, tool charges (web search, code execution, grounding, container sessions).
• Tags. Whatever attribution you pass — user, feature, tenant, env.
• Provider IDs. Response, project, API key, workspace — for downstream audits.
• Pricing snapshot. So historical numbers don't drift when prices change.

Capture surfaces

Surface	Path
OpenAI	Official SDK or Faraday
Anthropic	Official SDK or Faraday
Azure OpenAI	Faraday or official SDK (auto-detected on *.openai.azure.com and Foundry *.services.ai.azure.com, both deployments and /openai/v1/...)
Google Gemini	Faraday
RubyLLM	Provider layer
ruby-openai	Faraday
OpenRouter, DeepSeek, Groq, LiteLLM-style gateways	OpenAI-compatible Faraday
Anything else	LlmCostTracker.track

Streams capture when the provider emits final usage. OpenAI Faraday streams need stream_options: { include_usage: true }.

What it isn't

• No proxy. Direct calls only.
• No prompts. Token counts and metadata only.
• No traces, evals, or prompt management. Different product, different gem.
• Not multi-service. Built for a Rails monolith.

Manual tracking

For batch jobs, internal gateways, or anything without an SDK/Faraday hook:

LlmCostTracker.track(
  provider: :anthropic,
  model: "claude-sonnet-4-6",
  tokens: { input: 1500, output: 320 },
  tags: { feature: "summarizer", user_id: current_user.id }
)

Docs

• Configuration
• Pricing
• Budgets
• Data model
• Querying
• Dashboard
• Streaming
• Cookbook
• Extending
• Operations
• Architecture
• EU AI Act record-keeping
• Upgrading
• Changelog

Development

bundle install
bin/check

License

MIT — see LICENSE.txt.