🛠️Integration Options for AI Metering

Python SDK: pip install revenium-python-sdk — available on PyPI with extras for each provider. Node.js SDKs: available on npm. Go SDKs: available on GitHub.

Overview

Revenium SDKs wrap your AI provider’s client library to automatically capture token usage, costs, latencies, and metadata — no changes to your API logic required. Data flows to the AI Analytics and Alerts dashboards in real time.

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Python SDK

Install: pip install revenium-python-sdk

The unified Python SDK supports all major AI providers through optional extras. Install only the providers you need:

Provider	Install Command	Chat Completions	Embeddings
OpenAI	pip install "revenium-python-sdk[openai]"	✅	✅
Azure OpenAI	pip install "revenium-python-sdk[openai]"	✅	✅
Anthropic	pip install "revenium-python-sdk[anthropic]"	✅	Anthropic has no embedding models
Anthropic via AWS Bedrock	pip install "revenium-python-sdk[anthropic]"	✅	Anthropic has no embedding models
Google Gemini (AI SDK)	pip install "revenium-python-sdk[google-genai]"	✅	✅
Google Vertex AI (Enterprise)	pip install "revenium-python-sdk[google-vertex]"	✅	✅
LiteLLM	pip install "revenium-python-sdk[litellm]"	✅	✅
LiteLLM Proxy	pip install "revenium-python-sdk[litellm-proxy]"	✅	✅
Ollama	pip install "revenium-python-sdk[ollama]"	✅	✅
Perplexity (OpenAI-compatible)	pip install "revenium-python-sdk[perplexity-openai]"	✅	Perplexity does not currently support embeddings
Perplexity (Native)	pip install "revenium-python-sdk[perplexity-native]"	✅	Perplexity does not currently support embeddings
Fal.ai (image, video, audio metering)	pip install "revenium-python-sdk[fal]"	–	–
LangChain	pip install "revenium-python-sdk[langchain]"	✅	✅

You can install multiple providers at once: pip install "revenium-python-sdk[openai,anthropic,langchain]"

The Python SDK is available on PyPI. Source code and examples are on GitHub.

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Node.js SDKs

Provider	Package	Chat Completions	Embeddings
OpenAI	@revenium/middleware (/openai)	✅	✅
Azure OpenAI	@revenium/middleware (/openai)	✅	✅
Anthropic	@revenium/middleware (/anthropic)	✅	Anthropic has no embedding models
Google Vertex AI (Enterprise)	@revenium/middleware (/google/vertex)	✅	✅
Google AI SDK	@revenium/middleware (/google/genai)	✅	✅
Perplexity	@revenium/middleware (/perplexity)	✅	Perplexity does not currently support embeddings
LiteLLM	@revenium/middleware (/litellm)	✅	✅

All Node.js SDKs are available on npm.

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Go SDKs

Provider	Chat Completions	Embeddings	Image	Video	Audio
OpenAI	✅	✅	–	–	–
Azure OpenAI	✅	✅	–	–	–
Anthropic	✅	Anthropic has no embedding models	–	–	–
Google	✅	✅	–	–	–
Perplexity	✅	Perplexity does not currently support embeddings	–	–	–
Fal.ai	–	–	✅	✅	✅
Runway	–	–	–	✅	–

Go SDKs are available on GitHub.

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LangChain

pip install "revenium-python-sdk[langchain]"

from revenium_middleware.openai.langchain import wrap  # bundled with the OpenAI module
from langchain_openai import ChatOpenAI

llm = wrap(ChatOpenAI(model="gpt-4o"))
response = llm.invoke("Hello from Revenium!")

The wrap() function attaches a callback handler that reports usage data to Revenium's metering API. See the SDK README for additional examples.

For LangChain apps already using OpenTelemetry, see OpenTelemetry Integration as an alternative path.

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Other Framework Integrations

Framework / Platform	Language	Install
n8n – Chat Agent	Node.js	npm
Griptape	Python	Via griptape driver
OpenTelemetry	Any	See OTEL docs

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AI Coding Assistants

Revenium ingests telemetry from AI coding assistants via OpenTelemetry, tracking adoption and usage across your engineering team.

Tool	Status
Claude Code	✅ Supported
Gemini CLI	✅ Supported

Setup: configure the tool's OTLP exporter to point at Revenium — see OpenTelemetry Integration. Usage data appears in the AI Coding Dashboard.

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Multimodal Cost Tracking

Revenium tracks costs across all AI modalities in a single view: Completions, Images, Video, and Audio.

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Using a different SDK or framework? Revenium supports direct API calls and OpenTelemetry for any application. Contact [email protected] for integration assistance.

Using an AI agent? Revenium docs are available in Claude Code, Cursor, Windsurf, and other MCP-compatible agents via Context7. See For AI Agents.

Usage Metadata Reference

Each SDK accepts an optional usage_metadata object for billing, cost attribution, and alerting. The more fields you provide, the more granular your reporting.

Key fields: traceId, taskType, organizationId, subscriptionId, productId, agent, responseQualityScore, subscriber (with id, email, credential).

For field definitions, naming conventions, and examples, see each SDK's documentation on npm or PyPI. For OTEL-based attribution, see the revenium.* attributes in the OpenTelemetry Integration docs.

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Direct API Integration

For complete customization, use the metering API directly:

• Completions API | Images API | Video API | Audio API

• Agent-friendly API documentation

A 201 response does NOT confirm your payload was processed correctly. The metering API returns 201 Created even when your payload contains unrecognized fields. Misspelled or incorrect field names are silently ignored, which can result in $0 cost calculations. Always verify the calculated cost in the AI Analytics dashboard after your first integration.

Common field-name mistakes:

• imageCount (ignored) vs actualImageCount (correct)

• audioLength (ignored) vs audioDurationSeconds (correct)

• stop_reason (ignored) vs stopReason (correct)

Required field: stopReason — For completion metering, the stopReason field is required. Valid values: END, END_SEQUENCE, TOKEN_LIMIT, COST_LIMIT, COMPLETION_LIMIT, ERROR, TIMEOUT, CANCELLED. Omitting this field or sending an invalid value (e.g., MAX_TOKENS, CONTENT_FILTER, STOP) will result in a 400 Bad Request.

Authentication errors return 403, not 401. If your API key is missing or invalid, the metering API returns 403 Forbidden. You will not receive a 401 Unauthorized response.