Integrations Overview

If your stack can speak the OpenAI API, Xenovia usually fits with a base_url change. Start there unless you need to govern actions that happen outside the model call itself.

Recommended order

Start with the framework your production workload already uses.
If you are unsure, use the OpenAI SDK guide because it maps cleanly to most OpenAI-compatible clients.
Add the Xenovia Python SDK when you need policy checks around downstream actions.

Proxy mode integrations

Xenovia Runtime is an OpenAI-compatible proxy. Any client that accepts a custom base_url works without further changes, and every call passes through Xenovia’s policy and trace pipeline.

https://runtime.xenovia.io/a/{proxy_id}/openai/v1

Provider credentials are configured in the proxy and resolved server-side.

OpenAI SDK

Python and Node.js. Best default starting point for any OpenAI-compatible client.

LangChain

Python and JS chains, agents, and RAG pipelines.

LlamaIndex

RAG pipelines and agentic query engines.

OpenAI Agents SDK

Multi-agent orchestration with the Responses API.

Vercel AI SDK

Next.js and edge streaming.

AutoGen / CrewAI

Multi-agent frameworks that can sit on top of an OpenAI-compatible endpoint.

SDK mode

The Xenovia Python SDK (pip install xenovia-sdk) gates arbitrary agent actions such as tool calls, database writes, API requests, and file operations without proxying an LLM call.

from xenovia_sdk import Xenovia

xenovia = Xenovia(api_key="xe_...", identity_id="billing-agent")

@xenovia.guard(capability="payments.transfer")
def transfer_funds(payload: dict) -> dict:
    return run_transfer(payload["amount"], payload["to"])

result = transfer_funds({"amount": 500, "to": "acct_123"})

Xenovia Python SDK

Full SDK reference for execute(), @guard(), session handling, and error behavior.

Choose the right guide

	Proxy mode	SDK mode
What is governed	Every LLM call through the proxy	Arbitrary agent actions such as tools, writes, and APIs
Code change required	`base_url` swap only	`execute()` call or `@guard()` decorator
Policy input	Full LLM request context	Capability string plus payload
Trace contains	LLM request and response, tokens, latency, tool calls	Capability, payload, decision, and session
Session tracking	Automatic via Xenovia session resolution	Explicit `session_id` or `auto_session=True`

Use both together: proxy mode for LLM governance, SDK mode for downstream tool governance.

If your framework is not listed

If it accepts an OpenAI-compatible base_url, start from the OpenAI SDK guide.
If it only needs HTTP access, point it at https://runtime.xenovia.io/a/{proxy_id}/openai/v1.
If the framework makes risky local calls after the model response, add the Xenovia Python SDK alongside it.

Supported proxy endpoints

Endpoint	Use case
`POST /v1/chat/completions`	Chat, agents, tool calling
`POST /v1/responses`	OpenAI Agents SDK and multi-step runs
`POST /v1/embeddings`	RAG and vector search
`POST /v1/completions`	Legacy text completions

Start Here

Integrations

Platform

Integrations Overview

Recommended order

Proxy mode integrations

OpenAI SDK

LangChain

LlamaIndex

OpenAI Agents SDK

Vercel AI SDK

AutoGen / CrewAI

SDK mode

Xenovia Python SDK

Choose the right guide

If your framework is not listed

Supported proxy endpoints

​Recommended order

​Proxy mode integrations

OpenAI SDK

LangChain

LlamaIndex

OpenAI Agents SDK

Vercel AI SDK

AutoGen / CrewAI

​SDK mode

Xenovia Python SDK

​Choose the right guide

​If your framework is not listed

​Supported proxy endpoints

Recommended order

Proxy mode integrations

SDK mode

Choose the right guide

If your framework is not listed

Supported proxy endpoints