Quickstart

Use this page when your application already calls the OpenAI SDK. The wrappers keep the OpenAI client shape and add Averta checkpoints around supported calls.

Install

npm install openai @averta-security/sdk-openai

yarn add openai @averta-security/sdk-openai

pnpm add openai @averta-security/sdk-openai

python3 -m venv .venv
. .venv/bin/activate
python3 -m pip install "openai>=2" -e packages/python-core -e packages/python-openai

Python support is source-install only until averta-openai is published to PyPI. Run the Python install command from the SDK repository.

export OPENAI_API_KEY="your-openai-key"
export AVERTA_API_KEY="your-averta-key"

The OpenAI wrapper reads AVERTA_API_KEY from the environment. Pass avertaApiKey or averta_api_key only when this client should use a different Averta key.

Wrap the Client

import OpenAI from "openai";
import { wrapOpenAI } from "@averta-security/sdk-openai";

let client = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY!,
});

client = wrapOpenAI(client);

import os

from openai import OpenAI
from averta_openai import wrap_openai

client = wrap_openai(OpenAI(api_key=os.environ["OPENAI_API_KEY"]))

Do not wrap the same OpenAI client twice. Create a fresh OpenAI client for each distinct Averta configuration.

Send a Tool-capable Request

const tools = [
  {
    type: "function" as const,
    name: "search_docs",
    description: "Search the internal support documentation.",
    strict: true,
    parameters: {
      type: "object",
      properties: {
        query: { type: "string" },
      },
      required: ["query"],
      additionalProperties: false,
    },
  },
];

const response = await client.responses.create({
  model: process.env.OPENAI_MODEL ?? "gpt-5.4-mini",
  input: "Search the docs for password reset guidance.",
  tools,
});

tools = [
    {
        "type": "function",
        "name": "search_docs",
        "description": "Search the internal support documentation.",
        "strict": True,
        "parameters": {
            "type": "object",
            "properties": {"query": {"type": "string"}},
            "required": ["query"],
            "additionalProperties": False,
        },
    }
]

response = client.responses.create(
    model=os.environ.get("OPENAI_MODEL", "gpt-5.4-mini"),
    input="Search the docs for password reset guidance.",
    tools=tools,
)

At this point Averta has run the request checkpoint. If policy returns restrict_tools, the wrapper forwards only the allowed tools to OpenAI.

Continue the Tool Loop

OpenAI function calls include a call_id. Use that value when you send the result back.

const functionCall = response.output.find(
  (item) => item.type === "function_call"
);

if (functionCall) {
  const nextResponse = await client.responses.create({
    model: process.env.OPENAI_MODEL ?? "gpt-5.4-mini",
    input: [
      ...response.output,
      {
        type: "function_call_output",
        call_id: functionCall.call_id,
        output: JSON.stringify({
          matches: ["Password reset links expire after 24 hours."],
        }),
      },
    ],
    tools,
  });

  console.log(nextResponse.output_text);
}

function_call = next(
    (item for item in response.output if item.type == "function_call"),
    None,
)

if function_call:
    next_response = client.responses.create(
        model=os.environ.get("OPENAI_MODEL", "gpt-5.4-mini"),
        input=[
            *response.output,
            {
                "type": "function_call_output",
                "call_id": function_call.call_id,
                "output": '{"matches":["Password reset links expire after 24 hours."]}',
            },
        ],
        tools=tools,
    )

    print(next_response.output_text)

When the continuation request is sent, Averta evaluates the tool result before OpenAI sees it.

Confirm Decisions

With an allowing policy and a tool call, Events should show a sequence like:

request -> tool_call -> tool_result -> output

The exact sequence depends on whether the model calls a tool. A request with no tool call can skip tool_call and tool_result. The SDK generates requestId and traceId automatically; pass requestContext only when you need your own conversationId, requestId, or traceId.

Runnable Example

The SDK repository includes runnable OpenAI examples:

cp examples/.env.example examples/.env
npm --prefix examples/openai/basic install
npm run example:openai:basic:start

cp examples/.env.example examples/.env
python3 -m venv .venv
. .venv/bin/activate
python3 -m pip install "openai>=2" -e packages/python-core -e packages/python-openai
npm run example:python:openai:start

Fill OPENAI_API_KEY and AVERTA_API_KEY in examples/.env before running an example.

Chat Completions

The same wrapped client also guards supported Chat Completions calls.

const completion = await client.chat.completions.create({
  model: process.env.OPENAI_MODEL ?? "gpt-5.4-mini",
  messages: [
    {
      role: "user",
      content: "Explain password reset link expiration in one sentence.",
    },
  ],
});

console.log(completion.choices[0]?.message.content);

completion = client.chat.completions.create(
    model=os.environ.get("OPENAI_MODEL", "gpt-5.4-mini"),
    messages=[
        {
            "role": "user",
            "content": "Explain password reset link expiration in one sentence.",
        }
    ],
)

print(completion.choices[0].message.content)

Python Support

Python V1 wraps sync OpenAI clients and guards responses.create(...), responses.create(stream=True, ...), responses.stream(...), chat.completions.create(...), and chat.completions.create(stream=True, ...).

Next Steps

Responses API

See the guarded Responses lifecycle.

Tools

Understand tool exposure and tool-call checks.

Output checks

Evaluate final answers before returning them.

Events

Investigate decisions in the dashboard.

Get Started

Core Concepts

OpenAI

Anthropic

Dashboard

Advanced

Install

Wrap the Client

Send a Tool-capable Request

Continue the Tool Loop

Confirm Decisions

Runnable Example

Chat Completions

Python Support

Next Steps

Responses API

Tools

Output checks

Events

​Install

​Wrap the Client

​Send a Tool-capable Request

​Continue the Tool Loop

​Confirm Decisions

​Runnable Example

​Chat Completions

​Python Support

​Next Steps

Responses API

Tools

Output checks

Events

Install

Wrap the Client

Send a Tool-capable Request

Continue the Tool Loop

Confirm Decisions

Runnable Example

Chat Completions

Python Support

Next Steps