OpenAI SDK

Open Interpreter does not maintain a separate SDK. It is a drop-in replacement for Codex surfaces, so SDK integrations should use OpenAI's Codex SDK and point the launched agent process at Open Interpreter.

Use the upstream SDK docs for the complete API:

Python App-Server SDK

For Python integrations that use codex_app_server, launch interpreter-app-server instead of codex app-server.

from codex_app_server import AppServerConfig, Codex

oi_server = AppServerConfig(
    launch_args_override=(
        "interpreter-app-server",
        "--listen",
        "stdio://",
    ),
)

with Codex(config=oi_server) as codex:
    thread = codex.thread_start(
        model_provider="moonshotai",
        model="kimi-k2.5",
        config={"harness": "kimi-cli"},
    )
    result = thread.run("Review this repo and list the first migration step.")
    print(result.final_response)

The important part is the process override. The SDK still speaks the Codex app-server protocol; Open Interpreter supplies the compatible app server.

TypeScript SDK

For TypeScript automation, install OpenAI's SDK and point the binary override at interpreter:

import { Codex } from "@openai/codex-sdk";

const codex = new Codex({
  codexPathOverride: "interpreter",
  config: {
    model_provider: "moonshotai",
    harness: "kimi-cli",
  },
});

const thread = codex.startThread({ model: "kimi-k2.5" });
const result = await thread.run(
  "Review this repo and list the first migration step.",
);

console.log(result);

For OpenAI models, omit the harness override and use the same model names you would use from the CLI.

CI

If you only need one job to run to completion, prefer interpreter exec over embedding the SDK:

interpreter exec \
  -c 'model_provider="moonshotai"' \
  -c 'harness="kimi-cli"' \
  -m "kimi-k2.5" \
  "Review this pull request and report blocking issues."

Use the SDK when you need to keep a thread alive, stream events into an application, handle approvals programmatically, or embed the agent in a larger workflow.

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