OpenAI

Lightweight, dependency-free, in-memory OpenAI REST API fake for testing code that uses the real openai Node.js/Python SDK (and the language-agnostic OpenAI REST API). All generated content is deterministic — text and embedding vectors are derived from a hash of the input so tests are repeatable.

Default port: 4747

Quick start

Start the server:

import { OpenaiServer } from "./services/openai/src/server.js";

const server = new OpenaiServer(4747);
await server.start();
// ... run your app/tests ...
await server.stop();

Point the real openai client at it via baseURL:

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "sk-parlel",
  baseURL: "http://127.0.0.1:4747/v1",
});

const completion = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "Hello!" }],
});
// completion.choices[0].message.content => deterministic text for that prompt

Implemented operations

All /v1/* routes require an Authorization: Bearer <key> header (any non-empty bearer token is accepted, matching how a local test key behaves). State is in-memory and ephemeral.

• POST /v1/chat/completions — chat completion. Supports stream: true (SSE chunks ending with data: [DONE]). Returns the chat.completion shape with choices[].message (incl. refusal: null), finish_reason, system_fingerprint, and a usage object that includes prompt_tokens_details and completion_tokens_details (matching the real API).
• POST /v1/completions — legacy text completion (text_completion). usage includes the token-detail sub-objects.
• POST /v1/embeddings — deterministic fixed-length embedding vectors (default 1536 dims, dimensions override supported). Accepts a string or array of strings.
• GET /v1/models — list models ({ object: "list", data: [...] }).
• GET /v1/models/{id} — retrieve one model. Unknown model ids return 404 with code: "model_not_found".
• POST /v1/images/generations — image generation. Returns url or b64_json depending on response_format, plus revised_prompt.
• POST /v1/moderations — content moderation. Returns flagged, categories, category_scores, and category_applied_input_types across the full 13-category omni-moderation-latest set (including illicit and illicit/violent).

Service & inspection operations (parlel extensions)

• GET / — service metadata.
• GET /health — health check ({ status: "ok" }).
• POST /__parlel/reset — reset all in-memory state.
• GET /__parlel/requests — list every captured request ({ requests, count }).
• DELETE /__parlel/requests — clear the captured request log.
• OPTIONS * — CORS preflight (204).

SDK usage example

from openai import OpenAI

client = OpenAI(api_key="sk-parlel", base_url="http://127.0.0.1:4747/v1")

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Stream me"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

Access via MCP / preview URL

HTTP services are auto-exposed at the Daytona preview URL. Send requests to the preview URL with the x-daytona-preview-token header for authentication. The OpenAI surface is mounted under /v1, so set OPENAI_BASE_URL to <preview-url>/v1.

Error codes & shapes

Every error uses the real OpenAI envelope: { "error": { "message", "type", "param", "code" } } (all four keys always present; param and code may be null).

Any non-empty Bearer token is accepted (the emulator does not validate real secrets), so a missing/malformed Authorization header is the only auth failure you will see.

Surface coverage

This emulator faithfully replicates the API surface most application code and agents exercise. Anything below the supported lines is either an intentional design choice for a fast, zero-cost local emulator (✓ By design) or a candidate for a future release (⟳ Roadmap) — never a silent inaccuracy.

Legend: ✅ fully supported · ◐ accepted (stored, not strictly enforced) · ✓ by design · ⟳ on the roadmap.

Manifest

See services/openai/manifest.json:

• name: openai, image: parlel/openai:1
• port: 4747, protocol: http, healthcheck: /health, startup ≈ 100ms
• env: OPENAI_API_KEY, OPENAI_BASE_URL

Configuration — test.env

Copy these into your test.env (used by the bridge sidecar flow). Tokens are Parlel's seeded test credentials — any non-empty value is accepted by the emulator, so you rarely need to change them. Swap in real credentials only when pointing at the live service in prod.env.

OPENAI_API_KEY=sk-parlel
OPENAI_BASE_URL=http://parlel-bridge:4747/v1