glopenai

A sans-IO OpenAI API client for Gleam, ported from the Rust async-openai library.

Sans-IO means glopenai builds HTTP requests and parses HTTP responses, but never sends or receives anything itself. You bring your own HTTP client (gleam_httpc, hackney, fetch, etc.) and call it between the request and response functions. This makes the library transport-agnostic, easy to test, and free of runtime dependencies beyond the Gleam standard library.

Installation

gleam add glopenai

Quick start

import gleam/httpc
import gleam/io
import gleam/option.{Some}
import glopenai/chat
import glopenai/config

pub fn main() {
  let cfg = config.new(api_key: "sk-...")

  // 1. Build the request
  let request =
    chat.new_create_request(model: "gpt-4o-mini", messages: [
      chat.system_message("You are a helpful assistant."),
      chat.user_message("What is the capital of France?"),
    ])
    |> chat.with_max_completion_tokens(256)

  let http_request = chat.create_request(cfg, request)

  // 2. Send it with any HTTP client
  let assert Ok(http_response) = httpc.send(http_request)

  // 3. Parse the response
  let assert Ok(response) = chat.create_response(http_response)

  case response.choices {
    [choice, ..] ->
      case choice.message.content {
        Some(content) -> io.println(content)
        _ -> Nil
      }
    _ -> Nil
  }
}

Every API module follows the same *_request / *_response pattern. Multipart endpoints (file uploads, upload parts) return Request(BitArray) instead of Request(String) – use httpc.send_bits for those.

Origin

glopenai is based on async-openai, the most complete OpenAI client library for Rust. Types, field names, and API coverage were mapped as faithfully as possible from the Rust source, adapted to Gleam conventions (custom types instead of serde enums, Result instead of panics, builder functions instead of derive_builder macros).

API coverage

Available now

Module	API	Highlights
`chat`	Chat Completions	Messages, tools, streaming, web search, structured output
`response`	Responses API	25 input item types, 20 output types, 48 stream events, tools
`model`	Models	List, retrieve, delete
`embedding`	Embeddings	String, array, token, and multi-input variants
`moderation`	Moderations	Text, image, and multi-modal input
`image`	Image Generation	8 sizes, 5 models, URL and base64 responses
`audio`	Audio (TTS)	13 voices, 6 output formats
`file`	Files	List, retrieve, delete, content, and multipart upload
`completion`	Completions (legacy)	4 prompt variants, logprobs, streaming
`fine_tuning`	Fine-tuning	Jobs, events, checkpoints, DPO/reinforcement methods
`batch`	Batch API	Create, retrieve, cancel, list, JSONL helpers
`vector_store`	Vector Stores	Stores, files, batches, search with filters, chunking strategies
`chatkit`	ChatKit	Sessions, threads, items
`upload`	Uploads	Create, add part (multipart), complete, cancel
`webhook`	Webhooks	15 event types, HMAC-SHA256 signature verification
`config`	Configuration	OpenAI and Azure endpoints, custom headers

Not yet ported

Module	Notes
Assistants	Deprecated upstream but still used; large surface area
Video (Sora)	Create, edit, extend, remix
Containers	Container management
Skills	Skill definitions
Evals	Evaluation framework
Admin	Users, projects, API keys, audit logs, invites, roles, usage, and more
Realtime	WebSocket-based; needs a different transport abstraction
Audio transcription/translation	Waiting on multipart integration
Image edit/variation	Waiting on multipart integration
SSE parsing helper	Per-module stream parsers exist; generic helper planned

Compatible APIs

glopenai works with any API that follows the OpenAI HTTP contract. Set config.with_api_base to point at a different endpoint:

let cfg =
  config.new(api_key: "...")
  |> config.with_api_base("http://localhost:11434/v1")  // Ollama

Azure OpenAI is also supported via config.new_azure.

Dependencies

gleam_stdlib >= 0.44.0
gleam_json   >= 3.1.0
gleam_http   >= 4.3.0

No HTTP client dependency. Bring your own.

Development

gleam build   # Compile
gleam test    # Run the test suite

Runnable examples live in dev/example/. Run them with:

OPENAI_API_KEY=sk-... gleam run -m example/chat

License

MIT