---
title: "WASM Bindings"
description: "Using llms-sdk from the browser via WebAssembly."
---

> Documentation Index
> Fetch the complete documentation index at: https://llms-sdk.cc/llms.txt
> Use this file to discover all available pages before exploring further.

# WASM Bindings

> **Note**
>
> As opposed to the Rust, TS and Python SDKs, WASM bindings do not support built-in retries.

WASM bindings for `llms-sdk`, built with `wasm-bindgen`. Run OpenAI- and Anthropic-compatible chat completions directly in the browser.

## Installation

```bash
npm install @cle-does-things/llms-sdk-wasm
```

The package includes the compiled `.wasm` module and JS glue. Use it with any bundler that supports WASM (Vite, Webpack, Rollup, etc.) or load it directly in the browser.

## Quick start

Import `init` first to load and instantiate the WASM module, then call `chat`:

```javascript
import init, { chat } from "@cle-does-things/llms-sdk-wasm";

await init();

const response = await chat({
  api_type: "openai",
  api_key: "sk-...",
  model: "gpt-5.4-mini",
  messages: [
textmessage("Hello!")
  ],
  stream: false,
  parallel_tool_calls: false,
});

console.log(response.message.content);
```

## Streaming

Use `streamChat` with a callback to receive deltas as they arrive:

```javascript
import init, { streamChat } from "@cle-does-things/llms-sdk-wasm";

await init();

const request = {
  api_type: "openai",
  api_key: "sk-...",
  model: "gpt-5.4-mini",
  messages: [
textmessage("Count to 5")
  ],
  stream: true,
  parallel_tool_calls: false,
};

await streamChat(request, (err, chunk) => {
  if (err) {
console.error("Stream error:", err);
return;
  }

  switch (chunk.type) {
case "delta":
  console.log("Text:", chunk.delta);
  console.log("Done?", chunk.stop);
  break;
case "thinkingDelta":
  console.log("Reasoning:", chunk.delta);
  break;
case "toolDelta":
  console.log("Tool call:", chunk.name, chunk.partial_arguments);
  break;
case "complete":
  console.log("Final message:", chunk.message);
  console.log("Usage:", chunk.usage);
  break;
  }
});
```

## Multimodal input

### Image

```javascript
import { imagePart } from "@cle-does-things/llms-sdk-wasm";

const message = {
  role: "user",
  content: [
{ type: "text", text: "Describe this image." },
imagePart("https://example.com/image.png"),     // URL
// or
imagePart({ bytes: new Uint8Array([...]) }),    // raw bytes
  ],
};
```

### Document (Anthropic only)

```javascript
import { documentPart } from "@cle-does-things/llms-sdk-wasm";

const message = {
  role: "user",
  content: [
{ type: "text", text: "Summarize this document." },
documentPart("https://example.com/doc.pdf"),    // URL
// or
documentPart({ bytes: new Uint8Array([...]) }), // raw bytes
  ],
};
```

### Audio (OpenAI only)

```javascript
import { audioPart } from "@cle-does-things/llms-sdk-wasm";

const message = {
  role: "user",
  content: [
{ type: "text", text: "Transcribe this audio." },
audioPart({ bytes: new Uint8Array([...]) }),    // raw bytes only
  ],
};
```

## Structured output

Pass an `output_format` with a JSON Schema to enforce structured responses:

```javascript
const request = {
  api_type: "openai",
  api_key: "sk-...",
  model: "gpt-5.4-mini",
  messages: [
{ role: "user", content: [{ type: "text", text: "France" }] }
  ],
  stream: false,
  parallel_tool_calls: false,
  output_format: {
name: "capital",
description: "Country capital",
schema: {
  type: "object",
  properties: {
    country: { type: "string" },
    capital: { type: "string" },
  },
  required: ["country", "capital"],
},
  },
};
```

## Tool use

```javascript
const request = {
  api_type: "openai",
  api_key: "sk-...",
  model: "gpt-5.4-mini",
  messages: [
{ role: "user", content: [{ type: "text", text: "What's the weather in Paris?" }] }
  ],
  stream: false,
  parallel_tool_calls: false,
  tools: [
{
  name: "get_weather",
  description: "Return weather for a city.",
  parameters: {
    type: "object",
    properties: {
      city: { type: "string" },
    },
    required: ["city"],
  },
},
  ],
  tool_choice: "auto",
};
```

## Request schema

| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `api_type` | `"openai" \| "anthropic"` | ✅ | Provider type |
| `base_url` | `string` | | Override the default API base URL |
| `api_key` | `string` | ✅ | API key |
| `model` | `string` | ✅ | Model identifier |
| `messages` | `Message[]` | ✅ | Conversation history |
| `max_output_tokens` | `number` | | Maximum tokens to generate |
| `temperature` | `number` | | Sampling temperature |
| `top_p` | `number` | | Nucleus sampling |
| `reasoning_effort` | `ReasoningEffort` | | Control reasoning depth (`none` … `maximum`) |
| `prompt_cache_ttl` | `string` | | Prompt cache TTL hint |
| `stream` | `boolean` | ✅ | Enable streaming |
| `output_format` | `OutputFormat` | | Structured output JSON schema |
| `tools` | `Tool[]` | | Available function tools |
| `tool_choice` | `ToolChoice` | | Tool selection mode (`auto`, `none`, `required`) |
| `parallel_tool_calls` | `boolean` | ✅ | Allow parallel tool calls |

Source: https://llms-sdk.cc/wasm/index.mdx