hashbrown

Getting Started

Guide

  1. 1. Basics of AI
  2. 2. System Instructions
  3. 3. Skillet Schema
  4. 4. Streaming
  5. 5. Tool Calling
  6. 6. Structured Output
  7. 7. Generative UI
  8. 8. JavaScript Runtime

Recipes

  1. Natural Language Forms
  2. UI Chatbot with Tools
  3. Predictive Suggestions
  4. Remote MCP

Platforms

OpenAI (React)

First, install the OpenAI adapter package:

npm install @hashbrownai/openai

Streaming Text Responses

Hashbrown’s OpenAI adapter lets you stream chat completions from OpenAI’s GPT models, including support for tool calling, response schemas, and request transforms.

API Reference

HashbrownOpenAI.stream.text(options)

Streams an OpenAI chat completion as a series of encoded frames. Handles content, tool calls, and errors, and yields each frame as a Uint8Array.

Options:

Name Type Description
apiKey string Your OpenAI API Key.
request Chat.Api.CompletionCreateParams The chat request: model, messages, tools, system, responseFormat, etc.
transformRequestOptions (params) => params | Promise (Optional) Transform or override the final OpenAI request before it is sent.

Supported Features:

  • Roles: user, assistant, tool
  • Tools: Supports OpenAI tool calling, including toolCalls and strict function schemas.
  • Response Format: Optionally specify a JSON schema for structured output (uses OpenAI’s response_format parameter).
  • System Prompt: Included as the first message if provided.
  • Tool Calling: Handles OpenAI tool calling modes and emits tool call frames.
  • Streaming: Each chunk is encoded into a resilient streaming format

How It Works

  • Messages: Translated to OpenAI’s message format, supporting all roles and tool calls.
  • Tools/Functions: Tools are passed as OpenAI function definitions, using your JSON schemas as parameters.
  • Response Format: Pass a JSON schema in responseFormat for OpenAI to validate the model output.
  • Streaming: All data is sent as a stream of encoded frames (Uint8Array). Chunks may contain text, tool calls, errors, or finish signals.
  • Error Handling: Any thrown errors are sent as error frames before the stream ends.

Example: Using with Express

import { HashbrownOpenAI } from '@hashbrownai/openai';

app.post('/chat', async (req, res) => {
  const stream = HashbrownOpenAI.stream.text({
    apiKey: process.env.OPENAI_API_KEY!,
    request: req.body, // must be Chat.Api.CompletionCreateParams
  });

  res.header('Content-Type', 'application/octet-stream');

  for await (const chunk of stream) {
    res.write(chunk); // Pipe each encoded frame as it arrives
  }

  res.end();
});

Transform Request Options

The transformRequestOptions parameter allows you to intercept and modify the request before it's sent to OpenAI. This is useful for server-side prompts, message filtering, logging, and dynamic configuration.

app.post('/chat', async (req, res) => {
  const stream = HashbrownOpenAI.stream.text({
    apiKey: process.env.OPENAI_API_KEY!,
    request: req.body,
    transformRequestOptions: (options) => {
      return {
        ...options,
        // Add server-side system prompt
        messages: [
          { role: 'system', content: 'You are a helpful assistant.' },
          ...options.messages,
        ],
        // Adjust temperature based on user preferences
        temperature: getUserPreferences(req.user.id).creativity,
      };
    },
  });

  // ... rest of the code
});

Learn more about transformRequestOptions


Advanced: Tools and Response Schema

  • Tools: Add tools using OpenAI-style function specs (name, description, parameters).
  • Tool Calling: Supported via toolChoice (auto, required, none, etc.).
  • Response Format: Pass a JSON schema in responseFormat for OpenAI to return validated structured output.
OpenAI (React) Streaming Text Responses API Reference How It Works Example: Using with Express Transform Request Options Advanced: Tools and Response Schema