Getting Started

Installation

npm install @hashbrownai/anthropic --save

You'll also need to install the Anthropic SDK as a peer dependency:

npm install @anthropic-ai/sdk --save

Basic Usage

Deploy an express server with a single /chat endpoint to use Hashbrown with Anthropic.

import { HashbrownAnthropic } from '@hashbrownai/anthropic';

app.post('/chat', async (req, res) => {
  const stream = HashbrownAnthropic.stream.text({
    apiKey: process.env.ANTHROPIC_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();
});

Advanced Usage with Custom Base URL

import { HashbrownAnthropic } from '@hashbrownai/anthropic';

const stream = HashbrownAnthropic.stream.text({
  apiKey: process.env.ANTHROPIC_API_KEY!,
  baseURL: 'https://api.anthropic.com', // Optional custom base URL
  request: {
    model: process.env.ANTHROPIC_MODEL ?? 'claude-haiku-4-5-20251001',
    system: 'You are a helpful assistant.',
    messages: [
      {
        role: 'user',
        content: 'Hello, how are you?',
      },
    ],
    // Optional: Add tools for function calling
    tools: [
      {
        name: 'get_weather',
        description: 'Get the current weather for a location',
        parameters: {
          type: 'object',
          properties: {
            location: {
              type: 'string',
              description: 'The city and state, e.g. San Francisco, CA',
            },
          },
          required: ['location'],
        },
      },
    ],
    toolChoice: 'auto',
    // Optional: Add structured output schema
    responseFormat: {
      type: 'object',
      properties: {
        answer: { type: 'string' },
        confidence: { type: 'number' },
      },
      required: ['answer'],
    },
  },
  // Optional: Transform request options before sending to Anthropic
  transformRequestOptions: (options) => {
    // Modify options as needed
    return {
      ...options,
      max_tokens: 1000, // Override max tokens
    };
  },
});

API Reference

HashbrownAnthropic.stream.text(options)

Creates a streaming text completion using Anthropic's Claude models.

Parameters

• options.apiKey (string, required): Your Anthropic API key
• options.baseURL (string, optional): Custom base URL for Anthropic API
• options.request (Chat.Api.CompletionCreateParams, required): The completion request parameters
• options.transformRequestOptions (function, optional): Function to modify request options before sending

Returns

An async iterable that yields Uint8Array chunks encoded with Hashbrown's frame protocol.

Supported Features

• ✅ Text Streaming: Real-time streaming of text completions
• ✅ Tool Calling: Function calling with automatic tool execution
• ✅ Structured Output: JSON schema validation for responses
• ✅ System Messages: Custom system prompts and instructions
• ✅ Message History: Full conversation context support
• ✅ Error Handling: Proper error propagation through the stream

Models

The adapter supports all Anthropic Claude models. We currently recommend using claude-haiku-4-5-20251001, which is widely available for streaming and tool calling. Switch to newer releases by setting the ANTHROPIC_MODEL environment variable.

Docs

Read the docs for the Hashbrown Anthropic adapter.

Contributing

hashbrown is a community-driven project. Read our contributing guidelines on how to get involved.

Workshops and Consulting

Want to learn how to build web apps with AI? Learn more about our workshops.

LiveLoveApp provides hands-on engagement with our AI engineers for architecture reviews, custom integrations, proof-of-concept builds, performance tuning, and expert guidance on best practices. Learn more about LiveLoveApp.

License

MIT © LiveLoveApp, LLC