Autofix

AI-powered text completion platform with CLI tool, web editor, and Node.js server for seamless writing assistance.

The full API of this library can be found in api.md.

Installation

CLI Tool (Recommended)

npm install -g @harpertoken/autofix-cli

Full System (Development)

git clone https://github.com/harpertoken/autofix.git
cd autofix
npm install
npm run prepare

Docker (Production)

For containerized deployment:

# Pull from Docker Hub
docker pull harpertoken/autofix-server

# Or from GHCR
docker pull ghcr.io/harpertoken/autofix-server

# Run with environment variables
docker run -p 3001:3001 \
  -e GEMINI_API_KEY=your_api_key \
  -e SAMBANOVA_API_KEY=your_samba_key \
  harpertoken/autofix-server

See server README for detailed Docker usage.

Usage

CLI Usage

# Basic completion
autofix "hello this is a"

# With custom style and mode
autofix "write a function to" --style technical --mode sentence

# Create new document with output file
echo "Once upon a time" | autofix new --output story.txt

# Edit existing file
autofix edit myfile.txt --style formal --mode paragraph

Web Editor

npm run dev
# Open http://localhost:3000

Request & Response types

This library includes TypeScript definitions for all request params and response fields. You may import and use them like so:

// POST /api/complete
{
  "text": "hello this is a",
  "mode": "sentence",
  "style": "casual",
  "provider": "auto",
  "geminiModel": "gemini-3-pro-preview"
}

// Response
{
  "suggestion": " test of the AI completion system."
}

Advanced API Usage

# Using curl to test the API
curl -X POST http://localhost:3000/api/complete \
  -H "Content-Type: application/json" \
  -d '{
    "text": "The future of AI is",
    "mode": "sentence",
    "style": "technical",
    "provider": "gemini",
    "geminiModel": "gemini-2.5-flash"
  }'

Status Endpoint

// GET /api/status
{
  "status": "ok",
  "providers": {
    "gemini": true,
    "sambanova": true
  }
}

API Keys Setup

This tool requires AI provider API keys for text completion.

Required: Google Gemini

1. Get a Google Gemini API key
2. Set environment variable:

   export GEMINI_API_KEY=your_api_key_here

Optional: SambaNova (Fallback)

1. Get a SambaNova API key
2. Set environment variable:

   export SAMBANOVA_API_KEY=your_api_key_here

Note

SambaNova provides automatic fallback when Gemini hits rate limits (200 requests/day free tier).

Features

CLI Editor

• Real-time AI text completion
• Multiple completion modes: word, sentence, paragraph
• Writing styles: casual, formal, creative, technical
• Auto-save functionality
• Keyboard shortcuts support

Web Client

• Modern React-based interface
• Live text completion with AI model switching
• Settings panel with craft options and model selection
• Keyboard shortcuts for model switching:
  • Press 1 for gemini-2.5-pro
  • Press 2 for gemini-2.5-flash
  • Press 3 for gemini-2.5-flash-lite
  • Press Escape to dismiss model switch prompt
• Responsive design
• Welcome modal for new users

Server & API

• RESTful API endpoints
• Dual AI provider support
• Automatic fallback system
• Request/response validation
• Error handling and logging

Development

• TypeScript throughout
• Pre-commit hooks (Husky)
• Automated testing (Vitest + Playwright)
• Code formatting (Prettier)
• Semantic release automation

AI Provider Fallback

Autofix uses a smart fallback system for maximum reliability:

1. Primary: Google Gemini (configurable model, defaults to gemini-3-pro-preview)
2. Fallback: SambaNova GPT-OSS-120B (when Gemini rate limited)

The system automatically detects rate limits and switches providers seamlessly. Users can also manually switch Gemini models via keyboard shortcuts in the web editor when suggestions fail.

Rate Limit Handling

// Automatic fallback on 429 errors
if (geminiError.status === 429) {
  return await sambaNovaFallback(text, mode, style);
}

Handling errors

When the library is unable to connect to the API, or if the API returns a non-success status code (i.e., 4xx or 5xx response), a subclass of APIError will be thrown:

const response = await client.search.recommend().catch(async (err) => {
  if (err instanceof Autofix.APIError) {
    console.log(err.status); // 400
    console.log(err.name); // BadRequestError
    console.log(err.headers); // {server: 'nginx', ...}
  } else {
    throw err;
  }
});

Error codes are as follows:

Status Code	Error Type
400	BadRequestError
401	AuthenticationError
403	PermissionDeniedError
404	NotFoundError
422	UnprocessableEntityError
429	RateLimitError
>=500	InternalServerError
N/A	APIConnectionError

Retries

Certain errors will be automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors will all be retried by default.

You can use the maxRetries option to configure or disable this:

// Configure the default for all requests:
const client = new Autofix({
  maxRetries: 0, // default is 2
});

// Or, configure per-request:
await client.complete({
  maxRetries: 5,
});

Timeouts

Requests time out after 1 minute by default. You can configure this with a timeout option:

// Configure the default for all requests:
const client = new Autofix({
  timeout: 20 * 1000, // 20 seconds (default is 1 minute)
});

// Override per-request:
await client.complete({
  timeout: 5 * 1000,
});

On timeout, an APIConnectionTimeoutError is thrown.

Note that requests which time out will be retried twice by default.

Advanced Usage

Accessing raw Response data (e.g., headers)

The "raw" Response returned by fetch() can be accessed through the .asResponse() method on the APIPromise type that all methods return. This method returns as soon as the headers for a successful response are received and does not consume the response body, so you are free to write custom parsing or streaming logic.

You can also use the .withResponse() method to get the raw Response along with the parsed data. Unlike .asResponse() this method consumes the body, returning once it is parsed.

const client = new Autofix();

const response = await client.complete().asResponse();
console.log(response.headers.get('X-My-Header'));
console.log(response.statusText); // access the underlying Response object

const { data: response, response: raw } = await client
  .complete()
  .withResponse();
console.log(raw.headers.get('X-My-Header'));
console.log(response.suggestion);

Logging

Important

All log messages are intended for debugging only. The format and content of log messages may change between releases.

Log levels

The log level can be configured in two ways:

1. Via the AUTOFIX_LOG environment variable
2. Using the logLevel client option (overrides the environment variable if set)

import Autofix from 'autofix';

const client = new Autofix({
  logLevel: 'debug', // Show all log messages
});

Available log levels, from most to least verbose:

• 'debug' - Show debug messages, info, warnings, and errors
• 'info' - Show info messages, warnings, and errors
• 'warn' - Show warnings and errors (default)
• 'error' - Show only errors
• 'off' - Disable all logging

At the 'debug' level, all HTTP requests and responses are logged, including headers and bodies. Some authentication-related headers are redacted, but sensitive data in request and response bodies may still be visible.

Custom logger

By default, this library logs to globalThis.console. You can also provide a custom logger. Most logging libraries are supported, including pino, winston, bunyan, consola, signale, and @std/log. If your logger doesn't work, please open an issue.

When providing a custom logger, the logLevel option still controls which messages are emitted, messages below the configured level will not be sent to your logger.

import Autofix from 'autofix';
import pino from 'pino';

const logger = pino();

const client = new Autofix({
  logger: logger.child({ name: 'Autofix' }),
  logLevel: 'debug', // Send all messages to pino, allowing it to filter
});

Making custom/undocumented requests

This library is typed for convenient access to the documented API. If you need to access undocumented endpoints, params, or response properties, the library can still be used.

Undocumented endpoints

To make requests to undocumented endpoints, you can use client.get, client.post, and other HTTP verbs. Options on the client, such as retries, will be respected when making these requests.

await client.post('/some/path', {
  body: { some_prop: 'foo' },
  query: { some_query_arg: 'bar' },
});

Undocumented request params

To make requests using undocumented parameters, you may use // @ts-expect-error on the undocumented parameter. This library doesn't validate at runtime that the request matches the type, so any extra values you send will be sent as-is.

client.complete({
  // ...
  // @ts-expect-error baz is not yet public
  baz: 'undocumented option',
});

For requests with the GET verb, any extra params will be in the query, all other requests will send the extra param in the body.

If you want to explicitly send an extra argument, you can do so with the query, body, and headers request options.

Undocumented response properties

To access undocumented response properties, you may access the response object with // @ts-expect-error on the response object, or cast the response object to the requisite type. Like the request params, we do not validate or strip extra properties from the response from the API.

Customizing the fetch client

By default, this library expects a global fetch function is defined.

If you want to use a different fetch function, you can either polyfill the global:

import fetch from 'my-fetch';

globalThis.fetch = fetch;

Or pass it to the client:

import Autofix from 'autofix';
import fetch from 'my-fetch';

const client = new Autofix({ fetch });

Fetch options

If you want to set custom fetch options without overriding the fetch function, you can provide a fetchOptions object when instantiating the client or making a request. (Request-specific options override client options.)

import Autofix from 'autofix';

const client = new Autofix({
  fetchOptions: {
    // `RequestInit` options
  },
});

Configuring proxies

To modify proxy behavior, you can provide custom fetchOptions that add runtime-specific proxy options to requests:

Node ^[docs]

import Autofix from 'autofix';
import * as undici from 'undici';

const proxyAgent = new undici.ProxyAgent('http://localhost:8888');
const client = new Autofix({
  fetchOptions: {
    dispatcher: proxyAgent,
  },
});

Bun ^[docs]

import Autofix from 'autofix';

const client = new Autofix({
  fetchOptions: {
    proxy: 'http://localhost:8888',
  },
});

Deno ^[docs]

import Autofix from 'npm:autofix';

const httpClient = Deno.createHttpClient({
  proxy: { url: 'http://localhost:8888' },
});
const client = new Autofix({
  fetchOptions: {
    client: httpClient,
  },
});

Requirements

• Node.js: 20 LTS or later
• npm: 9+
• AI API Keys: At least one provider key required

Supported Runtimes

• Node.js 20+
• Modern web browsers
• Vercel (deployment)
• Local development

Development Tools

• Playwright: E2E testing
• Vitest: Unit testing
• TypeScript: Type checking
• Prettier: Code formatting
• Husky: Git hooks

Development

Setup

git clone https://github.com/harpertoken/autofix.git
cd autofix
npm install
npm run prepare

Available Scripts

npm run dev          # Start development server
npm run build        # Build for production
npm run check        # TypeScript type checking
npm run test         # Run unit tests
npm run test:e2e     # Run E2E tests
npm run format       # Format code with Prettier
npm run preflight    # Run all checks (format, check, test, build)

Project Structure

autofix/
├── apps/
│   ├── cli/          # Command-line interface
│   ├── client/       # React web application
│   └── server/       # Node.js API server
├── packages/
│   └── shared/       # Shared utilities and types
├── tests/            # Test files
└── scripts/          # Build and utility scripts

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Make your changes with tests
4. Run preflight: npm run preflight
5. Commit with conventional format: git commit -m "feat: add new feature"
6. Push and open a PR

Commit Convention

This project uses Conventional Commits:

• feat: - New features
• fix: - Bug fixes
• docs: - Documentation
• style: - Code style changes
• refactor: - Code refactoring
• test: - Testing
• chore: - Maintenance

Release Process

Releases are automated using semantic-release:

• Push to main triggers release
• Version bumps based on commit messages
• NPM publishing for CLI package
• GitHub releases with changelogs

Troubleshooting

Common Issues

Problem	Solution
GEMINI_API_KEY required	Get key from Google AI Studio
Rate limit errors	Add SAMBANOVA_API_KEY for fallback
No suggestions in web app	Press 1,2,3 keys to switch Gemini models
CLI not found	Run npm install -g @harpertoken/autofix-cli
Web app not loading	Check npm run dev output
Build failures	Run npm run preflight to check all issues

Debug Mode

Enable verbose logging:

DEBUG=autofix:* npm run dev

Frequently Asked Questions

Semantic versioning

This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

1. Changes that only affect static types, without breaking runtime behavior.
2. Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals.)
3. Changes that we do not expect to impact the vast majority of users in practice.

We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.

We are keen for your feedback; please open an issue with questions, bugs, or suggestions.

License

MIT - See LICENSE file for details.

Related Projects

• Google Gemini - Primary AI provider
• SambaNova - Fallback AI provider