@inngest/ai

AI adapter package for Inngest, providing type-safe interfaces to various AI providers including OpenAI, Anthropic, Gemini, Grok, and Azure OpenAI.

Installation

``bash
npm install @inngest/ai
`

Usage

`typescript
import { openai, anthropic, gemini } from "@inngest/ai/models";

// Use with Inngest step.ai
const result = await step.ai.infer("Analyze this data", {
model: openai({ model: "gpt-4" }),
body: {
messages: [{ role: "user", content: "What is machine learning?" }],
},
});
`

Development

$3

This package includes comprehensive smoke tests that verify our type definitions work correctly with real AI provider APIs.

#### Unit Tests

Run the standard unit tests (when they exist):

`bash
pnpm test
`

#### Smoke Tests

Smoke tests make actual API calls to AI providers to ensure our type definitions are accurate and complete. Note: These tests will consume API credits and should only be run when needed.

##### Setup

1. Copy the environment example file:

`bash
cp .env.example .env
`

2. Add your API keys to .env:

`bash
# Required for Gemini smoke tests
GEMINI_API_KEY=your_gemini_api_key_here

# Optional: Other providers for future smoke tests
OPENAI_API_KEY=your_openai_api_key_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here
# ... see .env.example for full list
`

##### Running Smoke Tests

`bash


Run all smoke tests (requires API keys)

pnpm test:smoke

Run smoke tests in watch mode for development

pnpm test:smoke:watch
`

##### What Smoke Tests Cover

The smoke tests verify:

- Basic text generation - Simple prompts and responses
- Thinking features - Gemini's reasoning capabilities with thinking budgets
- Structured output - JSON schema validation and response formatting
- Parameter validation - Temperature, token limits, stop sequences, etc.
- Error handling - Invalid API keys and malformed requests
- Token usage tracking - Usage metadata accuracy and completeness
- Advanced features - Multi-candidate generation, sampling parameters

##### Cost Considerations

- Smoke tests are designed to use minimal tokens while thoroughly testing functionality
- Most tests use small maxOutputTokens` limits (50-400 tokens)
- Thinking tests may use more tokens due to internal reasoning

$3

This package provides:

- Type-safe adapters for each AI provider's API format
- Model creators that handle authentication and configuration
- Comprehensive TypeScript definitions with extensive JSDoc documentation
- Developer-friendly interfaces with usage examples and best practices

$3

When adding new AI providers or updating existing ones:

1. Add comprehensive type definitions with JSDoc documentation
2. Include usage examples for complex features
3. Add smoke tests to verify real-world functionality
4. Update this README with any new setup requirements

$3

- OpenAI - GPT models and embeddings
- Anthropic - Claude models
- Google Gemini - Gemini models with thinking features
- Grok - Grok models (OpenAI-compatible)
- Azure OpenAI - Azure-hosted OpenAI models