# LaunchDarkly AI SDK for Server-Side JavaScript

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## LaunchDarkly overview

[LaunchDarkly](https://www.launchdarkly.com) is a feature management platform that serves over 100 billion feature flags daily to help teams build better software, faster. [Get started](https://docs.launchdarkly.com/home/getting-started) using LaunchDarkly today!

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## Quick Setup

This assumes that you have already installed the LaunchDarkly Node.js (server-side) SDK, or a compatible edge SDK.

1. Install this package with `npm` or `yarn`:

```shell
npm install @launchdarkly/server-sdk-ai --save
# or
yarn add @launchdarkly/server-sdk-ai
```

2. Create an AI SDK instance:

```typescript
// The ldClient instance should be created based on the instructions in the relevant SDK.
const aiClient = initAi(ldClient);
```

## Setting Default AI Configurations

When retrieving AI configurations, you need to provide default values that will be used if the configuration is not available from LaunchDarkly:

### Fully Configured Default

```typescript
const defaultConfig = {
  enabled: true,
  model: {
    name: 'gpt-4',
    parameters: { temperature: 0.7, maxTokens: 1000 },
  },
  messages: [{ role: 'system', content: 'You are a helpful assistant.' }],
};
```

### Default value

The `defaultValue` parameter is optional. When omitted, a disabled default is used.

## Retrieving AI Configurations

The `completionConfig` method retrieves AI configurations from LaunchDarkly with support for dynamic variables and fallback values:

```typescript
const aiConfig = await aiClient.completionConfig(
  aiConfigKey,
  context,
  defaultConfig,
  { myVariable: 'My User Defined Variable' }, // Variables for template interpolation
);

// Ensure configuration is enabled
if (aiConfig.enabled) {
  const { messages, model, tracker } = aiConfig;
  // Use with your AI provider
}
```

## ManagedModel for Tracked Model Invocations

`ManagedModel` provides a high-level interface for invoking AI models with automatic metrics tracking and judge evaluation:

- Automatically configures models based on AI configuration
- Automatically tracks token usage, latency, and success rates
- Runs configured judges asynchronously and reports their results
- Works with any supported AI provider (see [AI Providers](https://github.com/launchdarkly/js-core#ai-providers) for available packages)

### Using ManagedModel

```typescript
// Use the same defaultConfig from the retrieval section above
const model = await aiClient.createModel('customer-support-chat', context, defaultConfig, {
  customerName: 'John',
});

if (model) {
  // Metrics are automatically tracked by run()
  const result = await model.run('I need help with my order');
  console.log(result.content);

  // Judge evaluations run asynchronously; await if you need their results
  const evals = await result.evaluations;
  console.log('Judge results:', evals);
}
```

## Advanced Usage with Providers

For more control, you can use the configuration directly with AI providers. We recommend using [LaunchDarkly AI Provider packages](https://github.com/launchdarkly/js-core#ai-providers) when available:

### Using AI Provider Packages

```typescript
import { LangChainProvider } from '@launchdarkly/server-sdk-ai-langchain';

const aiConfig = await aiClient.completionConfig(aiConfigKey, context, defaultValue);

// Create LangChain model from configuration
const llm = await LangChainProvider.createLangChainModel(aiConfig);

// Use with tracking
const response = await aiConfig.tracker.trackMetricsOf(
  LangChainProvider.getAIMetricsFromResponse,
  () => llm.invoke(messages),
);

console.log('AI Response:', response.content);
```

### Using Custom Providers

```typescript
import { LDAIMetrics } from '@launchdarkly/server-sdk-ai';

const aiConfig = await aiClient.completionConfig(aiConfigKey, context, defaultValue);

// Define custom metrics mapping for your provider
const mapCustomProviderMetrics = (response: any): LDAIMetrics => ({
  success: true,
  usage: {
    total: response.usage?.total_tokens || 0,
    input: response.usage?.prompt_tokens || 0,
    output: response.usage?.completion_tokens || 0,
  },
});

// Use with custom provider and tracking
const result = await aiConfig.tracker.trackMetricsOf(mapCustomProviderMetrics, () =>
  customProvider.generate({
    messages: aiConfig.messages || [],
    model: aiConfig.model?.name || 'custom-model',
    temperature: aiConfig.model?.parameters?.temperature ?? 0.5,
  }),
);

console.log('AI Response:', result.content);
```

## Contributing

We encourage pull requests and other contributions from the community. Check out our [contributing guidelines](CONTRIBUTING.md) for instructions on how to contribute to this SDK.

## About LaunchDarkly

- LaunchDarkly is a continuous delivery platform that provides feature flags as a service and allows developers to iterate quickly and safely. We allow you to easily flag your features and manage them from the LaunchDarkly dashboard. With LaunchDarkly, you can:
  - Roll out a new feature to a subset of your users (like a group of users who opt-in to a beta tester group), gathering feedback and bug reports from real-world use cases.
  - Gradually roll out a feature to an increasing percentage of users, and track the effect that the feature has on key metrics (for instance, how likely is a user to complete a purchase if they have feature A versus feature B?).
  - Turn off a feature that you realize is causing performance problems in production, without needing to re-deploy, or even restart the application with a changed configuration file.
  - Grant access to certain features based on user attributes, like payment plan (eg: users on the ‘gold’ plan get access to more features than users in the ‘silver’ plan).
  - Disable parts of your application to facilitate maintenance, without taking everything offline.
- LaunchDarkly provides feature flag SDKs for a wide variety of languages and technologies. Check out [our documentation](https://docs.launchdarkly.com/sdk) for a complete list.
- Explore LaunchDarkly
  - [launchdarkly.com](https://www.launchdarkly.com/ 'LaunchDarkly Main Website') for more information
  - [docs.launchdarkly.com](https://docs.launchdarkly.com/ 'LaunchDarkly Documentation') for our documentation and SDK reference guides
  - [apidocs.launchdarkly.com](https://apidocs.launchdarkly.com/ 'LaunchDarkly API Documentation') for our API documentation
  - [blog.launchdarkly.com](https://blog.launchdarkly.com/ 'LaunchDarkly Blog Documentation') for the latest product updates

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