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The AI framework for building declarative and composable AI-powered LLM products.

## Getting Started with @langbase/core
## Getting Started with langbase

### Installation

First, install the `@langbase/core` package using npm or yarn:
First, install the `langbase` package using npm or yarn:

```bash
npm install @langbase/core
npm install langbase
```

or

```bash
pnpm add @langbase/core
pnpm add langbase
```

or

```bash
yarn add @langbase/core
yarn add langbase
```

### Usage

To use the `generate` function from the `@langbase/core` package, follow these steps:
You can `generateText` or `streamText` based on the type of a pipe.

1. **Import the `generate` function**:

```typescript
import {generate} from '@langbase/core';
```
```TypeScript
import 'dotenv/config';
import {Pipe} from 'langbase';

2. **Set up environment variables**:

Ensure you have the following environment variables set in your `.env` file:

```env
OPENAI_API_KEY=your_openai_api_key
```

3. **Generate a response using a prompt**:

```typescript
import {generate} from '@langbase/core';
async function exampleWithPrompt() {
const response = await generate({
model: 'gpt-3.5-turbo-0125',
prompt: '1+1',
});
console.log(response); // Output: '2'
}
exampleWithPrompt();
```

4. **Generate a response using messages array**:

```typescript
import {generate} from '@langbase/core';
async function exampleWithMessages() {
const response = await generate({
model: 'gpt-3.5-turbo-0125',
messages: [
{role: 'system', content: 'You are a helpful assistant.'},
{role: 'user', content: 'Give me 5 title ideas'},
{role: 'assistant', content: 'Sure, here you go … …'},
],
});
console.log(response);
}
exampleWithMessages();
```

## API Reference

### `generate`

Generates a response using the specified model, prompt, or messages array.

#### Signature

```typescript
async function generate(params: GenerateParams): Promise<string>;
```

#### Parameters

- `params`: An object containing the following properties:
- `model` (string): The model to use for generating the response.
- `prompt` (optional string): The prompt to use for generating the response. Either `prompt` or `messages` must be provided.
- `messages` (optional `Message[]`): An array of message objects. Each message object should contain `role` and `content` properties. Either `prompt` or `messages` must be provided.

#### Returns

- A promise that resolves to a string containing the generated response.

#### Example

```typescript
import {generate} from '@langbase/core';
const responseFromPrompt = await generate({
model: 'gpt-3.5-turbo-0125',
prompt: '1+1',
// STREAM: OFF
const pipeStreamOff = new Pipe({
apiKey: process.env.PIPE_LESS_WORDY!,
});

console.log(responseFromPrompt);
const responseFromMessages = await generate({
model: 'gpt-3.5-turbo-0125',
messages: [
{role: 'system', content: 'You are a helpful assistant.'},
{role: 'user', content: 'Give me 5 title ideas'},
{role: 'assistant', content: 'Sure, here you go … …'},
],
const result = await pipeStreamOff.generateText({
messages: [{role: 'user', content: 'Who is Ahmad Awais?'}],
});

console.log(responseFromMessages);
```

### `validateInput`

Validates the input parameters and environment variables.

#### Signature

```typescript
function validateInput(params: GenerateParams): ValidatedParams;
```

#### Parameters

- `params`: An object containing the following properties:
- `model` (string): The model to use for generating the response.
- `prompt` (optional string): The prompt to use for generating the response.
- `messages` (optional `Message[]`): An array of message objects.

#### Returns

- An object containing the validated parameters and environment variables.

#### Example

```typescript
const validatedParams = validateInput({
model: 'gpt-3.5-turbo-0125',
prompt: 'Hi',
});
```

### `buildMessages`

Constructs the messages array using the provided prompt or messages array.

#### Signature

```typescript
function buildMessages({
prompt,
messages,
}: {
prompt?: string;
messages?: Message[];
}): Message[];
```

#### Parameters

- `prompt` (optional string): The prompt to use for generating the response.
- `messages` (optional `Message[]`): An array of message objects.

#### Returns

- An array of message objects.

#### Example

```typescript
const messages = buildMessages({prompt: 'Hi'});
```

### `buildHeaders`

Constructs the headers for the API request using the provided API key.

#### Signature

```typescript
function buildHeaders(API_KEY: string): Record<string, string>;
```

#### Parameters

- `API_KEY` (string): The API key to use for the request.

#### Returns

- An object containing the headers for the API request.

#### Example

```typescript
const headers = buildHeaders('your-api-key');
```

### `handleResponse`

Processes the API response and extracts the generated message content.

#### Signature

```typescript
async function handleResponse(response: Response): Promise<string>;
```

#### Parameters

- `response` (Response): The response object from the API request.

#### Returns

- A promise that resolves to a string containing the generated message content.

#### Example

```typescript
const content = await handleResponse(response);
```

## Types
console.log(result.completion);

### `GenerateParams`

Type definition for the parameters of the `generate` function.

```typescript
interface GenerateParams {
model: string;
prompt?: string;
messages?: Message[];
}
```

### `Message`

Type definition for a message object.

```typescript
interface Message {
role: 'system' | 'user' | 'assistant';
content: string;
}
```

### `ValidatedEnv`

Type definition for the validated environment variables.

```typescript
interface ValidatedEnv {
API_KEY: string;
API_URL_CHAT: string;
}
```

## Environment Variables

### `OPEN_AI_API_KEY`

The API key for authenticating requests to the OpenAI API.

### `OPEN_AI_API_URL_CHAT`

The URL for the OpenAI API chat endpoint.

## Example Usage

```typescript
import {generate} from '@langbase/core';
const responseFromPrompt = await generate({
model: 'gpt-3.5-turbo-0125',
prompt: '1+1',
// STREAM: ON
const pipeStreaming = new Pipe({
apiKey: process.env.PIPE_LESS_WORDY_STREAM!,
});

console.log(responseFromPrompt);
const responseFromMessages = await generate({
model: 'gpt-3.5-turbo-0125',
messages: [
{role: 'system', content: 'You are a helpful assistant.'},
{role: 'user', content: 'Give me 5 title ideas'},
{role: 'assistant', content: 'Sure, here you go … …'},
],
const stream = await pipeStreaming.streamText({
messages: [{role: 'user', content: 'Who is Ahmad Awais?'}],
});

console.log(responseFromMessages);
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content || '');
}
```

This documentation provides a comprehensive guide for getting started with the `@langbase/core` package, as well as a detailed API reference for the `generate` function and its related components.

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