@memberjunction/ai-openai

MemberJunction AI provider for OpenAI. This is the foundational LLM provider in MemberJunction, implementing BaseLLM and BaseEmbeddings from @memberjunction/ai. Many other providers (Groq, Cerebras, Fireworks, OpenRouter, LMStudio, xAI) extend this package since they use OpenAI-compatible APIs.

Architecture

graph TD
    A["OpenAILLM<br/>(Provider)"] -->|extends| B["BaseLLM<br/>(@memberjunction/ai)"]
    C["OpenAIEmbedding<br/>(Provider)"] -->|extends| D["BaseEmbeddings<br/>(@memberjunction/ai)"]
    A -->|wraps| E["OpenAI SDK<br/>(openai npm)"]
    C -->|wraps| E
    A -->|provides| F["Chat + Streaming"]
    A -->|provides| G["Thinking Extraction"]
    A -->|provides| H["JSON / Response<br/>Format Control"]
    B -->|registered via| I["@RegisterClass"]
    D -->|registered via| I

    subgraph Subclasses["OpenAI-Compatible Subclasses"]
        J["GroqLLM"]
        K["CerebrasLLM"]
        L["FireworksLLM"]
        M["OpenRouterLLM"]
        N["LMStudioLLM"]
        O["xAILLM"]
    end
    J -->|extends| A
    K -->|extends| A
    L -->|extends| A
    M -->|extends| A
    N -->|extends| A
    O -->|extends| A

    style A fill:#7c5295,stroke:#563a6b,color:#fff
    style C fill:#7c5295,stroke:#563a6b,color:#fff
    style B fill:#2d6a9f,stroke:#1a4971,color:#fff
    style D fill:#2d6a9f,stroke:#1a4971,color:#fff
    style E fill:#2d8659,stroke:#1a5c3a,color:#fff
    style F fill:#b8762f,stroke:#8a5722,color:#fff
    style G fill:#b8762f,stroke:#8a5722,color:#fff
    style H fill:#b8762f,stroke:#8a5722,color:#fff
    style I fill:#b8762f,stroke:#8a5722,color:#fff

Features

• Chat Completions: Full support for GPT-4, GPT-4o, o1, o3, and other OpenAI models
• Streaming: Real-time response streaming with chunk processing
• Thinking/Reasoning: Extraction of thinking content from <think> blocks in reasoning model responses
• Embeddings: Text embedding generation via OpenAI embedding models
• Multimodal Input: Support for text and image content in messages
• Response Formats: JSON mode, text, and other format controls
• Effort Level: Maps MJ effort levels to OpenAI reasoning effort parameters
• Error Analysis: Integrated error analysis via ErrorAnalyzer
• Extensible Base: Designed as the foundation for OpenAI-compatible providers

Installation

npm install @memberjunction/ai-openai

Usage

Chat Completion

import { OpenAILLM } from '@memberjunction/ai-openai';

const llm = new OpenAILLM('your-openai-api-key');

const result = await llm.ChatCompletion({
    model: 'gpt-4o',
    messages: [
        { role: 'system', content: 'You are a helpful assistant.' },
        { role: 'user', content: 'Explain quantum computing.' }
    ],
    temperature: 0.7,
    maxOutputTokens: 1000
});

if (result.success) {
    console.log(result.data.choices[0].message.content);
}

Streaming

const result = await llm.ChatCompletion({
    model: 'gpt-4o',
    messages: [{ role: 'user', content: 'Write a detailed essay.' }],
    streaming: true,
    streamingCallbacks: {
        OnContent: (content) => process.stdout.write(content),
        OnComplete: (result) => console.log('\nDone!')
    }
});

Embeddings

import { OpenAIEmbedding } from '@memberjunction/ai-openai';

const embedder = new OpenAIEmbedding('your-openai-api-key');

const result = await embedder.EmbedText({
    text: 'Sample text for embedding',
    model: 'text-embedding-3-small'
});

console.log(`Dimensions: ${result.vector.length}`);

Supported Parameters

| Parameter | Supported | Notes | |-----------|-----------|-------| | temperature | Yes | 0.0 - 2.0 | | maxOutputTokens | Yes | Maximum tokens to generate | | topP | Yes | Nucleus sampling | | frequencyPenalty | Yes | -2.0 to 2.0 | | presencePenalty | Yes | -2.0 to 2.0 | | seed | Yes | Deterministic outputs | | stopSequences | Yes | Custom stop sequences | | responseFormat | Yes | JSON, text modes | | streaming | Yes | Real-time streaming | | effortLevel | Yes | Maps to reasoning_effort | | topK | No | Not supported by OpenAI | | minP | No | Not supported by OpenAI |

Extending for Compatible APIs

This provider is designed as a base class for any OpenAI-compatible API. To create a new provider, override the base URL:

import { OpenAILLM } from '@memberjunction/ai-openai';
import { RegisterClass } from '@memberjunction/global';
import { BaseLLM } from '@memberjunction/ai';

@RegisterClass(BaseLLM, 'MyProviderLLM')
export class MyProviderLLM extends OpenAILLM {
    constructor(apiKey: string) {
        super(apiKey);
        // Override the base URL
        this._openai = new OpenAI({
            apiKey: apiKey,
            baseURL: 'https://api.my-provider.com/v1'
        });
    }
}

Class Registration

• OpenAILLM -- Registered via @RegisterClass(BaseLLM, 'OpenAILLM')
• OpenAIEmbedding -- Registered via @RegisterClass(BaseEmbeddings, 'OpenAIEmbedding')

Dependencies

• @memberjunction/ai - Core AI abstractions
• @memberjunction/global - Class registration
• openai - Official OpenAI SDK