@memberjunction/ai-ollama

MemberJunction AI provider for Ollama, enabling integration with locally-hosted open-source models. This package provides both LLM and embedding capabilities through Ollama's local inference server.

Architecture

graph TD
    A["OllamaLLM<br/>(Provider)"] -->|extends| B["BaseLLM<br/>(@memberjunction/ai)"]
    C["OllamaEmbeddings<br/>(Provider)"] -->|extends| D["BaseEmbeddings<br/>(@memberjunction/ai)"]
    A -->|wraps| E["Ollama Client<br/>(ollama SDK)"]
    C -->|wraps| E
    E -->|connects to| F["Ollama Server<br/>(localhost:11434)"]
    F -->|runs| G["Local Models<br/>(Llama, Mistral, etc.)"]
    B -->|registered via| H["@RegisterClass"]
    D -->|registered via| H

    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:#2d8659,stroke:#1a5c3a,color:#fff
    style G fill:#b8762f,stroke:#8a5722,color:#fff
    style H fill:#b8762f,stroke:#8a5722,color:#fff

Features

• Local Model Hosting: Run AI models locally via Ollama without cloud dependencies
• Chat Completions: Full conversational AI with any Ollama-hosted model
• Embeddings: Local text embeddings through Ollama's embedding API
• Streaming: Real-time response streaming
• Multimodal Support: Image input support for vision-capable models
• Privacy: All data stays on your local infrastructure
• No API Key Required: Connects to local Ollama server
• Configurable Endpoint: Support for custom host configuration

Installation

npm install @memberjunction/ai-ollama

Usage

Chat Completion

import { OllamaLLM } from '@memberjunction/ai-ollama';

const llm = new OllamaLLM('not-used'); // API key not needed for local

const result = await llm.ChatCompletion({
    model: 'llama3.1',
    messages: [
        { role: 'system', content: 'You are a helpful assistant.' },
        { role: 'user', content: 'Explain how Ollama works.' }
    ],
    temperature: 0.7
});

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

Streaming

const result = await llm.ChatCompletion({
    model: 'llama3.1',
    messages: [{ role: 'user', content: 'Write a short story.' }],
    streaming: true,
    streamingCallbacks: {
        OnContent: (content) => process.stdout.write(content),
        OnComplete: () => console.log('\nDone!')
    }
});

Embeddings

import { OllamaEmbeddings } from '@memberjunction/ai-ollama';

const embedder = new OllamaEmbeddings('not-used');

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

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

Prerequisites

1. Install Ollama
2. Pull a model: ollama pull llama3.1
3. Ollama server starts automatically on port 11434

Configuration

The default endpoint is http://localhost:11434. Configure via SetAdditionalSettings for custom hosts.

Supported Features

| Feature | Supported | Notes | |---------|-----------|-------| | stopSequences | Yes | Custom stop sequences | | assistantPrefill | Yes | Pre-seed the assistant's response (guide) | | streaming | Yes | Real-time streaming |

Class Registration

• OllamaLLM -- Registered via @RegisterClass(BaseLLM, 'OllamaLLM')
• OllamaEmbeddings -- Registered via @RegisterClass(BaseEmbeddings, 'OllamaEmbeddings')

Dependencies

• @memberjunction/ai - Core AI abstractions
• @memberjunction/global - Class registration
• ollama - Official Ollama SDK