Revised README for Buni (Ollama Client Library)

Buni

Ollama Client Library (Buni)

Buni is a TypeScript-based client API for Ollama, designed to be simple yet flexible. It is intended for use with the Bun JavaScript runtime. Buni should work in Node.js environments, although this has not been extensively tested. Why did I name it buni? idk just liked the name.

Installation

bun add github:nanofuxion/buni

Usage

Creating an Instance

Instantiate OllamaClient with an Options object to connect to the Ollama server:

const client = new OllamaClient({
    host: 'ollama_host',
    port: ollama_port,
    model: 'model_name', // Ollama model name
    // Optional parameters
    template: 'template_name', // Template for Ollama responses
    system: 'system_name', // System name for additional Ollama configurations
    config: modelParameters, // Configuration parameters for Ollama model
    context: contextArray // Context array for Ollama interactions
});

Class Properties

• url: URL of the Ollama server (constructed from host and port).
• model: Name of the Ollama model.
• template (optional): Template name for Ollama responses.
• system (optional): System name for additional Ollama configurations.
• config (optional): Configuration parameters for the Ollama model.
• context (optional): Context array for Ollama interactions.

Methods

async connect()

Establish a connection to the Ollama server. Returns a text response.

setContext(context: number[])

Update the context for the Ollama interactions.

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async generate(options)

Generate an Ollama response based on provided options, which include prompt, raw, config, system, template, and context.

async stream(options)

Stream data from the Ollama server. Options include prompt, raw, config, system, template, context, and a getToken function. This method returns the full response upon stream completion.

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async chat(options)

Initiate a non-streaming chat session with Ollama. Options include messages and config.

async stream_chat(options)

Initiate a streaming chat session with Ollama. Options include messages, config, and getToken. This method returns the message object upon stream completion.

Examples

Connecting to the Server

await client.connect();

Generating an Ollama Response

const response = await client.generate({
    prompt: "Your prompt here",
    raw: false,
    config: yourConfig,
    system: 'yourSystem',
    template: 'yourTemplate',
    context: yourContext
});

const streamResponse = await client.stream({
    prompt: "Your prompt here",
    raw: true,
    config: yourConfig,
    system: 'yourSystem',
    template: 'yourTemplate',
    context: yourContext,
    getToken: yourTokenFunction
});

Engaging in an Ollama Chat

const chatResponse = await client.chat({
    messages: yourMessagesArray,
    config: yourConfig
});

const streamedChatResponse = await client.stream_chat({
    messages: yourMessagesArray,
    config: yourConfig,
    getToken: yourTokenFunction
});

Contribution

Contributions to the Buni Ollama Client Library are welcome. Please ensure that your code aligns with the existing style and includes proper tests and documentation then submit a pull request.

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Note: This README is based on the index.ts file of the Ollama Client Library and may need adjustments to match the actual implementation and use cases of your project. (Readme Partially generated using ChatGPT).