npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

ollama-experimental

v0.1.41

Published

Ollama Javascript library

Downloads

107

Readme

Ollama JavaScript Library

The Ollama JavaScript library provides the easiest way to integrate your JavaScript project with Ollama.

Getting Started

npm i ollama

Usage

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'llama2',
  messages: [{ role: 'user', content: 'Why is the sky blue?' }],
})
console.log(response.message.content)

Browser Usage

To use the library without node, import the browser module.

import ollama from 'ollama/browser'

Streaming responses

Response streaming can be enabled by setting stream: true, modifying function calls to return an AsyncGenerator where each part is an object in the stream.

import ollama from 'ollama'

const message = { role: 'user', content: 'Why is the sky blue?' }
const response = await ollama.chat({ model: 'llama2', messages: [message], stream: true })
for await (const part of response) {
  process.stdout.write(part.message.content)
}

Create

import ollama from 'ollama'

const modelfile = `
FROM llama2
SYSTEM "You are mario from super mario bros."
`
await ollama.create({ model: 'example', modelfile: modelfile })

API

The Ollama JavaScript library's API is designed around the Ollama REST API

chat

ollama.chat(request)
  • request <Object>: The request object containing chat parameters.

    • model <string> The name of the model to use for the chat.
    • messages <Message[]>: Array of message objects representing the chat history.
      • role <string>: The role of the message sender ('user', 'system', or 'assistant').
      • content <string>: The content of the message.
      • images <Uint8Array[] | string[]>: (Optional) Images to be included in the message, either as Uint8Array or base64 encoded strings.
    • format <string>: (Optional) Set the expected format of the response (json).
    • stream <boolean>: (Optional) When true an AsyncGenerator is returned.
    • keep_alive <string | number>: (Optional) How long to keep the model loaded.
    • options <Options>: (Optional) Options to configure the runtime.
  • Returns: <ChatResponse>

generate

ollama.generate(request)
  • request <Object>: The request object containing generate parameters.
    • model <string> The name of the model to use for the chat.
    • prompt <string>: The prompt to send to the model.
    • system <string>: (Optional) Override the model system prompt.
    • template <string>: (Optional) Override the model template.
    • raw <boolean>: (Optional) Bypass the prompt template and pass the prompt directly to the model.
    • images <Uint8Array[] | string[]>: (Optional) Images to be included, either as Uint8Array or base64 encoded strings.
    • format <string>: (Optional) Set the expected format of the response (json).
    • stream <boolean>: (Optional) When true an AsyncGenerator is returned.
    • keep_alive <string | number>: (Optional) How long to keep the model loaded.
    • options <Options>: (Optional) Options to configure the runtime.
  • Returns: <GenerateResponse>

pull

ollama.pull(request)
  • request <Object>: The request object containing pull parameters.
    • model <string> The name of the model to pull.
    • insecure <boolean>: (Optional) Pull from servers whose identity cannot be verified.
    • stream <boolean>: (Optional) When true an AsyncGenerator is returned.
  • Returns: <ProgressResponse>

push

ollama.push(request)
  • request <Object>: The request object containing push parameters.
    • model <string> The name of the model to push.
    • insecure <boolean>: (Optional) Push to servers whose identity cannot be verified.
    • stream <boolean>: (Optional) When true an AsyncGenerator is returned.
  • Returns: <ProgressResponse>

create

ollama.create(request)
  • request <Object>: The request object containing create parameters.
    • model <string> The name of the model to create.
    • path <string>: (Optional) The path to the Modelfile of the model to create.
    • modelfile <string>: (Optional) The content of the Modelfile to create.
    • stream <boolean>: (Optional) When true an AsyncGenerator is returned.
  • Returns: <ProgressResponse>

delete

ollama.delete(request)
  • request <Object>: The request object containing delete parameters.
    • model <string> The name of the model to delete.
  • Returns: <StatusResponse>

copy

ollama.copy(request)
  • request <Object>: The request object containing copy parameters.
    • source <string> The name of the model to copy from.
    • destination <string> The name of the model to copy to.
  • Returns: <StatusResponse>

list

ollama.list()
  • Returns: <ListResponse>

show

ollama.show(request)
  • request <Object>: The request object containing show parameters.
    • model <string> The name of the model to show.
    • system <string>: (Optional) Override the model system prompt returned.
    • template <string>: (Optional) Override the model template returned.
    • options <Options>: (Optional) Options to configure the runtime.
  • Returns: <ShowResponse>

embeddings

ollama.embeddings(request)
  • request <Object>: The request object containing embedding parameters.
    • model <string> The name of the model used to generate the embeddings.
    • prompt <string>: The prompt used to generate the embedding.
    • keep_alive <string | number>: (Optional) How long to keep the model loaded.
    • options <Options>: (Optional) Options to configure the runtime.
  • Returns: <EmbeddingsResponse>

Custom client

A custom client can be created with the following fields:

  • host <string>: (Optional) The Ollama host address. Default: "http://127.0.0.1:11434".
  • fetch <Object>: (Optional) The fetch library used to make requests to the Ollama host.
import { Ollama } from 'ollama'

const ollama = new Ollama({ host: 'http://localhost:11434' })
const response = await ollama.chat({
  model: 'llama2',
  messages: [{ role: 'user', content: 'Why is the sky blue?' }],
})

Building

To build the project files run:

npm run build