View Source HyperLLM
Call all LLM APIs using the OpenAI format.
Installation
Add hyper_llm
to your list of dependencies in mix.exs
:
def deps do
[
{:hyper_llm, "~> 0.0.1"}
]
end
Configurations
config :hyper_llm,
openai: [
api_key: "sk-..."
],
anthropic: [
api_key: "sk-..."
]
Usage
HyperLLM.Chat.start(model: "openai/gpt-4o-mini")
|> HyperLLM.Chat.append(:developer, "You are a helpful assistant.")
|> HyperLLM.Chat.append(:user, "Spell \"strawberry\"")
|> HyperLLM.Chat.completion()
#=> {:ok, "Strawberry. 🍓"}
If you are using Phoenix, you can use the HyperLLM.Chat
module in your LiveView.
defmodule ChatLive do
use Phoenix.LiveView
def render(assigns) do
~H"""
<div>
<dl>
<%= for message <- @chat.messages do %>
<dt><%= message.role %></dt>
<dd><%= message.content %></dd>
<% end %>
</dl>
</div>
"""
end
def mount(params, session, socket) do
{:ok,
socket
|> assign(chat: HyperLLM.Chat.start(model: "gpt-4o-mini"))}
end
def handle_event("send_message", %{"message" => message}, socket) do
chat = HyperLLM.Chat.append(socket.assigns.chat, message)
send(self(), :chat_completion)
{:noreply, socket |> assign(chat: chat)}
end
def handle_info(:chat_completion, socket) do
with {:ok, response} <- HyperLLM.Chat.completion(socket.assigns.chat) do
chat = HyperLLM.Chat.append(socket.assigns.chat, :assistant, response)
{:noreply, socket |> assign(chat: chat)}
end
end
end
Providers
✅ Anthropic<br/> ✅ Groq<br/> ✅ OpenAI<br/>
Not implemented ... yet
❌ Azure<br/> ❌ AWS SageMaker<br/> ❌ AWS Bedrock<br/> ❌ Google - Vertex AI<br/> ❌ Google - Palm<br/> ❌ Mistral AI<br/> ❌ CloudFlare AI Workers<br/> ❌ Cohere<br/> ❌ Ollama<br/> ❌ Vertex AI<br/>